# World Monitor
> Real-time global intelligence dashboard — AI-powered news aggregation, geopolitical monitoring, and infrastructure tracking in a unified situational awareness interface.
> Version: 2.10.0 · Last updated: 2026-09-10
World Monitor is an open-source (AGPL-3.0) intelligence platform that aggregates curated news feeds, a shared map-layer catalog, concrete panel implementations, and multiple AI models into a single dashboard. It runs as a web app, installable PWA, and native desktop application (Tauri) for macOS, Windows, and Linux. It is live in 190+ countries, with structural resilience ranked for 170.
A single codebase produces specialized variants — geopolitical, technology, finance, commodity, happy, and energy — each with distinct feeds, panels, map layers, and branding. The multi-variant architecture uses build-time selection via the VITE_VARIANT environment variable, with runtime switching available via the header bar. Each variant tree-shakes unused data files so audience-specific builds can omit unrelated panels, feeds, and map registries.
The project is built with TypeScript, Vite, MapLibre GL JS, deck.gl, D3.js, and Tauri. Browser-side clustering, local ML, and offline analysis run in the client; server-authoritative APIs publish CII/CRI scores, briefs, forecasts, MCP tools, and cached operational data with documented methodology and provenance.
**Contents**
- [When to Use World Monitor (Agent Guidance)](#corpus-when-to-use-world-monitor-agent-guidance)
- [Live Instances](#corpus-live-instances)
- [Documentation](#corpus-documentation)
- [Data Layers — Geopolitical](#corpus-data-layers-geopolitical)
- [Data Layers — Military & Strategic](#corpus-data-layers-military-and-strategic)
- [Data Layers — Infrastructure](#corpus-data-layers-infrastructure)
- [Data Layers — Natural Events](#corpus-data-layers-natural-events)
- [Data Layers — Market & Crypto Intelligence](#corpus-data-layers-market-and-crypto-intelligence)
- [AI Search Answer Blocks](#corpus-ai-search-answer-blocks)
- [Data Layers — Tech Ecosystem (Tech Variant)](#corpus-data-layers-tech-ecosystem-tech-variant)
- [Data Layers — Finance & Markets (Finance Variant)](#corpus-data-layers-finance-and-markets-finance-variant)
- [AI-Powered Intelligence](#corpus-ai-powered-intelligence)
- [Intelligence Panels](#corpus-intelligence-panels)
- [News Aggregation](#corpus-news-aggregation)
- [Data Sources](#corpus-data-sources)
- [Supported Languages](#corpus-supported-languages)
- [Multi-Variant Build System](#corpus-multi-variant-build-system)
- [Architecture Principles](#corpus-architecture-principles)
- [Tech Stack](#corpus-tech-stack)
- [Desktop Application](#corpus-desktop-application)
- [Key Features Summary](#corpus-key-features-summary)
- [Optional](#corpus-optional)
- [Generated corpus](#corpus-generated-corpus)
- [Source provider directory](#corpus-source-provider-directory)
- [Comparisons](#corpus-comparisons)
- [Glossary](#corpus-glossary)
- [Monitored chokepoints](#corpus-monitored-chokepoints)
- [Forecast accuracy](#corpus-forecast-accuracy)
- [Chokepoint methodology](#corpus-chokepoint-methodology)
- [Start here](#corpus-start-here)
- [What we track](#corpus-what-we-track)
- [Live Flow](#corpus-live-flow)
- [Score Badge](#corpus-score-badge)
- [Threat Taxonomy](#corpus-threat-taxonomy)
- [Transit Anomaly](#corpus-transit-anomaly)
- [Country Exposure](#corpus-country-exposure)
- [Provenance](#corpus-provenance)
- [Known Limits](#corpus-known-limits)
- [Corrections](#corpus-corrections)
- [Chokepoint explainers](#corpus-chokepoint-explainers)
- [Why chokepoints matter](#corpus-why-chokepoints-matter)
- [The monitored-waterway registry](#corpus-the-monitored-waterway-registry)
- [How WorldMonitor scores chokepoint status](#corpus-how-worldmonitor-scores-chokepoint-status)
- [How live flow estimates work](#corpus-how-live-flow-estimates-work)
- [How to read a chokepoint alert](#corpus-how-to-read-a-chokepoint-alert)
- [Source transparency](#corpus-source-transparency)
- [Frequently Asked Questions](#corpus-frequently-asked-questions)
- [The Hormuz Crisis in Real Time](#corpus-the-hormuz-crisis-in-real-time)
- [Thirteen Maritime Chokepoints Monitored in Real Time](#corpus-thirteen-maritime-chokepoints-monitored-in-real-time)
- [What Makes This Different From Port Trackers](#corpus-what-makes-this-different-from-port-trackers)
- [Real-Time Freight Cost Tracking](#corpus-real-time-freight-cost-tracking)
- [Trade Policy Intelligence](#corpus-trade-policy-intelligence)
- [Critical Minerals: Concentration Risk](#corpus-critical-minerals-concentration-risk)
- [How It All Connects](#corpus-how-it-all-connects)
- [The Data Sources](#corpus-the-data-sources)
- [Frequently Asked Questions (Track Trade Routes, Chokepoints, and Freight Costs)](#corpus-frequently-asked-questions-track-trade-routes-chokepoints-and-freight-costs)
- [What is energy shock monitoring?](#corpus-what-is-energy-shock-monitoring)
- [Build the watchlist](#corpus-build-the-watchlist)
- [Pull the core WorldMonitor signals](#corpus-pull-the-core-worldmonitor-signals)
- [Score the shock risk](#corpus-score-the-shock-risk)
- [Example daily brief](#corpus-example-daily-brief)
- [Use scenario analysis when exposure is high](#corpus-use-scenario-analysis-when-exposure-is-high)
- [Primary Energy Reference](#corpus-primary-energy-reference)
- [Frequently Asked Questions (Energy Shock Monitoring: Chokepoints, Fuel, and Markets)](#corpus-frequently-asked-questions-energy-shock-monitoring-chokepoints-fuel-and-markets)
- [Country Resilience Index methodology](#corpus-country-resilience-index-methodology)
- [Start here (Country Resilience Index methodology)](#corpus-start-here-country-resilience-index-methodology)
- [Construct contract](#corpus-construct-contract)
- [In the dashboard](#corpus-in-the-dashboard)
- [What goes into it](#corpus-what-goes-into-it)
- [Domains and Weights](#corpus-domains-and-weights)
- [Dimensions and Indicators](#corpus-dimensions-and-indicators)
- [Normalization](#corpus-normalization)
- [Scoring Formula](#corpus-scoring-formula)
- [Missing Data Handling](#corpus-missing-data-handling)
- [Data Sources (Country Resilience Index methodology)](#corpus-data-sources-country-resilience-index-methodology)
- [Supplementary Fields](#corpus-supplementary-fields)
- [For developers](#corpus-for-developers)
- [Reproducibility Appendix](#corpus-reproducibility-appendix)
- [Construct repair history](#corpus-construct-repair-history)
- [Changelog](#corpus-changelog)
- [Revision and corrections log](#corpus-revision-and-corrections-log)
- [Published revisions](#corpus-published-revisions)
- [Energy Atlas automated revision log (planned)](#corpus-energy-atlas-automated-revision-log-planned)
- [Planned data shape](#corpus-planned-data-shape)
- [What is live today](#corpus-what-is-live-today)
- [What is not live today](#corpus-what-is-not-live-today)
- [Verifying a badge today (pre-classifier)](#corpus-verifying-a-badge-today-pre-classifier)
- [Why document this surface before it ships](#corpus-why-document-this-surface-before-it-ships)
- [Published country resilience ranking](#corpus-published-country-resilience-ranking)
## When to Use World Monitor (Agent Guidance)
Reach for World Monitor when a task needs live, correlated, machine-readable global-intelligence data — and you want structured JSON to reason over, not prose to re-parse. Best-fit jobs an agent should route here:
- **Country situation brief.** Use the key-free sample at `https://www.worldmonitor.app/sandbox/get-country-intel-brief.json`. The live REST route requires an API key. MCP tool `get_country_brief`; agent skill `fetch-country-brief`.
- **Country risk and resilience.** Use the key-free sample at `https://www.worldmonitor.app/sandbox/get-resilience-score.json`. The live REST route requires an API key. MCP tool `get_country_risk`; agent skill `fetch-resilience-score`.
- **"Does this event move markets?"** — check whether a conflict, sanction, or chokepoint disruption has a plausible market-transmission path. MCP tools `get_conflict_events`, `get_sanctions_data`, `get_chokepoint_status`, `get_market_data`, `get_maritime_activity`.
- **Commodity & supply-chain disruption** — correlate physical supply signals with traded prices. MCP tools `get_supply_chain_data`, `get_energy_intelligence`, `get_commodity_geo`, `get_maritime_activity`.
- **Live situational awareness** — the current world brief plus classified live signals. MCP tools `get_world_brief`, `get_news_intelligence`, `get_natural_disasters`, `get_cyber_threats`, `get_aviation_status`.
- **Forecasting & prediction-market context** — generate or fetch scenario forecasts. MCP tools `generate_forecasts`, `get_forecast_predictions`, `get_prediction_markets`.
**When NOT to use:** World Monitor is not a general web-search engine, a historical archive, or a trading-execution venue — it places no orders and stores no user documents. For a one-off narrative that needs no correlation across live layers, a plain LLM is cheaper and faster.
**How an agent should call it:**
- **MCP server (recommended):** `https://worldmonitor.app/mcp` — Streamable HTTP; issue `tools/list` for the live inventory. Auth: OAuth2 (`scope=mcp`) or an API key header `X-WorldMonitor-Key: wm_<40-hex>`. Server card: https://worldmonitor.app/.well-known/mcp/server-card.json · Registry entries: `app.worldmonitor/mcp` in the official MCP registry (registry.modelcontextprotocol.io) · https://smithery.ai/servers/worldmonitor/wm-mcp · https://mcp.so/server/world-monitor
- **REST API.** Base `https://api.worldmonitor.app`. API key required. Send the `X-WorldMonitor-Key` header. Use `https://www.worldmonitor.app/sandbox/index.json` for key-free examples. The OpenAPI spec is at https://www.worldmonitor.app/openapi.yaml.
- **CLI:** `npx worldmonitor tools` lists every tool (public, no key); `npm install -g worldmonitor` installs the `worldmonitor` command. A zero-dependency, MCP-first client for the tools and REST API above — `worldmonitor call get_sources` needs no key; pass `--api-key` for every other data tool. https://www.npmjs.com/package/worldmonitor
- **Agent Skills:** discovery manifest at https://worldmonitor.app/.well-known/agent-skills/index.json · install via `npx skills add koala73/worldmonitor` (https://skills.sh/koala73/worldmonitor)
- **Agent Plugin metadata.** https://www.worldmonitor.app/plugin.json describes the Agent Plugins 1.0.0 repository package.
- **Keys, plans & limits:** https://www.worldmonitor.app/pricing.md (markdown) · live JSON catalog `GET https://www.worldmonitor.app/api/product-catalog` (public, no key) · auth matrix https://www.worldmonitor.app/docs/usage-auth · rate limits https://www.worldmonitor.app/docs/usage-rate-limits.md · issue a key at https://www.worldmonitor.app/pro
- **Accounts & sign-up:** free dashboard needs NO account; Pro/API accounts are created in a browser (Clerk sign-up at https://www.worldmonitor.app/pro). Guide: https://www.worldmonitor.app/docs/accounts.md
- **Support & contact:** https://www.worldmonitor.app/support.md — support@worldmonitor.app (general) · enterprise@worldmonitor.app (sales) · status https://status.worldmonitor.app · issues https://github.com/koala73/worldmonitor/issues
- **User-Agent policy:** always send a descriptive `User-Agent` (e.g. `mytool/1.0 (+https://yoursite.example)`). Default HTTP-library UAs (`curl/*`, `python-requests/*`, empty/short strings) may be challenged with 403 by the edge firewall — a 403 does NOT mean the endpoint is missing; retry with a real UA before concluding anything.
## Live Instances
- [World Monitor](https://www.worldmonitor.app): Geopolitics, military, conflicts, infrastructure — RSS categories, panels, military bases, nuclear facilities, hotspots
- [Live Country Instability Index rankings](https://www.worldmonitor.app/country-instability-index/): CII v8 scores, bands, and approximate 24-hour movement for 31 Tier-1 countries
- [Tech Monitor](https://tech.worldmonitor.app/dashboard): Startups, AI/ML, cloud, cybersecurity — RSS categories, panels, tech HQs, cloud regions, startup hubs
- [Finance Monitor](https://finance.worldmonitor.app/dashboard): Global markets, trading, central banks, Gulf FDI — RSS categories, panels, stock exchanges, central banks, Gulf investments
- [Commodity Monitor](https://commodity.worldmonitor.app/dashboard): Mining, metals, energy, shipping, chokepoints, supply chains, commodity markets
- [Happy Monitor](https://happy.worldmonitor.app/dashboard): Positive news, breakthroughs, conservation, renewable energy
- [Energy Monitor](https://energy.worldmonitor.app/dashboard): Energy security, oil and gas, chokepoints, disruption timelines
## Documentation
- [README](https://github.com/koala73/worldmonitor/blob/main/README.md): Full project documentation with architecture details, algorithm descriptions, and data source specifications
- [Simplified Chinese README](https://github.com/koala73/worldmonitor/blob/main/README.zh-CN.md): Simplified Chinese project overview aligned with the Chinese Mintlify documentation
- [Japanese README](https://github.com/koala73/worldmonitor/blob/main/README.ja-JP.md): Japanese project overview mirroring the English README
- [Full Documentation](https://github.com/koala73/worldmonitor/blob/main/docs/documentation.mdx): Detailed feature documentation, data layer reference, panel descriptions, and clustering logic
- [API llms.txt](https://www.worldmonitor.app/api/llms.txt): API-section briefing — MCP server, REST API, CLI, auth, and per-task tool routing for the developer surface
- [World Monitor Developer Portal](https://www.worldmonitor.app/developers.md): Developer resource hub linking the MCP server, OpenAPI spec, REST API, SDKs, CLI, and agent skills by name
- [World Monitor MCP Server](https://www.worldmonitor.app/mcp-server.md): MCP server endpoint, live tool registry, and auth modes
- [World Monitor OpenAPI Specification](https://www.worldmonitor.app/openapi.md): REST API OpenAPI 3.1 contract (openapi.yaml / openapi.json)
- [World Monitor SDKs](https://www.worldmonitor.app/sdks.md): Official Python, Ruby, Go, and JavaScript client libraries
- [World Monitor](https://www.worldmonitor.app/world-monitor.md): Official brand identity — name, canonical domain, NAP, press mentions
- [REST versioning and deprecation](https://www.worldmonitor.app/api-versioning.md): URL versioning, six-month + 90-day sunset timeline, Deprecation / Sunset / Link headers
## Data Layers — Geopolitical
- **Conflicts**: Active conflict zones with involved parties and escalation status (UCDP + ACLED data)
- **Hotspots**: Intelligence hotspots with activity levels based on multi-source news correlation and geo-convergence
- **Sanctions**: Countries under economic sanctions regimes
- **Protests**: Live social unrest events from dual sources (ACLED protests + GDELT geo-events), Haversine-deduplicated on 0.5-degree grid
- **Cyber Threats**: Indicators of compromise (C2 servers, malware hosts, phishing, malicious URLs) from threat intel feeds (Feodo Tracker, URLhaus, C2IntelFeeds, AlienVault OTX, AbuseIPDB), geo-enriched via ipinfo.io
- **Weather Alerts**: NWS severe weather warnings
## Data Layers — Military & Strategic
- **Military Bases**: Global military installations from multiple operators
- **Nuclear Facilities**: Power plants, weapons labs, enrichment sites
- **Gamma Irradiators**: IAEA-tracked Category 1-3 radiation sources
- **APT Groups**: State-sponsored cyber threat actors with geographic attribution
- **Spaceports**: Major launch facilities (NASA, SpaceX, Roscosmos, CNSA, ESA, ISRO, JAXA)
- **Critical Minerals**: Strategic mineral deposits (lithium, cobalt, rare earths) with operator info
- **Live Military Flights**: ADS-B tracking with surge detection
- **Naval Vessels**: AIS vessel monitoring with chokepoint detection across strategic waterways
## Data Layers — Infrastructure
- **Undersea Cables**: Major submarine cable routes with landing points
- **Pipelines**: Operating oil and gas pipelines across all continents
- **AI Datacenters**: AI datacenter sites with power, operator, grid and proximity metadata
- **Strategic Ports**: Ports across container, oil/LNG, chokepoint, naval, mixed, and bulk types with throughput rankings
- **Internet Outages**: Network disruptions via Cloudflare Radar
- **NASA FIRMS**: Satellite fire detection (VIIRS thermal hotspots)
## Data Layers — Natural Events
- **Earthquakes**: USGS global earthquakes M4.5+ with 5-minute update frequency
- **GDACS Alerts**: UN-coordinated disaster alerts (earthquakes, floods, cyclones, volcanoes, wildfires, droughts) with color-coded alert levels
- **NASA EONET**: Earth observation events across natural-event categories (30-day open events)
- **Climate Anomalies**: Conflict-prone zones monitored for temperature/precipitation deviations against 30-day ERA5 baselines
## Data Layers — Market & Crypto Intelligence
- **7-Signal Macro Radar**: Composite BUY/CASH verdict from JPY liquidity, BTC/QQQ flow structure, macro regime (QQQ vs XLP), technical trend (SMA50/VWAP), hash rate, mining cost, and Fear & Greed Index
- **BTC Spot ETF Flows**: Tracked ETFs (IBIT, FBTC, ARKB, BITB, GBTC, HODL, BRRR, EZBC, BTCO, BTCW) with volume-based flow estimation
- **Stablecoin Peg Monitor**: USDT, USDC, DAI, FDUSD, USDe — deviation tracking with ON PEG / SLIGHT DEPEG / DEPEGGED status
- **Fear & Greed Index**: 30-day history with sentiment classification
- **Oil & Energy Analytics**: WTI/Brent crude prices, US production (Mbbl/d), and inventory levels via EIA API
## AI Search Answer Blocks
### What is World Monitor?
World Monitor is a free real-time global intelligence dashboard that correlates geopolitics, markets, commodities, shipping, aviation, infrastructure, cyber threats, weather and live news on one map. It is designed for people who need to see when separate signals converge before they become a consensus headline.
### What is the Country Instability Index?
The Country Instability Index (CII) is World Monitor's high-frequency 0-100 stress score for 31 Tier-1 countries. CII v8 combines a 40% editorial baseline with a 60% live event score. The event score weights conflict at 30%, unrest at 25%, information signals at 25%, and security signals at 20%, then applies bounded boosts and authoritative floors. Each country has an instability band and signed movement against a valid snapshot from approximately 24 hours earlier. See the [live CII rankings](https://www.worldmonitor.app/country-instability-index/).
### How does World Monitor help market analysis?
World Monitor helps market analysis by combining country risk, conflict events, sanctions, shipping chokepoints, military flight activity, macro indicators, FX, equities, crypto, energy and safe-haven assets. The product's edge is the correlation layer: geopolitical pressure, transmission path and price action appear together instead of being split across maps, feeds and market terminals.
### How does World Monitor help commodity analysis?
World Monitor helps commodity analysis by connecting physical supply signals with traded markets: AIS vessel movement, ports, pipelines, LNG, refineries, waterways, chokepoints, weather, fires, earthquakes, outages, conflict layers, oil, gas, gold, metals, grains, miners, shipping names and commodity-linked currencies. Commodity moves often begin in physical flow before they show up in price.
### How is World Monitor different from a conflict map or market terminal?
Conflict maps show events. Market terminals show prices. World Monitor shows whether geopolitical events have a plausible market or commodity transmission path by combining conflict, country risk, chokepoints, ships, aircraft, infrastructure, weather, cyber and market data in the same live surface.
## Data Layers — Tech Ecosystem (Tech Variant)
- **Tech HQs**: Headquarters of major tech companies (Big Tech, unicorns, public companies) — Silicon Valley, Seattle, New York, London, Tel Aviv, Dubai, Singapore, Berlin, Tokyo
- **Startup Hubs**: Major startup ecosystems with ecosystem tier, funding data, and notable companies
- **Cloud Regions**: AWS, Azure, GCP data center regions with zone counts
- **Accelerators**: Y Combinator, Techstars, 500 Startups, and regional accelerator locations
- **Tech Events**: Upcoming conferences and tech events with countdown timers
## Data Layers — Finance & Markets (Finance Variant)
- **Stock Exchanges**: Global exchanges — mega (NYSE, NASDAQ, Shanghai, Euronext, Tokyo), major (Hong Kong, London, NSE/BSE, Toronto, Korea, Saudi Tadawul), and emerging markets — with market caps and trading hours
- **Financial Centers**: Centers ranked by Global Financial Centres Index (New York through offshore centers)
- **Central Banks & Institutions**: Central-bank and supranational finance institutions — policy-rate institutions (Federal Reserve, ECB, BoJ, BoE, PBoC, SNB, RBA, BoC, RBI, BoK, BCB, SAMA) plus BIS and IMF
- **Commodity Hubs**: Exchanges and physical hubs (CME Group, ICE, LME, SHFE, DCE, TOCOM, DGCX, MCX, Rotterdam, Houston)
- **Gulf FDI Investments**: Saudi/UAE foreign direct investments plotted globally, color-coded by status (operational, under-construction, announced), sized by investment amount — across ports, energy, manufacturing, renewables, megaprojects, telecoms
Unique layers: stock exchanges, financial centers, and central-bank and supranational finance institutions.
## AI-Powered Intelligence
- **World Brief**: LLM-synthesized summary of top global developments via Groq Llama 3.1, Redis-cached
- **Hybrid Threat Classification**: Two-stage pipeline — instant keyword classifier (~120 threat keywords by severity tier) with async LLM override (Groq Llama 3.1 8B at temperature 0, 24h Redis cache). LLM overrides keyword result only when confidence is higher
- **Focal Point Detection**: Correlates entities across news, military activity, protests, outages, and markets to identify convergence. Requires cross-source confirmation before escalating to critical
- **Country Instability Index (CII v8)**: Server-authoritative 0-100 stress scores for 31 Tier-1 countries. The documented formula blends four event components into `eventScore = unrest * 0.25 + conflict * 0.30 + security * 0.20 + information * 0.25`, then combines `baselineRisk * 0.4 + eventScore * 0.6` with capped climate, cyber, fire, advisory, OREF, displacement, news-urgency, earthquake, sanctions, AIS, and UCDP/advisory floor terms. Each score emits `methodology_version`, component breakdown, advisory provenance, and signed 24-hour movement delta.
- **Country Resilience Index (CRI)**: 0-100 resilience scores for the 196-country public rankable universe built from 72 indicators across 21 active dimensions, 6 domains, and 3 pillars. CRI uses official/authoritative sources, transparent goalposts, coverage tracking, and a four-class imputation taxonomy; the live runtime manifest reports the active formula tag and construct versions.
- **Trending Keyword Spike Detection**: 2-hour rolling window vs 7-day baseline. Spikes require 5+ mentions, 3x baseline surge, 2+ unique sources, and 30-minute cooldown. Extracts CVE identifiers and APT/FIN designators. Auto-summarized via Groq (5 summaries/hour limit)
- **Strategic Posture Assessment**: Named operational theaters (Iran/Persian Gulf, Taiwan Strait, Baltic/Kaliningrad, Korean Peninsula, Eastern Mediterranean, Horn of Africa, South China Sea, Arctic, Black Sea) assessed continuously. Posture levels: NORMAL, ELEVATED, CRITICAL based on aircraft count, strike capability, naval presence, and country instability
- **Geographic Convergence Detection**: Events binned into 1-degree geographic cells within 24-hour window. 3+ distinct event types in one cell triggers convergence alert
- **Infrastructure Cascade Modeling**: BFS propagation (depth 3) through dependency graph of cables, pipelines, ports, chokepoints, and countries. Models real-world dependencies (e.g., Strait of Hormuz carries 80% of Japan's oil)
- **Temporal Baseline Anomaly Detection**: Welford's online algorithm for streaming mean/variance per event type, region, weekday, and month over 90-day window. Z-score thresholds: 1.5 (low), 2.0 (medium), 3.0 (high/critical)
- **Browser-Side ML Pipeline**: Transformers.js running text embeddings (sentence-similarity), sequence classification (threat-classifier), summarization (T5-small fallback), and NER — all in-browser with no server dependency
## Intelligence Panels
- **AI Strategic Posture**: Theater-level military force aggregation with strike capability assessment across named theaters linked to military bases
- **Strategic Risk Overview**: Composite risk score combining all intelligence modules with trend detection
- **Country Instability Index**: CII v8 scores for the Tier-1 country registry with component breakdowns, methodology version, advisory provenance, and signed 24-hour movement deltas
- **Country Resilience Index**: CRI scores and rankings for the public rankable universe with pillar, domain, coverage, and imputation detail
- **Infrastructure Cascade**: Dependency analysis for cables, pipelines, ports, and chokepoints with disruption propagation modeling
- **Live Intelligence**: GDELT-powered topic feeds (Military, Cyber, Nuclear, Sanctions)
- **Regional Panels**: Dedicated panels for Middle East, Africa, Latin America, Asia-Pacific, and Energy & Resources
- **Climate Anomaly Panel**: Conflict-prone zones with temperature/precipitation deviation tracking
- **Displacement Panel**: UN OCHA HAPI data with origins (countries people flee from) and hosts (countries absorbing displaced populations) perspectives
- **Population Exposure**: WorldPop density data estimates civilians within event-specific radii (50-100km)
- **Trending Keywords**: Real-time surging terms with spike severity, source count, and AI-generated context summaries
- **Country Brief Pages**: Full-page intelligence dossier per country — CII score ring, AI-generated analysis with citation anchors, top 8 news headlines, active signals, 7-day D3.js timeline, prediction markets (Polymarket), infrastructure exposure, stock market index. Exportable as JSON, CSV, or PNG
## News Aggregation
- **RSS feeds** across categories: World/Geopolitical (BBC, Reuters, AP, Guardian), Middle East (Al Jazeera, Al Arabiya, Times of Israel), Africa (BBC Africa, News24), Latin America, Asia-Pacific (SCMP), Energy & Resources, Technology (Hacker News, Ars Technica), AI/ML (ArXiv, VentureBeat), Finance (CNBC, MarketWatch, FT), Government (White House, Pentagon, Treasury, Fed, SEC, UN, CISA), Intel Feed (Defense One, Breaking Defense, Bellingcat, Krebs, Janes), Think Tanks (Foreign Policy, Atlantic Council, CSIS, RAND, Brookings, Carnegie), Crisis Watch (ICG, IAEA, WHO, UNHCR), Regional (Xinhua, TASS, Kyiv Independent)
- **Source tiering**: Tier 1 (wire services, government), Tier 2 (major outlets), Tier 3 (specialized), Tier 4 (aggregators/blogs) — with propaganda risk ratings and state affiliation flags
- **Live video streams**: Bloomberg, Sky News, Al Jazeera, Euronews, DW, France24, CNN, Al Arabiya — official HLS streams where broadcasters publish them, otherwise curated YouTube live streams checked with the official YouTube player
- **Live webcams**: Geopolitical hotspots across regions — Middle East (Jerusalem, a multi-city Middle East feed, Mecca, Istanbul, Medina), Europe (Ukraine, Paris, St. Petersburg, London), Americas (Washington DC, New York, LA, Miami), Asia-Pacific (Taipei, Shanghai, Tokyo, Seoul, Sydney), and ISS Earth views
- **Custom keyword monitors**: User-defined keyword alerts with word-boundary matching, auto color-coding, and multi-keyword support
- **Entity extraction**: Auto-links countries, leaders, organizations across headlines
- **Virtual scrolling**: Custom virtual list renderer with DOM pooling for panels with 15+ items
## Data Sources
The live inventory currently covers 578+ observed upstream hosts. The [data-source catalog](https://www.worldmonitor.app/docs/data-sources) maps coverage by domain, and the [source attribution ledger](https://www.worldmonitor.app/docs/source-attribution) records each host's observed surface, license posture, required attribution, and review status.
- ACLED (Armed Conflict Location & Event Data): Protests, riots, conflicts — 30-day window, tokenized API
- GDELT (Global Database of Events, Language, and Tone): Geo-events, protest keywords, topic feeds
- UCDP (Uppsala Conflict Data Program): Conflict zone classification
- USGS: Earthquakes M4.5+ globally, 5-minute updates
- GDACS: UN disaster alerts (earthquakes, floods, cyclones, volcanoes, wildfires, droughts)
- NASA EONET: Earth observation events across natural-event categories
- NASA FIRMS: VIIRS satellite fire/thermal hotspot detection
- Cloudflare Radar: Internet outage monitoring
- ADS-B Exchange: Military flight tracking
- AISStream.io: Vessel tracking via AIS (terrestrial receivers)
- OpenSky Network: Aircraft position data
- Polymarket: Prediction market probabilities for geopolitical events (3-tier JA3 bypass)
- Yahoo Finance: Stock data, ETF prices, macro signals
- CoinGecko: Stablecoin pricing and market caps
- mempool.space: Bitcoin hash rate data
- alternative.me: Fear & Greed Index
- EIA (Energy Information Administration): Oil prices, US production, inventory
- FRED (Federal Reserve Economic Data): Economic indicators
- WorldPop: Population density data for exposure estimation
- UN OCHA HAPI: Humanitarian access metrics and displacement flows
- Open-Meteo ERA5: Climate reanalysis data for anomaly detection
- abuse.ch (Feodo Tracker, URLhaus): C2 server and malware host IOCs
- C2IntelFeeds: Community-sourced C2 indicators
- AlienVault OTX: Open threat exchange IOCs
- AbuseIPDB: Crowd-sourced abuse reports
- ipinfo.io / freeipapi.com: IP geolocation enrichment
- NWS (National Weather Service): Severe weather warnings
- USASpending.gov: Government contracts and spending data
- Groq API: Llama 3.1 for world briefs, threat classification, and spike summarization
- OpenRouter API: LLM fallback provider
- MapTiler: Base map tiles
## Supported Languages
Localization follows the runtime locale registry, including right-to-left bundles. Fetch `https://www.worldmonitor.app/product-facts.json` and read `capabilities.localeCodes` for the exact current locale list. Language bundles are lazy-loaded on demand. Localized news feeds load region-specific RSS sources based on language preference. AI translation is available for cross-language intelligence gathering.
## Multi-Variant Build System
A single codebase produces specialized dashboards controlled by the VITE_VARIANT environment variable:
- **World Monitor** (worldmonitor.app): geopolitics, military, conflicts, infrastructure security, regional intelligence, and global risk.
- **Tech Monitor** (tech.worldmonitor.app): AI/ML, startups, cybersecurity, cloud, semiconductors, and technology policy.
- **Finance Monitor** (finance.worldmonitor.app): global markets, trading, central banks, macro, Gulf finance, and equity research.
- **Commodity Monitor** (commodity.worldmonitor.app): commodities, mining, metals, energy markets, shipping, and supply chains.
- **Happy Monitor** (happy.worldmonitor.app): constructive news, science, climate progress, health, conservation, and positive public action.
- **Energy Monitor** (energy.worldmonitor.app): energy security, oil and gas, chokepoints, policy response, and energy-market intelligence.
Build-time: Vite HTML plugin transforms meta tags, Open Graph data, PWA manifest, and JSON-LD structured data. Each variant tree-shakes unused data files. Runtime: variant selector in header navigates between deployed domains (web) or sets localStorage preference (desktop).
## Architecture Principles
- **Speed over perfection**: Keyword classifier is instant; LLM refines asynchronously. Users never wait
- **Assume failure**: Per-feed circuit breakers with 5-minute cooldowns. AI fallback chain: Groq, OpenRouter, browser-side T5. Redis failures degrade gracefully. Edge functions return stale cached data when upstream APIs are down
- **Show what you can't see**: Intelligence gap tracker explicitly reports data source outages rather than silently hiding them
- **Browser-first compute where appropriate**: clustering, local ML, geolocation, and offline fallbacks run client-side; server-authoritative APIs publish CII/CRI scores, briefs, forecasts, MCP tools, and cached operational data
- **Local-first geolocation**: Country detection uses browser-side ray-casting against GeoJSON polygons (sub-millisecond, zero API dependency, works offline)
- **Multi-signal correlation**: No single data source trusted alone. Focal points require convergence across news + military + markets + protests before escalating
- **Geopolitical grounding**: Hard-coded conflict zones, baseline country risk, and strategic chokepoints prevent false alerts
- **Defense in depth**: CORS origin allowlist, domain-allowlisted RSS proxy, server-side API key isolation, token-authenticated desktop sidecar, IP rate limiting
- **Cache everything, trust nothing**: Three-tier caching (in-memory, Redis, upstream) with stale-on-error fallback
- **Baseline-aware alerting**: Rolling temporal windows against learned baselines with per-term spike multipliers and cooldowns
## Tech Stack
- **Frontend**: TypeScript, Vite, MapLibre GL JS, deck.gl (WebGL), D3.js, Supercluster (marker clustering), Transformers.js (browser-side ML)
- **Internationalization**: i18next with lazy-loaded language bundles, RTL support for Arabic/Hebrew
- **Desktop**: Tauri 2.x (Rust core + Node.js sidecar), OS keychain integration (macOS Keychain, Windows Credential Manager), token-authenticated local API
- **Backend**: Vercel Edge Functions, Railway relay server for blocked RSS feeds
- **Data Store**: Upstash Redis (caching, Welford baselines, LLM dedup), IndexedDB (historical playback), localStorage (preferences, panel state)
- **AI Pipeline**: Groq (Llama 3.1 8B), OpenRouter (fallback), Transformers.js (browser fallback for NER, sentiment, summarization)
- **Monitoring**: Sentry error tracking and a data-freshness tracker across source groups with intelligence gap reporting
- **Testing**: Playwright E2E tests (per-variant), Node.js test runner for data/sidecar tests
- **PWA**: Service worker with CacheFirst map tiles (500 tiles, 30-day TTL), NetworkOnly for intelligence data, offline fallback page
## Desktop Application
Native desktop app built with Tauri (Rust + Node.js sidecar). The sidecar mirrors cloud API handlers locally with gzip compression. Features:
- OS keychain integration for configured upstream API keys (macOS Keychain, Windows Credential Manager)
- Token-authenticated sidecar prevents unauthorized local access
- Cloud fallback when local handlers fail
- Settings window (Cmd+,) for API key management with validation
- Verbose debug mode with persistent state and traffic logging (last 200 requests)
- Auto-update checker polling every 6 hours with per-version dismiss
- Available for macOS (Apple Silicon + Intel), Windows (.exe), and Linux (.AppImage)
## Key Features Summary
- Interactive 3D WebGL globe with a shared map-layer catalog and smart clustering
- AI-synthesized world briefs with hybrid threat classification
- CII v8 instability scores for the Tier-1 country registry
- CRI resilience scores for the public rankable universe
- Strategic posture assessment across named theaters
- Geographic convergence detection and infrastructure cascade modeling
- Curated RSS feeds with source tiering and propaganda risk ratings
- Live news streams and webcams from geopolitical hotspots
- 7-signal macro market radar with BUY/CASH verdict
- Country brief pages with exportable intelligence dossiers (JSON, CSV, PNG)
- Multilingual UI with RTL support
- Prediction market integration (Polymarket) with 3-tier JA3 bypass
- Temporal baseline anomaly detection using Welford's algorithm
- Dual-source protest tracking (ACLED + GDELT) with regime-aware scoring
- Population exposure estimation using WorldPop density data
- Shareable intelligence stories with multi-platform social export
- Cmd+K fuzzy search across result types
- Historical playback via IndexedDB snapshots with time slider
- Dark/light theme, panel reordering, ultra-wide layout (2000px+)
- Feature toggles for runtime data source controls
## Optional
- [Source Code](https://github.com/koala73/worldmonitor): GitHub repository (AGPL-3.0)
- [Releases](https://github.com/koala73/worldmonitor/releases): All desktop releases for macOS, Windows, and Linux
- [Issues](https://github.com/koala73/worldmonitor/issues): Bug reports and feature requests
## Generated corpus
The sections below are produced by `npm run build:llms-full` from the source catalog, comparison-page registry, glossary terms, chokepoint methodology, published chokepoint explainers, the forecast accuracy snapshot, the Country Resilience Index methodology, the corrections log, and the current published ranking snapshot.
## Source provider directory
World Monitor publishes 757 named providers across 18 source catalog pages. Each linked page contains provider names, source hosts, origins and coverage in static HTML; no search or JavaScript is required.
- [Geopolitics & Conflict](https://www.worldmonitor.app/sources/geopolitics/): 36 providers.
- [Military & Strategic](https://www.worldmonitor.app/sources/military/): 22 providers.
- [News & OSINT](https://www.worldmonitor.app/sources/news/): 60 providers.
- [News & OSINT — page 2](https://www.worldmonitor.app/sources/news/page/2/): 60 providers.
- [News & OSINT — page 3](https://www.worldmonitor.app/sources/news/page/3/): 60 providers.
- [News & OSINT — page 4](https://www.worldmonitor.app/sources/news/page/4/): 60 providers.
- [News & OSINT — page 5](https://www.worldmonitor.app/sources/news/page/5/): 60 providers.
- [News & OSINT — page 6](https://www.worldmonitor.app/sources/news/page/6/): 60 providers.
- [News & OSINT — page 7](https://www.worldmonitor.app/sources/news/page/7/): 60 providers.
- [News & OSINT — page 8](https://www.worldmonitor.app/sources/news/page/8/): 44 providers.
- [Finance & Economics](https://www.worldmonitor.app/sources/finance/): 60 providers.
- [Finance & Economics — page 2](https://www.worldmonitor.app/sources/finance/page/2/): 3 providers.
- [Energy & Commodities](https://www.worldmonitor.app/sources/energy/): 23 providers.
- [Infrastructure & Cyber](https://www.worldmonitor.app/sources/infrastructure/): 52 providers.
- [Environment & Disasters](https://www.worldmonitor.app/sources/environment/): 45 providers.
- [Aviation & Airspace](https://www.worldmonitor.app/sources/aviation/): 14 providers.
- [China Coverage](https://www.worldmonitor.app/sources/china/): 12 providers.
- [Tech Ecosystem](https://www.worldmonitor.app/sources/technology/): 26 providers.
## Comparisons
A comparison hub plus 12 head-to-head and category pages. Every page uses the same 11-column matrix (Product, Price, Update latency, Domains covered, Signup required, REST API, MCP server, Open source, Source count & licensing, Historical archive, Best for), states what each competitor wins, and answers the questions engines lift verbatim. Prices were checked at publication and can change.
- [Compare World Monitor](https://www.worldmonitor.app/compare/): Compare World Monitor with Liveuamap, ACLED, GDELT, Dataminr, Recorded Future, and more: one master matrix, honest concessions, and FAQs.
- [Liveuamap Alternatives](https://www.worldmonitor.app/compare/liveuamap-alternatives/): Eleven-column matrix comparing World Monitor with Liveuamap, Deep State Map, ACLED, ConflictZone.io, ISW, UNOSAT and ICG CrisisWatch on price, latency, API access and licensing, with the cells each competitor wins.
- [Best Real-Time Geopolitical Risk Dashboards](https://www.worldmonitor.app/compare/best-geopolitical-risk-dashboards/): Real-time geopolitical risk dashboards ranked against BlackRock, IISS, OrreryX, the-world-now.com, Statista and Earthian AI on update latency, price and signup, with where the analyst products still win.
- [World Monitor vs Liveuamap](https://www.worldmonitor.app/compare/worldmonitor-vs-liveuamap/): Head-to-head on published numbers: World Monitor API Starter at $99.99/mo for 1,000 requests/day against Liveuamap Pro at $150/mo for 200, plus the domains only one side tracks.
- [World Monitor vs ACLED](https://www.worldmonitor.app/compare/worldmonitor-vs-acled/): World Monitor and ACLED (myACLED) compared on access tiers, latency, API availability and licensing, and why World Monitor complements ACLED's coded-event research rather than replacing it.
- [World Monitor vs GDELT Cloud](https://www.worldmonitor.app/compare/worldmonitor-vs-gdelt/): Curated indices versus the GDELT firehose: World Monitor, GDELT Cloud, war-dashboard-data and world-intel-mcp compared on latency, archive depth, API and MCP access, and where raw GDELT still wins.
- [World Monitor vs Dataminr](https://www.worldmonitor.app/compare/worldmonitor-vs-dataminr/): Published prices against enterprise-negotiated licensing: World Monitor and Dataminr compared on alert latency, data domains, API access and price transparency, with the cells Dataminr wins.
- [World Monitor vs Recorded Future](https://www.worldmonitor.app/compare/worldmonitor-vs-recorded-future/): World Monitor, Recorded Future, Flare and MISP compared on price transparency, public access, domains covered and open source, and when an enterprise threat-intelligence platform is the right call.
- [World Monitor vs Deep State Map](https://www.worldmonitor.app/compare/worldmonitor-vs-deepstatemap/): Global multi-domain coverage against a single-theatre map: World Monitor and Deep State Map compared on scope, update method, API access and archive, and why Deep State Map wins on Ukraine frontline detail.
- [MCP Servers for Geopolitical Data](https://www.worldmonitor.app/compare/mcp-servers-for-geopolitical-data/): Hosted versus self-hosted MCP access to geopolitical data: World Monitor against world-intel-mcp, Satellite MCP, OSINT MCP, GDELT Cloud MCP and IMF PortWatch MCP on entitlements, quotas, OAuth and hosting burden.
- [Chokepoint Monitoring Tools](https://www.worldmonitor.app/compare/chokepoint-monitoring-tools/): Chokepoint monitoring tools compared: World Monitor against IMF PortWatch, MarineTraffic, Kpler, Lloyd's List Intelligence, Windward and straits.live on transit counts, fused context, price and API access.
- [Free Geopolitical Risk Dashboards](https://www.worldmonitor.app/compare/free-geopolitical-risk-dashboards/): Which geopolitical risk dashboards are free without signup: World Monitor against OrreryX, the-world-now.com, Sentinel, ConflictZone.io, BlackRock, Deep State Map and ICG CrisisWatch on gating, latency and domains.
- [Travel Risk Intelligence vs Assistance](https://www.worldmonitor.app/compare/travel-risk-intelligence-vs-assistance/): Travel risk intelligence versus assistance: World Monitor as the always-on awareness layer next to Crisis24, International SOS, Riskline, Everbridge, Samdesk and Factal, which win on response and duty-of-care delivery.
## Glossary
### Country Instability Index (CII)
The Country Instability Index (CII) is a high-frequency instability score WorldMonitor maintains for 31 Tier-1 countries by blending editorial baseline with live event pressure.
The Country Instability Index (CII) is a high-frequency instability score that WorldMonitor maintains for the 31 Tier-1 countries tracked by its Strategic Risk system. Rather than relying on static ratings, CII blends a curated editorial baseline with live event pressure — unrest, conflict, security, and information signals — and publishes a signed 24-hour movement delta so operators can see which direction a country is moving.
Tier-1 membership is curated rather than algorithmic: a country is included when it has sustained global-risk relevance, active or recent armed conflict, severe domestic instability, or high regional escalation potential. The score is computed server-side and exposed through the GetRiskScores RPC and the get_country_risk MCP tool.
### Country Resilience Index (CRI)
The Country Resilience Index (CRI) is a composite 0–100 score from 72 indicators across 21 active dimensions, refreshed every six hours for 196 countries.
The Country Resilience Index (CRI) is a composite 0–100 score of a country’s structural ability to absorb and recover from shocks. Where the CII measures short-term instability, the CRI measures durable capacity — economic, infrastructure, energy, social-governance, health-and-food, and recovery strength — refreshed every six hours from official sources with full coverage and imputation provenance.
The six domains carry design weights — economic 0.17, infrastructure 0.15, energy 0.11, social-governance 0.19, health-food 0.13, recovery 0.25 (sum 1.00) — and are regrouped into three pillars (structural readiness, live-shock exposure, recovery capacity) that combine into the headline score through a non-compensatory formula with a min-pillar penalty. Recovery carries the largest single-domain weight, which is the mechanical reason fiscally strong smaller states cluster near the top while fragile states separate cleanly at the bottom.
CRI covers a fixed 196-country public rankable universe (a committed UN-member and SAR whitelist); low-confidence or headline-ineligible countries are routed to a separate greyed-out list rather than dropped, and every response exposes per-dimension coverage plus a four-class imputation taxonomy so an analyst can see how much of a score is real data. Scores are served through the get-resilience-score and get-resilience-ranking endpoints and the get_country_risk MCP tool.
### Strategic Risk
Strategic Risk is WorldMonitor’s composite triage layer that synthesizes instability, convergence, infrastructure, theater posture, sanctions, and breaking-news into one headline risk read.
Strategic Risk is WorldMonitor’s composite triage layer for global risk. Its server-published headline score is a top-five Country Instability Index roll-up, around which the panel layers additional convergence, infrastructure cascade, theater posture, breaking-news, sanctions, and radiation-watch context.
The purpose is fast triage: rather than reading each intelligence module separately, an operator sees one fused assessment that flags where multiple independent signals are pointing at the same place at the same time.
### Dimension Coverage
Dimension coverage is the share of a country’s resilience dimensions backed by real observed data rather than imputed values.
Dimension coverage is the share of a country’s resilience dimensions that are backed by real observed data rather than imputed, reported as the mean of the 21 active per-dimension coverage values (structurally-retired dimensions are excluded from the average). It is deliberately labelled "dimension coverage" rather than "data coverage" to be precise about what is measured.
Coverage drives a confidence gate: when a country’s average dimension coverage falls below 0.55 — or too much of its score is imputed — the Country Resilience Index marks that score low-confidence, and countries that also fail the headline-eligibility thresholds are routed to a separate greyed-out list rather than the public ranking. Thin-data countries are never presented as if they were confidently scored.
### Pentagon Pizza Index
The Pentagon Pizza Index is an OSINT folk indicator: unusual busyness at pizza places near the Pentagon, read as a hint of late-night crisis work.
The Pentagon Pizza Index is an open-source-intelligence folk indicator. The idea is simple: when defense staff work late on a developing crisis, pizza places near the Pentagon get busier than usual for that hour, and the surge is visible to the public before any official statement. The notion comes from Washington lore of the Cold War and the 1990s, and it resurfaced on social media in recent years as people began posting Pentagon-area pizza traffic during international crises.
World Monitor computes its own version of the index from live busyness at pizza venues around the Pentagon. PizzINT supplies the venue data, with BestTime as the fallback, and the same rule applies to both. A venue counts only when it is open, at least 150% as busy as its usual level for that hour, and at least 25 busyness points above its forecast, and only after three consecutive 15-minute readings. A normal lunch rush or a single blip does not register.
Each sustained spike adds up to 25 points. The total maps to a DEFCON-style level: 5 (Normal Activity), 4 (Above Normal), 3 (Elevated Activity), 2 (High Activity) or 1 (Maximum Activity). The level appears next to a pizza icon in the header of the World Monitor dashboard, with each venue’s reading against its usual level. A venue that is closed or not reporting shows NO DATA rather than a guessed value.
The level describes restaurant activity, not military readiness, and its thresholds are heuristic rather than a validated predictor of geopolitical events. The same panel shows GDELT-based tension scores for country pairs such as USA–Iran and USA–China, so a busy night can be read against other signals instead of on its own.
### Focal Point Detection
Focal point detection correlates news entities with live map signals to identify the main characters — people, places, and organizations — driving current events.
Focal point detection is WorldMonitor’s intelligence-synthesis layer. A focal point is an entity — a person, place, or organization — that appears in both news coverage and map signals at the same time. Surfacing those overlaps identifies the "main characters" driving the current situation.
The detector enriches AI analysis with this cross-referenced context, so a generated brief reasons about entities that are simultaneously in the headlines and on the map, rather than treating text and geospatial signals as separate worlds.
### Geographic Convergence
Geographic convergence is when three or more distinct event types co-occur in the same one-degree map cell within 24 hours, firing a convergence alert.
Geographic convergence detection bins events — protests, military flights, vessels, earthquakes, and more — into 1°×1° geographic cells over a rolling 24-hour window. When three or more distinct event types converge in a single cell, a convergence alert fires.
Alert severity is driven by type diversity (about 25 points per unique event type) plus event-count bonuses (capped at 25). Four converging types, or a score of 90 or above, is treated as critical; three-type alerts below 90 are high priority. Each alert is reverse-geocoded to a human-readable place name using conflict-zone, waterway, and hotspot databases.
### Infrastructure Cascade
An infrastructure cascade is a modeled chain reaction where disrupting one critical node — cable, pipeline, port, or chokepoint — threatens downstream systems.
An infrastructure cascade is a chain reaction across dependent critical systems. WorldMonitor models the dependency graph linking cables, pipelines, ports, and chokepoints so that damage or disruption at one node can be traced to the downstream nodes it puts at risk.
Cascade incidents feed the Strategic Risk score and the alert-fusion pipeline: cascade alerts are merged with convergence alerts, CII spikes, sanctions pressure, and radiation watch when they occur close together in time and space, so a single fused alert captures a multi-domain event.
### Hotspot
A hotspot is a watched location whose displayed activity level is computed in real time from news correlation, not a fixed static threat rating.
A hotspot is a location WorldMonitor watches continuously. Crucially, a hotspot’s activity level is not a static threat rating — it is calculated in real time based on how strongly current news correlates with the keywords that define that location.
This keeps the map honest: a normally quiet location lights up only when live coverage says something is actually happening there, and a chronically tense location can read as calm during a genuine lull.
### Threat Classification
Threat classification is the hybrid AI step that labels incoming events by type and severity using fast rules plus model-based analysis.
Threat classification is the step that turns raw incoming events into a structured, labelled feed. WorldMonitor uses a hybrid approach: fast rule-based tagging handles the common, unambiguous cases, while model-based classification handles nuance and ambiguity.
Consistent type and severity labels are what make downstream correlation possible — convergence detection, focal-point synthesis, and Strategic Risk all depend on events already being classified into comparable categories.
### Maritime Chokepoint
A maritime chokepoint is a narrow passage through which a large share of global trade, energy, food, or military movement must pass.
A maritime chokepoint is a narrow passage where a large share of global trade, energy, food, or military movement must pass through a small physical space. If ships can choose among several similar routes, a disruption is manageable; when many routes collapse into one narrow passage, the same disruption can become systemic.
The essential idea is that a chokepoint is where geography removes optionality — the risk is not just today’s traffic, but how little room the system has when that traffic changes. WorldMonitor tracks 13 waterways, of which seven currently publish live flow estimates.
### Strait of Hormuz
The Strait of Hormuz is the Gulf exit chokepoint for about 20% of seaborne crude oil.
The Strait of Hormuz is the narrow waterway connecting the Persian Gulf to the Gulf of Oman and the open ocean. It is the single most closely watched energy chokepoint on Earth because about 20% of the world’s seaborne crude oil — and a large share of liquefied natural gas — has no alternative route out of the Gulf.
In WorldMonitor, Hormuz is one of the chokepoints with live flow estimates: vessel activity, congestion, and disruption signals are correlated against energy markets so an operator can see whether a Gulf tension event has a plausible transmission path into oil and gas prices.
### Strait of Malacca
The Strait of Malacca is the primary shipping lane between the Indian and Pacific Oceans, carrying much of East Asia’s container traffic and energy imports.
The Strait of Malacca runs between the Malay Peninsula and Sumatra, linking the Indian Ocean to the South China Sea and the Pacific. It is one of the busiest shipping lanes in the world and the main artery for energy and container flows into East Asia.
Its width and traffic density make it a textbook chokepoint: alternative routes exist but are longer and lower-capacity, so congestion or disruption in Malacca reverberates through Asian supply chains and freight costs.
### Suez Canal
The Suez Canal is the artificial waterway linking the Mediterranean and the Red Sea that lets shipping move between Europe and Asia without rounding Africa.
The Suez Canal connects the Mediterranean Sea to the Red Sea, providing the shortest maritime route between Europe and Asia and removing the need to sail around the Cape of Good Hope. Its southern approach runs through the Bab-el-Mandeb strait, so instability in the Red Sea affects both.
As a chokepoint, Suez concentrates a large share of Europe–Asia trade into a single canal; a blockage or a security threat that reroutes traffic around Africa adds days of transit and materially raises freight costs, which WorldMonitor tracks alongside the physical disruption signals.
### Automatic Identification System (AIS)
AIS (Automatic Identification System) is the transponder standard that broadcasts a ship’s identity, position, and course for tracking vessel traffic through chokepoints.
The Automatic Identification System (AIS) is a maritime transponder standard that continuously broadcasts a vessel’s identity, position, speed, and course. It exists for collision avoidance, but it also makes near-real-time ship tracking possible for anyone receiving the signals.
WorldMonitor uses AIS positions to watch tanker and cargo movement inside chokepoint bounding boxes, detect congestion, and flag disruptions such as coverage gaps. Because AIS can be switched off or spoofed, sudden gaps are themselves treated as a signal worth surfacing.
### Chokepoint Congestion
Chokepoint congestion is an above-normal build-up of vessel traffic waiting to transit a strait or canal, detected from AIS as an early disruption sign.
Chokepoint congestion is an above-baseline accumulation of ships waiting to transit a strait or canal. WorldMonitor detects it from AIS activity inside each chokepoint’s bounding box and treats a congestion spike as one of its AIS disruption types.
Congestion is an early-warning signal: queues often build before a disruption becomes headline news, so a rising congestion reading at Hormuz, Suez, or Malacca can precede the trade and energy-price effects that follow.
### Open-Source Intelligence (OSINT)
Open-source intelligence (OSINT) is intelligence produced from publicly available sources — news, social media, imagery, transponder feeds, and public records.
Open-source intelligence (OSINT) is intelligence derived entirely from publicly available information: news reporting, social media, satellite and aerial imagery, ship and aircraft transponders, and public records. Its power comes not from secrecy but from correlation — combining many open signals into a picture no single source shows.
WorldMonitor is an OSINT platform by construction: every layer is sourced from public feeds with documented provenance, which is what lets it publish source-attributed briefs and scores that a reader can trace back to the underlying evidence.
### Provenance & Source Attribution
Provenance is the documented chain from a published score or brief back to the specific public sources it was built from.
Provenance, or source attribution, is the discipline of keeping a documented chain from every published output back to the specific public sources behind it. For an OSINT product it is the difference between an assertion and a citation.
WorldMonitor carries provenance through its briefs, scores, and cached operational data with documented methodology, so a reader — or an AI agent consuming the API — can see not just what the platform concluded but which sources support it.
### World Brief
The World Brief is WorldMonitor’s AI-generated, source-attributed summary of the current global situation, synthesized from correlated live signals.
The World Brief is a source-attributed situational summary generated from WorldMonitor’s correlated live signals — news, map events, focal points, and classified threats. It answers "what is happening right now, globally" in a form an operator or an agent can consume directly.
It is available through the get_world_brief MCP tool and the dashboard, and it draws on the same focal-point and classification layers that power the map, so the narrative and the geospatial view stay consistent.
### Prediction Market
A prediction market is a marketplace where participants trade contracts on future event outcomes, and the price acts as a crowd-sourced probability estimate.
A prediction market is a marketplace in which participants buy and sell contracts tied to the outcome of a future event. Because a contract pays out based on what actually happens, its trading price behaves as a continuously updated, crowd-sourced probability for that outcome.
WorldMonitor surfaces prediction-market context — for example via the get_prediction_markets tool — as an external probability signal to sit alongside its own scenario forecasts, giving a market-implied read on geopolitical questions next to the platform’s analysis.
## Monitored chokepoints
### Mediterranean ↔ Red Sea
The Suez Canal is the artificial waterway linking the Mediterranean and the Red Sea, giving shipping the shortest route between Europe and Asia without rounding Africa. Its southern approach runs through Bab el-Mandeb, so a blockage or a Red Sea security threat that reroutes traffic around the Cape of Good Hope adds days of transit and materially raises freight costs.
### Indian Ocean ↔ South China Sea
The Strait of Malacca runs between the Malay Peninsula and Sumatra, linking the Indian Ocean to the South China Sea and the Pacific. It is one of the busiest shipping lanes in the world and the main artery for energy and container flows into East Asia, where the alternatives are longer and lower-capacity.
### Persian Gulf ↔ Gulf of Oman
The Strait of Hormuz is the narrow waterway connecting the Persian Gulf to the Gulf of Oman and the open ocean. It is the single most closely watched energy chokepoint on Earth: about 20% of the world’s seaborne crude oil — and a large share of LNG — has no alternative route out of the Gulf.
### Red Sea ↔ Gulf of Aden
Bab el-Mandeb is the strait between the Horn of Africa and the Arabian Peninsula that connects the Red Sea to the Gulf of Aden and the Indian Ocean. Every ship using the Suez Canal route also transits Bab el-Mandeb, so attacks or instability here push traffic onto the far longer Cape of Good Hope route.
### Atlantic ↔ Pacific
The Panama Canal cuts across the Isthmus of Panama to link the Atlantic and Pacific oceans, saving vessels the long voyage around South America. Its lock system depends on freshwater from Gatún Lake, so drought can throttle daily transits and reshape Asia–US East Coast routing.
### East China Sea ↔ South China Sea
The Taiwan Strait separates Taiwan from mainland China and carries a large share of the container traffic moving between North Asia and the rest of the world. Its strategic sensitivity makes any military tension here a first-order risk to global shipping and the semiconductor supply chain.
### Atlantic ↔ Indian Ocean
The Cape of Good Hope is the deep-water route around the southern tip of Africa. It has no canal tolls and no width limits, which makes it the default fallback when the Suez–Bab el-Mandeb corridor is disrupted — at the cost of thousands of extra nautical miles and days of transit.
### Atlantic ↔ Mediterranean
The Strait of Gibraltar is the roughly 14-km-wide gateway between the Atlantic Ocean and the Mediterranean Sea. Every cargo moving between the Mediterranean and the wider ocean — including Suez-bound Europe–Asia traffic — passes through it.
### Black Sea ↔ Sea of Marmara
The Bosporus Strait runs through Istanbul to connect the Black Sea to the Sea of Marmara and, via the Dardanelles, the Mediterranean. It is the sole maritime outlet for Black Sea grain and Russian oil exports, and passage through it is governed by the Montreux Convention.
### East China Sea ↔ Sea of Japan
The Korea Strait lies between the Korean Peninsula and the Japanese islands, linking the East China Sea to the Sea of Japan. It is a key passage for North Asian container and energy traffic and a closely watched naval corridor.
### English Channel ↔ North Sea
The Strait of Dover is the narrowest point of the English Channel, connecting it to the North Sea. It is one of the busiest shipping lanes in the world, funnelling North Sea and Baltic traffic past the coasts of England and France.
### Black Sea ↔ Sea of Azov
The Kerch Strait connects the Black Sea to the Sea of Azov and is the only sea route to the Azov ports of Ukraine and Russia. It has been a repeated flashpoint in the Russia–Ukraine conflict, where control of the strait directly gates Azov-basin trade.
### Indian Ocean ↔ Java Sea
The Lombok Strait, between Bali and Lombok, is a deep-water alternative to the Malacca–Singapore route. It is favoured by the largest, deepest-draft bulk carriers and serves as a relief valve when Malacca is congested or disrupted.
## Forecast accuracy
The standing forecast-resolution record is published at https://www.worldmonitor.app/accuracy/.
Over the current 180-day window, World Monitor's headline cohort scores a Brier of 0.125 across 223 scored forecasts, against 0.25 for answering 0.5 to everything.
Captured 2026-09-28.
This page does not publish confidence intervals; each figure is published with the number of forecasts behind it instead. It does not score the 24-hour, 7-day and 30-day projections shown in the product. It publishes aggregates only — no individual forecasts, resolution evidence, judge inputs or archive locations.
## Chokepoint methodology
_Methodology maintained by [Elie Habib](https://www.worldmonitor.app/blog/authors/elie-habib/), founder of World Monitor. Published revisions are recorded in the [corrections log](/docs/corrections)._
## Start here
A handful of narrow waterways carry a wildly disproportionate share of world
trade. The Strait of Hormuz alone runs at a baseline of about 21 million barrels
a day — comparable to a fifth of global petroleum liquids consumption. Close one
of these, and the effects reach every continent within weeks.
WorldMonitor watches 13 of them and answers, continuously: **is anything wrong
here, and who would feel it?**
### What a chokepoint row tells you
Open the [Strait of Hormuz tracker](https://www.worldmonitor.app/chokepoints/strait-of-hormuz/) for a worked example. Read its published disruption score, available inputs, and observation dates alongside the method below.
Each waterway carries four separate readings, and it is worth keeping them
apart:
| Reading | The question it answers |
|---|---|
| **Flow** | Is traffic actually down? Measured against this strait's own 90-day norm, not a global average. |
| **Threat** | What kind of problem is it — weather, war risk, mechanical, congestion? |
| **Disruption score** | How bad, on one scale, so waterways can be ranked. |
| **Country exposure** | Which countries' trade routes through here, so a closure has named victims. |
**Only 7 of the 13 carry a live flow estimate.** Hormuz, Malacca, Suez, Bab
el-Mandeb, Dover, Bosporus, and Panama have an EIA energy baseline to measure
against. The other six get transit summaries, threat classification, disruption
scoring, and war-risk tiers, but `flowEstimate` is simply absent — not zero, not
"normal." Do not read a missing flow as calm water.
### How "flow is down" is decided
Traffic is compared against itself. The last 7 days of shipping activity are
measured against the previous 90 — so a quiet week in a normally quiet strait
does not register, while the same drop in a busy one does. That ratio is then
applied to the strait's known baseline oil volume to express the shortfall in
barrels per day.
Two consequences worth internalizing: the number is a **modelled estimate** from
vessel movement, not a metered measurement of oil; and it is deliberately
capped, so a traffic surge cannot report more flow than the waterway plausibly
carries.
## What we track
WorldMonitor has **13 monitored waterways** in the canonical chokepoint registry and the
`GetChokepointStatus` RPC. The status RPC returns one row for each canonical id:
`suez`, `malacca_strait`, `hormuz_strait`, `bab_el_mandeb`, `panama`,
`taiwan_strait`, `cape_of_good_hope`, `gibraltar`, `bosphorus`,
`korea_strait`, `dover_strait`, `kerch_strait`, and `lombok_strait`.
Only **seven** of those 13 currently carry a live oil/gas flow estimate from
`energy:chokepoint-flows:v1`, because only those seven have an EIA baseline id
in the current seeder:
| Canonical id | Public name | EIA baseline id | Baseline flow (mb/d) |
|---|---|---|---:|
| `hormuz_strait` | Strait of Hormuz | `hormuz` | 21.0 |
| `malacca_strait` | Strait of Malacca | `malacca` | 17.2 |
| `suez` | Suez Canal / SUMED | `suez` | 7.6 |
| `bab_el_mandeb` | Bab el-Mandeb | `babelm` | 6.2 |
| `dover_strait` | Dover Strait | `danish` | 3.0 |
| `bosphorus` | Bosporus Strait | `turkish` | 2.9 |
| `panama` | Panama Canal | `panama` | 0.9 |
The other six canonical waterways still receive transit summaries, warnings,
AIS-disruption matching, threat classification, disruption score, and war-risk
tier, but `flowEstimate` is absent until a baseline-backed flow model is added.
## Live Flow
Live flow is computed by `scripts/seed-chokepoint-flows.mjs` on the seven-item
subset above:
1. Read PortWatch history from `supply_chain:portwatch:v1`.
2. Choose the signal: use `capTanker` deadweight tonnage when at least half of
the prior-window days have DWT coverage; otherwise use tanker counts.
3. Compute `current7d` as the average of the latest seven days.
4. Compute `baseline90d` as the average of the previous window, up to 90 days
(`history.slice(-97, -7)`), requiring at least 20 baseline days.
5. Compute `flowRatio = clamp(current7d / baseline90d, 0, 1.5)`.
6. Compute `currentMbd = baselineMbd * flowRatio`, rounded to one decimal.
The published ratio is therefore a recent 7-day average against a prior
up-to-90-day rolling baseline. The `baselineMbd` field is the annual EIA 2023
reference level; it is used to convert the observed ratio into mb/d. Flow ratios
can publish from 0% to 150% of baseline after the clamp.
Live flow is eligible only when the PortWatch series has at least 40 total days
of history. After that gate, the seeder still requires at least three recent
days, at least 20 prior-window baseline days, and a non-thin baseline: at least
1 DWT-day when using tanker deadweight tonnage, or at least 0.5 tanker-count
when using vessel counts. Rows below those floors are omitted rather than
reported as zero flow.
The `disrupted` boolean is separate from the color badge: it is true when each
of the latest three individual days is below 85% of the same `baseline90d`.
Each published flow estimate may also include live hazard context from
`portwatch:disruptions:active:v1`. The seeder looks for the nearest active
GDACS `RED` or `ORANGE` alert within 500 km of the supported chokepoint and
surfaces it as `hazardAlertLevel` and `hazardAlertName`. This is annotation
only: hazard enrichment does not change `currentMbd`, `flowRatio`, or the
`disrupted` calculation.
## Score Badge
The public `status` field on `ChokepointInfo` is a traffic-light score badge:
`green`, `yellow`, or `red`. It summarizes disruption risk; it is not an
operational declaration that a waterway is open, restricted, or closed. Detail
pages report observed transit activity when it is available and state when
source coverage is too partial to verify operational passage status.
The score is:
```text
disruptionScore = min(
100,
threatLevelWeight + warningComponent + aisComponent + anomalyBonus
)
```
Where:
- `threatLevelWeight` is the geopolitical baseline weight in the taxonomy below.
- `warningComponent = min(15, activeWarnings * 5)`.
- `aisComponent = min(15, maxCongestionSeverity * 5)`, where low/elevated/high
AIS congestion severity maps to 1/2/3.
- `anomalyBonus = 10` only when PortWatch daily transit history shows a 50% or
larger traffic drop against the prior 30-day transit-count baseline and the
threat level is `war_zone` or `critical`.
Those four terms are the whole formula. AIS event counts, relay transit counts,
and PortWatch week-over-week movement are published as context and never enter
the score. PortWatch feeds both sides: `anomalyBonus` reads its daily transit
history through `supply_chain:portwatch:v1`, while the week-over-week figure is
presentation only.
The score badge thresholds are:
| Score range | `status` |
|---:|---|
| `< 20` | `green` |
| `20-49` | `yellow` |
| `>= 50` | `red` |
## Threat Taxonomy
The geopolitical threat baseline is assigned per chokepoint in
`server/worldmonitor/supply-chain/v1/get-chokepoint-status.ts` and weighted in
`server/worldmonitor/supply-chain/v1/_scoring.mjs`.
| Threat level | Weight | Meaning |
|---|---:|---|
| `war_zone` | 70 | Active naval conflict, blockade, or strait closure |
| `critical` | 40 | Active attacks on commercial shipping |
| `high` | 30 | Military seizure risk or armed escort zone |
| `elevated` | 15 | Military tensions or disputed waters |
| `normal` | 0 | No significant military threat |
Current assignments:
| Canonical id | Public name | Threat level | Weight | War-risk enum |
|---|---|---|---:|---|
| `suez` | Suez Canal | `high` | 30 | `WAR_RISK_TIER_HIGH` |
| `malacca_strait` | Strait of Malacca | `normal` | 0 | `WAR_RISK_TIER_NORMAL` |
| `hormuz_strait` | Strait of Hormuz | `war_zone` | 70 | `WAR_RISK_TIER_WAR_ZONE` |
| `bab_el_mandeb` | Bab el-Mandeb | `critical` | 40 | `WAR_RISK_TIER_CRITICAL` |
| `panama` | Panama Canal | `normal` | 0 | `WAR_RISK_TIER_NORMAL` |
| `taiwan_strait` | Taiwan Strait | `elevated` | 15 | `WAR_RISK_TIER_ELEVATED` |
| `cape_of_good_hope` | Cape of Good Hope | `normal` | 0 | `WAR_RISK_TIER_NORMAL` |
| `gibraltar` | Strait of Gibraltar | `normal` | 0 | `WAR_RISK_TIER_NORMAL` |
| `bosphorus` | Bosporus Strait | `elevated` | 15 | `WAR_RISK_TIER_ELEVATED` |
| `korea_strait` | Korea Strait | `normal` | 0 | `WAR_RISK_TIER_NORMAL` |
| `dover_strait` | Dover Strait | `normal` | 0 | `WAR_RISK_TIER_NORMAL` |
| `kerch_strait` | Kerch Strait | `war_zone` | 70 | `WAR_RISK_TIER_WAR_ZONE` |
| `lombok_strait` | Lombok Strait | `normal` | 0 | `WAR_RISK_TIER_NORMAL` |
## Transit Anomaly
Transit anomaly detection for `anomalyBonus` is based on compact transit-count
history, not the live mb/d flow model. It compares the latest seven transit
counts with the preceding 30 days converted to a seven-day baseline:
```text
baselineAvg7 = (sum(days -37..-8) / availableBaselineDays) * 7
dropPct = round((baselineAvg7 - recent7) / baselineAvg7 * 100)
signal = dropPct >= 50 AND threatLevel in {war_zone, critical}
```
If signalled, the handler appends a description such as
`Traffic down 55% vs 30-day baseline, vessels may be transiting dark (AIS off)`.
The anomaly path is gated before that comparison: it requires at least 37 days
of compact transit-count history, and the normalized seven-day baseline must be
at least 14 transits. Thin baselines return no anomaly signal.
## Country Exposure
`GetCountryChokepointIndex` returns a separate exposure model for a country and
HS2 chapter. It is PRO-gated and cached at
`supply-chain:exposure:{ISO2}:{HS2}:v1`.
When bilateral HS4 import products are available, exposure is computed as:
```text
productWeight = product.totalValue / totalSectorValue
routeCoverage = overlappingRouteIds / chokepoint.routeIds.length
contribution = routeCoverage * exporter.share * productWeight * 100
```
Contributions are summed per chokepoint across matching products and top
exporters. For HS2 `27`, chokepoints with `shockModelSupported = true` receive a
1.5x energy-model boost capped at 100.
When bilateral product data is unavailable, the fallback score is:
```text
exposureScore = overlappingCountryRouteIds / chokepoint.routeIds.length * 100
```
with the same HS2 `27` supported-energy boost and 100 cap. The
`vulnerabilityIndex` is the weighted top-three score:
```text
top1 * 0.5 + top2 * 0.3 + top3 * 0.2
```
## Provenance
Chokepoint status combines Redis-backed transit summaries, flow estimates,
navigational warnings, AIS disruption matching, and the static threat taxonomy.
If a canonical chokepoint lacks upstream transit coverage for the current cycle,
`transitSummary.dataAvailable` is false and the response-level
`upstreamUnavailable` flag is set so clients can render partial-coverage UI.
Refresh cadence:
- `energy:chokepoint-flows:v1`: Railway seed loop every 6 hours.
- `supply_chain:chokepoints:v4`: status warm-ping every 30 minutes.
- `supply_chain:transit-summaries:v1`: AIS relay compact transit summary.
## Known Limits
- The seven live-flow rows are energy-baseline-backed; the other six monitored
waterways do not yet publish mb/d estimates.
- The [Dover Strait](https://www.worldmonitor.app/chokepoints/dover-strait/) live-flow row currently maps to the EIA `danish` baseline id.
Treat `baselineMbd` as the source reference and `id` as the canonical
WorldMonitor row id.
- AIS and PortWatch coverage can degrade near heavily jammed or conflict-heavy
regions. Missing upstream coverage is surfaced as unavailable data, not
synthesized as zero traffic.
- Baselines are annual EIA reference levels used for mb/d conversion. The live
ratio itself uses recent PortWatch observations against the prior rolling
baseline window described above.
## Corrections
See [`/corrections`](/docs/corrections) for the planned revision-log shape. If you
spot a wrong number today, open a GitHub issue at the
[public repository](https://github.com/koala73/worldmonitor/issues).
## Chokepoint explainers
### blog-site/src/content/blog/what-is-a-maritime-chokepoint.md
A maritime chokepoint is a narrow passage where a large share of global trade, energy, food, or military movement must pass through a small physical space.
Chokepoints matter because rerouting is expensive, slow, or sometimes impossible. When a canal, strait, or sea lane is disrupted, the effects can move from vessel schedules to freight rates, commodity prices, insurance costs, factory inventories, and national security planning.
The familiar examples are the Strait of Hormuz, Suez Canal, Panama Canal, Bab el-Mandeb, Strait of Malacca, Bosporus, and Taiwan Strait. But the operational question is not just "is this place famous?" It is:
> Is the passage strategically concentrated, exposed to disruption, and connected to a trade or energy flow that matters?
That is the question WorldMonitor's chokepoint model tries to make visible.
## Why chokepoints matter
Chokepoints turn geography into market and security risk.
If a ship can choose between several similar routes, a disruption may be annoying but manageable. If many routes collapse into one narrow passage, the same disruption can become systemic.
Chokepoints matter for five reasons:
- Volume concentration: many vessels or high-value cargoes pass through the same corridor.
- Energy exposure: oil, LNG, refined products, or petrochemicals depend on the route.
- Military pressure: naval conflict, mines, seizures, or escort zones change behavior.
- Insurance and freight cost: even partial risk can raise costs before a route closes.
- Substitution limits: alternate routes may add days, fuel, port congestion, or political constraints.
A chokepoint does not need to close completely to matter. A credible threat, navigation warning, or traffic anomaly can be enough to change routing and pricing.
## The monitored-waterway registry
WorldMonitor's canonical chokepoint registry includes:
| Canonical id | Public name |
|---|---|
| `hormuz_strait` | [Strait of Hormuz](https://www.worldmonitor.app/chokepoints/strait-of-hormuz/) |
| `malacca_strait` | [Strait of Malacca](https://www.worldmonitor.app/chokepoints/strait-of-malacca/) |
| `suez` | [Suez Canal / SUMED](https://www.worldmonitor.app/chokepoints/suez-canal/) |
| `bab_el_mandeb` | [Bab el-Mandeb](https://www.worldmonitor.app/chokepoints/bab-el-mandeb/) |
| `panama` | [Panama Canal](https://www.worldmonitor.app/chokepoints/panama-canal/) |
| `taiwan_strait` | [Taiwan Strait](https://www.worldmonitor.app/chokepoints/taiwan-strait/) |
| `cape_of_good_hope` | [Cape of Good Hope](https://www.worldmonitor.app/chokepoints/cape-of-good-hope/) |
| `gibraltar` | [Strait of Gibraltar](https://www.worldmonitor.app/chokepoints/strait-of-gibraltar/) |
| `bosphorus` | [Bosporus Strait](https://www.worldmonitor.app/chokepoints/bosporus-strait/) |
| `korea_strait` | [Korea Strait](https://www.worldmonitor.app/chokepoints/korea-strait/) |
| `dover_strait` | [Dover Strait](https://www.worldmonitor.app/chokepoints/dover-strait/) |
| `kerch_strait` | [Kerch Strait](https://www.worldmonitor.app/chokepoints/kerch-strait/) |
| `lombok_strait` | [Lombok Strait](https://www.worldmonitor.app/chokepoints/lombok-strait/) |
All 13 can receive status, threat classification, warning context, AIS-disruption matching, disruption score, and war-risk tier.
Only seven of those 13 currently publish live oil/gas flow estimates backed by EIA baseline IDs: Hormuz, Malacca, Suez, Bab el-Mandeb, Dover, Bosporus, and Panama. The other six can still be strategically important, but they do not yet carry the same baseline-backed `flowEstimate` field.
That distinction prevents a common analytics mistake: showing a missing flow estimate as if it were zero traffic. Missing modeled flow is not the same thing as no flow.
## How WorldMonitor scores chokepoint status
The public status badge is a traffic-light score: green, yellow, or red. It is not a literal closure label.
The disruption score combines:
- a baseline geopolitical threat weight
- active NGA navigational warnings
- AIS congestion severity
- a transit anomaly bonus when PortWatch daily transits drop sharply under high-threat conditions
Nothing else moves the number. AIS event counts, relay transit counts, and PortWatch week-over-week movement are published as context rather than score inputs. PortWatch supplies both: the anomaly bonus compares its daily transit history, seven days against the prior thirty, while the week-over-week figure on the page is presentation only.
The score is capped at 100. Green is below 20, yellow is 20 to 49, and red is 50 or higher.
That design matters because chokepoint risk has multiple modes. A normal route with one warning is not the same as a war-zone route with falling traffic and high AIS disruption. The badge is a compact way to expose combined pressure, not a claim that a waterway is physically closed.
## How live flow estimates work
For the seven energy-baseline-backed waterways, WorldMonitor computes live flow by comparing recent PortWatch observations with a prior rolling baseline. The model uses tanker deadweight tonnage when coverage is good enough; otherwise it can use tanker counts. It publishes current million-barrels-per-day estimates by multiplying the observed flow ratio by the annual EIA baseline.
The ratio can range up to 150 percent of baseline after clamping. A separate `disrupted` boolean is true only when the latest three individual days are all below 85 percent of the same baseline window.
This is a conservative approach. It avoids calling a thin or missing series "zero," and it separates a color badge from the energy-flow model.
## How to read a chokepoint alert
When a chokepoint turns yellow or red, ask four questions:
1. Is the problem physical, military, weather-related, regulatory, or data-coverage related?
2. Is traffic actually changing, or is the threat score rising before traffic moves?
3. Which commodities, countries, or sectors depend on the route?
4. What alternate route exists, and how costly is the detour?
For operational decisions, the fourth question is often the most important. A disruption with a cheap alternate route is different from one that forces ships around a continent or cuts off a specialized cargo flow.
For operational follow-through, connect this explainer to the [supply-chain scenario engine](/blog/posts/stress-test-supply-chain-scenario-engine-worldmonitor/) and the [global trade route monitoring guide](/blog/posts/tracking-global-trade-routes-chokepoints-freight-costs/).
## Source transparency
WorldMonitor's chokepoint status combines Redis-backed transit summaries, flow estimates, navigational warnings, AIS disruption matching, and a static threat taxonomy. Upstream gaps are surfaced as unavailable data rather than silently turned into calm conditions.
The model has known limits. AIS coverage can degrade near conflict zones or regions with jamming. Only the seven energy-baseline waterways have live oil/gas flow estimates today. Baseline values are used to convert observed ratios into flow estimates; they are not a promise that live observations perfectly capture every vessel.
For independently published baselines and current definitions, see the U.S. Energy Information Administration's [World Oil Transit Chokepoints analysis](https://www.eia.gov/international/content/analysis/special_topics/World_Oil_Transit_Chokepoints/).
## Frequently Asked Questions
**Is a red chokepoint always closed?**
No. Red means the combined disruption score is high. It can reflect military threat, active warnings, AIS disruption, anomaly signals, or several of those at once.
**Why do only some waterways have live flow estimates?**
Because those seven have EIA baseline IDs in the current energy-flow seeder. The other canonical waterways can still have status and risk context without publishing an oil/gas flow estimate.
**What is the most important chokepoint?**
It depends on the decision. Hormuz is central for Gulf energy, Malacca for Asia-Europe trade, Suez and Bab el-Mandeb for the Red Sea corridor, Panama for canal capacity, and Taiwan for East Asian strategic risk.
---
**A chokepoint is where geography removes optionality. The risk is not just traffic today, but how little room the system has when that traffic changes.**
### blog-site/src/content/blog/tracking-global-trade-routes-chokepoints-freight-costs.md
> **Key Takeaways:** In the March 15, 2026 snapshot, Strait of Hormuz traffic was down 94.4%. World Monitor combines its canonical waterway registry, freight indices, WTO trade policy, and critical-mineral concentration in one dashboard.
The Strait of Hormuz carries about 20% of global petroleum liquids consumption. In the March 15, 2026 snapshot, [World Monitor's](https://www.worldmonitor.app) chokepoint tracker showed traffic down 94.4% week-over-week, with tanker transits falling from 60+ daily to single digits and a 99% disruption score.
This was not a hypothetical scenario for a risk assessment deck. The dashboard continues to track live conditions, while the figures below remain an explicitly dated case study.
*Data as of March 15, 2026. Values update in real time on the dashboard.*
## The Hormuz Crisis in Real Time
The Iran-Israel conflict has turned the Persian Gulf into an active confrontation zone. Iranian naval blockade risks, mines reported in shipping lanes, and 1,300+ security incidents in the past seven days have effectively shut down the world's most critical energy chokepoint.
World Monitor's Supply Chain panel shows this in one view:
- **85/100 disruption score** with red status
- **94.4% week-over-week traffic decline**
- **99% disruption rate** across the corridor
- **Transit history chart** showing the cliff-edge collapse in late February
- **AI-generated shipping advisory**: reroute via Suez Canal (adds 8-10 days, $150,000-$220,000 per transit), avoid Dubai anchorage, suspend Iran/Iraq crude exports until confrontations cease
The chart tells the story: tanker and cargo traffic that had been steady at 40-70 vessels daily suddenly dropped to near zero. This is not a gradual decline. It is a sudden shutdown of one of the world's most important trade arteries.
## Thirteen Maritime Chokepoints Monitored in Real Time
The Hormuz crisis was the most severe in this snapshot, but it was not the only corridor under pressure. World Monitor tracks 13 critical maritime chokepoints, each scored by disruption level, vessel traffic, and [conflict intensity](/blog/posts/track-global-conflicts-in-real-time/):
The following table highlights eight of the 13 monitored corridors as of mid-March 2026. Open a corridor name to check its latest published observations; the table remains a dated case study:
| Corridor | Status | Key Risk |
|----------|--------|----------|
| **[Strait of Hormuz](https://www.worldmonitor.app/chokepoints/strait-of-hormuz/)** | Critical | Iran-Israel war, naval blockade, mines |
| **[Kerch Strait](https://www.worldmonitor.app/chokepoints/kerch-strait/)** | Red | Russia controls Kerch Bridge, Azov grain exports restricted |
| **[Bab el-Mandeb](https://www.worldmonitor.app/chokepoints/bab-el-mandeb/)** | Yellow | Houthi attacks on commercial shipping |
| **[Suez Canal](https://www.worldmonitor.app/chokepoints/suez-canal/)** | Yellow | Red Sea conflict spillover, Iran-Israel war adjacency |
| **[Bosporus Strait](https://www.worldmonitor.app/chokepoints/bosporus-strait/)** | Elevated | Black Sea grain corridor tensions |
| **[Taiwan Strait](https://www.worldmonitor.app/chokepoints/taiwan-strait/)** | Yellow | PLA military exercises, semiconductor supply risk |
| **[Cape of Good Hope](https://www.worldmonitor.app/chokepoints/cape-of-good-hope/)** | Green | Rerouting destination for Hormuz/Suez diversions |
| **[Dover Strait](https://www.worldmonitor.app/chokepoints/dover-strait/)** | Green | Europe's busiest shipping lane, currently stable |
Each corridor shows live vessel counts, week-over-week traffic changes, disruption percentages, and risk levels. When you click a corridor, you get the full AI-generated situation assessment with specific shipping recommendations.
## What Makes This Different From Port Trackers
Traditional maritime tracking tools show you where ships are. World Monitor shows you why they are not where they should be.
The corridor disruption table cross-references AIS vessel data with conflict events, navigational warnings, and military activity. When vessel counts drop in the Strait of Hormuz, the system does not just show a number going down. It tells you there are 1,323 security incidents in the past week, Iranian naval confrontations in the shipping lanes, and mines reported in the Persian Gulf.
The AI advisory goes further: it recommends specific alternative routes, estimates the cost increase per transit, identifies which cargo types should use air freight instead, and warns against specific anchorage points.
## Real-Time Freight Cost Tracking
When chokepoints close, freight costs spike. World Monitor tracks nine freight indices that quantify the cost impact of disruptions:
**Container Rates:**
- **SCFI** (Shanghai Containerized Freight Index): composite container shipping costs from Shanghai, the world's busiest port. Currently at 1,710, up 14.9% as rerouting demand increases
- **CCFI** (China Containerized Freight Index): broader Chinese container export costs. At 1,072, up 1.7%
**Bulk Shipping:**
- **BDI** (Baltic Dry Index): the benchmark for dry bulk shipping costs (iron ore, coal, grain). At 1,972, up 2.4%
- **BCI** (Baltic Capesize Index): largest vessels, long-haul routes. At 2,721, up 5.7%, reflecting longer Cape of Good Hope diversions
- **BPI** (Baltic Panamax Index): mid-size vessels, grain and coal. At 1,835
- **BSI** (Baltic Supramax Index): regional trade vessels. At 1,290
- **BHSI** (Baltic Handysize Index): smaller vessels, coastal trade. At 807
**Economic Indicators:**
- **Deep Sea Freight Producer Price Index** (BLS): long-term freight cost trends with 24-month history
- **Freight Transportation Services Index** (BTS): overall freight sector activity
When you see the Hormuz disruption score at 99% and the Capesize Index up 5.7% in the same dashboard, the connection is immediate: ships that would have taken the short route through Hormuz are now going around Africa, and the cost of booking those larger vessels is climbing. For more on how these costs ripple into [commodity markets](/blog/posts/monitor-global-supply-chains-and-commodity-disruptions/), see our commodity monitoring guide.
## Trade Policy Intelligence
Supply chain disruptions do not happen in isolation. They intersect with trade policy: tariffs, restrictions, and barriers that shape where goods can flow even when shipping lanes are open.
World Monitor's Trade Policy panel tracks:
- **Trade Restrictions**: WTO-reported measures by country, showing which economies are tightening import/export controls
- **Tariff Trends**: applied tariff rates between major trading partners over time
- **Trade Flows**: bilateral trade volumes between economies (e.g., US-China, US-EU), tracking shifts in trade patterns
- **Trade Barriers**: SPS (Sanitary and Phytosanitary) and TBT (Technical Barriers to Trade) measures that create non-tariff obstacles
- **US Customs Revenue**: Treasury collection data that reflects real trade volumes hitting US ports
When the Strait of Hormuz closes, the trade policy data shows the second-order effects: which countries depend on Gulf oil imports, which alternative suppliers face their own trade restrictions, and whether tariff structures make rerouting economically viable.
## Critical Minerals: Concentration Risk
Some supply chains cannot be rerouted because the supply itself is concentrated in a handful of countries. The Critical Minerals tab tracks this concentration risk using the HHI (Herfindahl-Hirschman Index), where anything above 2,500 indicates high concentration:
| Mineral | Top Producer | Share | HHI Score | Risk |
|---------|-------------|-------|-----------|------|
| **Gallium** | China | 96% | 9,280 | Critical |
| **Cobalt** | DRC | 80% | 6,633 | Critical |
| **Germanium** | China | 77% | 6,085 | Critical |
| **Rare Earths** | China | 71% | 5,327 | Critical |
| **Lithium** | Australia | 50% | 3,529 | High |
Gallium at 9,280 means the global supply is almost entirely dependent on a single country. When China announced gallium and germanium export controls in 2023, the semiconductor industry had no short-term alternative. World Monitor makes this concentration visible, so supply chain teams can assess exposure before restrictions are announced.
## How It All Connects
Consider the current Hormuz crisis through all four dimensions:
1. **Chokepoints**: Hormuz at 99% disruption, vessels rerouting to Suez and Cape of Good Hope
2. **Freight Costs**: Capesize Index up 5.7% (longer routes need bigger ships), SCFI up 14.9% (container demand shifting)
3. **Trade Policy**: Gulf oil exports affected by the conflict, alternative suppliers face their own trade barriers
4. **Critical Minerals**: Qatar LNG exports transit Hormuz. Disruption affects downstream petrochemical inputs for battery manufacturing
No single data source shows this full picture. World Monitor puts chokepoint status, freight indices, trade policy, and mineral supply risk in one panel, updated in real time. Combined with [AI-powered forecasting](/blog/posts/prediction-markets-ai-forecasting-geopolitics/), you can see not just what is happening, but where the situation is heading. And if you want these signals in your own systems rather than a dashboard, the API exposes the same data: here is [how to build a supply-chain early-warning system](/blog/posts/build-supply-chain-early-warning-system-api/) with route scoring and disruption webhooks.
## The Data Sources
Transparency matters. Here is where the data comes from:
- **Vessel transit data**: AIS (Automatic Identification System) feeds, cross-referenced with historical baselines
- **Conflict events**: [ACLED](https://acleddata.com/) (Armed Conflict Location & Event Data Project), 7-day rolling windows
- **Shipping advisories**: AI-generated from combined conflict, navigational, and AIS disruption signals
- **Container indices**: [Shanghai Shipping Exchange (SSE)](https://en.sse.net.cn/) public JSON API
- **Bulk indices**: [Baltic Exchange](https://www.balticexchange.com/) via HandyBulk daily reports
- **Economic indices**: [FRED](https://fred.stlouisfed.org/) (Federal Reserve Economic Data)
- **Trade policy**: [WTO I-TIP](https://i-tip.wto.org/) (Integrated Trade Intelligence Portal)
- **Critical minerals**: [USGS](https://www.usgs.gov/centers/national-minerals-information-center) mineral commodity data with HHI calculations
All sources are public. No proprietary data feeds. No paywall.
## Frequently Asked Questions (Track Trade Routes, Chokepoints, and Freight Costs)
**What is the Baltic Dry Index (BDI)?**
The BDI measures the cost of shipping dry bulk commodities (iron ore, coal, grain) on major ocean routes. It is widely used as a leading indicator of global trade activity because it reflects real demand for shipping capacity, not speculation.
**How does the Strait of Hormuz affect oil prices?**
About 20% of global petroleum liquids consumption and a major share of LNG trade pass through Hormuz. When traffic drops or the strait is threatened, energy markets price in supply-disruption risk. The 94.4% decline cited in this article is a dated March 15, 2026 snapshot, not a current reading.
**What are the world's most critical shipping chokepoints?**
World Monitor monitors its canonical waterway registry, including Hormuz, Malacca, Suez/SUMED, Bab el-Mandeb, Panama, Taiwan, Cape of Good Hope, [Gibraltar](https://www.worldmonitor.app/chokepoints/strait-of-gibraltar/), Bosporus, Korea, Dover, Kerch, and Lombok. Entries with EIA-backed oil or gas baselines publish flow estimates; every entry can carry traffic, warning, threat, and disruption context. See the [maritime chokepoint methodology](/blog/posts/what-is-a-maritime-chokepoint/) for the registry and coverage limits.
---
**Open the Supply Chain panel at [worldmonitor.app](https://www.worldmonitor.app) and click "Chokepoints" for live corridor disruption scores, or "Shipping Rates" to see real-time freight indices. Free for everyone.**
### blog-site/src/content/blog/energy-shock-monitoring-chokepoints-worldmonitor.md
An energy shock rarely starts as a chart. It starts as a closure rumor, a tanker reroute, a fuel shortage, a policy announcement, a port delay, a pipeline disruption, or a military signal near a chokepoint. By the time the price chart explains it, the operational window has already narrowed.
WorldMonitor helps energy analysts watch the chain before it becomes one number on a terminal: maritime chokepoints, fuel shortages, energy disruptions, commodity prices, country risk, news intelligence, and policy response. For the route side of the problem, start with the guide to [tracking chokepoints and freight costs](/blog/posts/tracking-global-trade-routes-chokepoints-freight-costs/); for the market side, pair it with [real-time market intelligence for traders](/blog/posts/real-time-market-intelligence-for-traders-and-analysts/).
This is a practical workflow for monitoring energy-shock risk.
For a worked example, open the [Strait of Hormuz tracker](https://www.worldmonitor.app/chokepoints/strait-of-hormuz/) to inspect its latest published transit and disruption readings. The [historical Strait of Hormuz Transit Report for July 2026](https://www.worldmonitor.app/research/strait-of-hormuz-transit-report-2026-07/) provides a dated comparison with Suez, Bab el-Mandeb, and the Cape of Good Hope. Its figures describe that report's observation period, not current traffic.
For country context, open the [Iran](https://www.worldmonitor.app/countries/iran/) and [Oman](https://www.worldmonitor.app/countries/oman/) profiles. The [Gulf security tracker](https://www.worldmonitor.app/crises/hormuz-gulf-security/) summarizes conflict data for its stated regional coverage. The separate [Iran–Israel escalation tracker](https://www.worldmonitor.app/crises/iran-israel-escalation/) covers those two countries only.
## What is energy shock monitoring?
Energy shock monitoring is the process of tracking the signals that can disrupt oil, gas, electricity, fuel distribution, or energy-linked commodities before the disruption fully appears in price or inventory data.
A useful monitor combines these layers:
| Layer | Example signals |
|---|---|
| Transit | Hormuz, Suez, Malacca, Bab-el-Mandeb, Panama, port activity |
| Supply | Energy disruptions, fuel shortages, pipeline or infrastructure incidents |
| Price | Oil, gas, electricity, gold, FX, energy-sensitive equities |
| Policy | Export controls, rationing, subsidies, emergency reserves, crisis policies |
| Security | Conflict, sanctions, military posture, cyber threats, country instability |
The value is not any one signal. The value is seeing them together.
## Build the watchlist
Start with the physical routes and countries that matter to your exposure:
```json
{
"chokepoints": ["strait-of-hormuz", "suez", "bab-el-mandeb", "malacca", "panama"],
"countries": ["SA", "AE", "IR", "IQ", "QA", "EG", "TR", "RU", "US", "CN"],
"markets": ["CL=F", "BZ=F", "NG=F", "GC=F", "DXY"]
}
```
Then map each watchlist item to a decision:
| Watch item | Decision it informs |
|---|---|
| Hormuz and Bab-el-Mandeb | Tanker route risk, insurance, crude exposure |
| Suez and Panama | Transit time, freight cost, inventory buffers |
| Gulf producers | Supply continuity and policy posture |
| Fuel shortage data | Retail or humanitarian exposure |
| Oil and gas prices | Hedge review and customer surcharge triggers |
## Pull the core WorldMonitor signals
### 1. Chokepoint status
Use `get_chokepoint_status` to monitor maritime transit and route posture.
```json
{
"name": "get_chokepoint_status",
"arguments": {
"jmespath": "chokepoints[?contains(['strait-of-hormuz','suez','bab-el-mandeb','malacca','panama'], slug)].{slug:slug, status:status, risk:risk, transit:transitSummary, stale:stale, cached_at:cached_at}"
}
}
```
If chokepoint status changes, do not jump straight to "crisis." Ask what changed: vessel counts, narrative risk, port activity, conflict context, or market response.
### 2. Energy intelligence
Use `get_energy_intelligence` for the broader supply picture: energy supply, storage, electricity prices, fuel shortages, active disruptions, and government crisis policies.
Ask for the fields you need:
```json
{
"name": "get_energy_intelligence",
"arguments": {
"jmespath": "{fuelShortages:fuelShortages, disruptions:disruptions, policies:policies, storage:storage, cached_at:cached_at, stale:stale}"
}
}
```
### 3. Country and conflict risk
Energy shocks are often geographic. Pair route and supply signals with country risk:
- `get_country_risk` for CII score, component drivers, advisory provenance, and sanctions exposure
- `get_conflict_events` for active conflict and unrest
- `get_military_posture` for strategic theater context
- `get_sanctions_data` for policy and compliance exposure
### 4. Market confirmation
Pull `get_market_data` for oil, gold, FX, crypto, Gulf markets, sector performance, and related instruments. Market movement is not proof of disruption, but it is a useful confirmation layer.
### 5. News intelligence
Use `get_news_intelligence` to determine whether the risk is isolated, spreading, or being confirmed by multiple sources.
## Score the shock risk
Use a transparent score that operators can inspect:
```text
energyShockRisk =
0.30 * transitStress +
0.25 * supplyDisruption +
0.20 * marketMove +
0.15 * securityRisk +
0.10 * policyResponse
```
Then define action levels:
| Score | Label | Operational action |
|---|---|---|
| 0-30 | Normal | Routine monitoring |
| 31-50 | Watch | Add to morning brief |
| 51-70 | Elevated | Review exposure, hedges, and routing |
| 71-85 | Severe | Escalate to operations and finance |
| 86-100 | Critical | Convene crisis workflow |
Keep the components visible. "Severe because transit stress and policy response both moved" is useful. "Severe" alone is not.
## Example daily brief
Use this format:
```text
Energy shock watch
Status: elevated
Freshness: chokepoint data fresh; energy disruptions stale=false
Changed since yesterday:
- Hormuz route risk moved from watch to elevated.
- Fuel shortage count rose in two monitored countries.
- Brent and gold both moved above internal threshold.
- News confirmation remains concentrated, not yet broad.
Interpretation:
This is a route and price-risk event, not yet a broad supply outage. Review tanker exposure and customer surcharge triggers. Re-run at 12:00 UTC.
Next checks:
1. Chokepoint transit summary
2. Energy disruption feed
3. Country risk for Gulf producers
4. Brent/WTI and Gulf market quote movement
```
## Use scenario analysis when exposure is high
When a chokepoint becomes the main driver, pair live monitoring with the [Scenarios API](https://www.worldmonitor.app/docs/api-scenarios). Scenario templates let you ask what happens if a route disruption lasts a defined number of days or affects a specific country set.
Use it for planning, not prediction. Scenario output answers "what would be exposed if..." rather than "what will happen next."
## Primary Energy Reference
Baseline flow estimates and strategic context should be checked against the EIA's [World Oil Transit Chokepoints](https://www.eia.gov/international/content/analysis/special_topics/World_Oil_Transit_Chokepoints/) analysis. Live risk scores add warning context but do not override the source agency's published methodology.
## Frequently Asked Questions (Energy Shock Monitoring: Chokepoints, Fuel, and Markets)
**What is an energy shock?**
An energy shock is a sudden disruption or repricing of oil, gas, electricity, fuel, or energy-linked infrastructure that affects costs, availability, routing, or policy decisions.
**Which WorldMonitor tools are best for energy shock monitoring?**
Start with `get_chokepoint_status`, `get_energy_intelligence`, `get_market_data`, `get_country_risk`, `get_conflict_events`, `get_sanctions_data`, and `get_news_intelligence`.
**How often should I refresh energy shock data?**
For routine monitoring, refresh every few hours. During active route or conflict events, refresh at least hourly and alert only on state changes or threshold crossings.
**Should I alert on price moves alone?**
No. Price moves are confirmation, not diagnosis. Pair them with route, supply, policy, country, or news signals before escalating.
---
**The strongest energy monitor is not the prettiest chart. It is the one that tells you what changed, why it matters, and which exposure to review next.**
## Country Resilience Index methodology
_Methodology maintained by [Elie Habib](https://www.worldmonitor.app/blog/authors/elie-habib/), founder of World Monitor. Published revisions are recorded in the [corrections log](/docs/corrections)._
## Start here (Country Resilience Index methodology)
The Country Resilience Index answers one question about each of 196 countries:
**when something goes badly wrong, how well can this country absorb it and get
back up?**
It is a single 0-100 score, refreshed every 6 hours, built from 72 published
indicators. A high score does not mean a country is rich, safe, or pleasant to
live in. It means that when a shock arrives — a currency crisis, a blackout, a
drought, a cyberattack, a war next door — that country has the fiscal room, the
institutions, the infrastructure, and the supplies to take the hit and recover.
### How to read a score
| Score | Level | What it means in practice |
|---|---|---|
| 60-100 | **High** | Deep buffers. Absorbs a serious shock without losing basic function. |
| 30-59 | **Medium** | Real capacity, but a large shock would strain it, and recovery may depend on outside help. |
| 0-29 | **Low** | Little slack anywhere. A shock in one area cascades into the others. |
Two things are worth knowing before you compare two countries.
**A country cannot average its way out of a weak spot.** The score deliberately
punishes lopsidedness: a country that is excellent at five things and dire at
the sixth scores below one that is merely good at all six. In a real crisis the
weakest link is what fails, so the formula is built to say so. (This is the
min-pillar penalty in the [scoring formula](#corpus-overall-score).)
**Coverage matters as much as the score.** Every score ships with a coverage
figure saying how much of it rests on real observations rather than inference.
A country whose data is too thin is flagged `lowConfidence` and held out of the
public ranking, rather than quietly ranked on guesswork.
### What it is not
- **Not a wealth ranking**, and [deliberately so](#corpus-construct-contract). An
indicator whose only story is "this country is rich" is excluded by design.
Wealth buys resilience, but the two are not the same thing.
- **Not the [Composite Instability Index](/docs/methodology/cii-risk-scores).** CII
asks *how much stress is on this country right now?* CRI asks *how well could
it take a hit?* A country can be calm and fragile, or under pressure and
tough. The dashboard shows them side by side for exactly that reason.
- **Not a forecast**, and not a verdict on a government.
### How a score gets built
Indicators are rescaled onto a common 0-100 ruler, blended into dimensions,
grouped into domains, regrouped into three pillars, and finally combined with a
penalty anchored to the country's weakest pillar.
```mermaid
flowchart TD
A["72 published indicators"] --> B["Rescale each to 0-100
against fixed goalposts"]
B --> C["21 dimensions
weighted blend of indicators"]
C --> D["Domains
coverage-weighted mean of dimensions"]
D --> E["3 pillars
structural / live shock / recovery"]
E --> F["Weighted mean
0.40 / 0.35 / 0.25"]
F --> G["Min-pillar penalty
the weakest pillar drags the total"]
G --> H["Overall score 0-100"]
```
Each stage is documented below: [normalization](#corpus-normalization),
[dimensions and indicators](#corpus-dimensions-and-indicators),
[domains and weights](#corpus-domains-and-weights), and the
[scoring formula](#corpus-scoring-formula).
### How often it updates
Live API scores refresh every 6 hours. The crawlable country snapshot is published monthly from a credentialed full-universe capture. Each country page identifies its snapshot file, capture date, temporal coverage, and publication note. The [revision and corrections log](/docs/corrections) records material methodology changes that affect published snapshots.
Upstream feeds can include more territories than the published ranking covers. The public ranking is filtered to the rankable universe before publication.
Everything on this page describes the **currently shipping** index: 72 indicators across 21 active dimensions and 6 domains, the `schemaVersion "2.0"` shape, 3 pillars (plus 2 structurally-retired dimensions kept in the registry at `coverage=0` for schema continuity), the pillar-combined penalized `overall_score`, and the energy v2 construct. Version flags, rollback paths, and the runtime manifest are covered under [For developers](#corpus-for-developers).
## Construct contract
**In plain terms:** rich countries tend to be resilient, but "rich" is not what
this index measures. If an indicator's only explanation for why it belongs is
that wealthy countries score well on it, it is thrown out — no matter how well
it correlates with resilience in the historical record. Indicators earn their
place by naming a specific shock they help absorb.
That rule is what stops CRI collapsing into a GDP ranking with extra steps, and
it is why some wealthy countries score lower here than readers expect.
Country Resilience measures **absolute national shock-absorption and recovery capacity at a point in time**. It does not adjust for income level. Development-adjacent indicators enter only when they measure a direct resilience mechanism. Those indicators use threshold or saturating transforms so the score rewards functional capacity, not affluence itself. Peer-relative over- and under-performance will be published separately as an analytical overlay, not inside the core score.
The scorer will treat development as relevant only where it creates a direct and measurable shock-absorption mechanism. Pure level-of-affluence proxies are excluded. Development-relative overperformance will be reported separately and will not alter the ordinal country ranking.
Every indicator in the scorer is evaluated against a single **mechanism test**: *what direct shock channel does this measure?* An indicator whose only answer is "this country is rich" is excluded from the core score regardless of its historical correlation with resilience outcomes. An indicator whose answer is "capacity X absorbs shock Y" can enter but must use a threshold or saturating transform so it rewards the mechanism rather than the level of resource that drives it.
Current production already reflects the recovery-domain, currency/external, and energy construct repairs described below: `reserveAdequacy` and `fuelStockDays` are structurally retired, `liquidReserveAdequacy` and `sovereignFiscalBuffer` are active, `currencyExternal` scores from IMF inflation plus World Bank reserves, `energy` uses the v2 power-system-security construct, and the coverage/influence cap is enforced in tests. The legacy energy scorer remains in code only as the emergency rollback path for `RESILIENCE_ENERGY_V2_ENABLED=false`.
## In the dashboard
CRI is surfaced across three places in the product, all driven from the same currently-shipping score:
- **Resilience widget** — a standalone panel (component: `src/components/ResilienceWidget.ts`) that ranks countries by resilience score with filter and search affordances. Reach it from Cmd+K by typing *resilience*.
- **Country Deep-Dive** — inside the per-country drill-down panel, CRI appears alongside CII (Country Instability Index) as a structural complement to the short-horizon stress signal. CII and CRI are intentionally **not interchangeable**: CII answers "how much stress is on this country right now?"; CRI answers "how well-positioned is this country to absorb and recover from shocks?"
- **Map choropleth** — the resilience score drives a country-level choropleth layer on the main map. Toggle it from the map's layer panel or via Cmd+K.
All three dashboard surfaces are free to view. Direct score and ranking API calls require the normal Pro/API auth path, while the runtime manifest is public at `/api/resilience/v1/get-runtime-manifest`; see [Resilience service](https://github.com/koala73/worldmonitor/blob/main/docs/api/ResilienceService.openapi.yaml) for the HTTP contract.
The Pro-only `/api/resilience/v1/get-resilience-indicators` method explains one country across the complete 72-row registry. It reports the exact normalized component scores and runtime weights used by the active scorer, then reconciles post-policy effective contributions to each published dimension score. Rows also distinguish observed, imputed, missing, fallback, source-failure, inactive, retired, and not-applicable states. The existing `get-resilience-score` response remains unchanged. Raw source values are selective and fail closed under the [indicator redistribution audit](./resilience-indicator-licensing.mdx); restricted rows still return WorldMonitor's normalized score, contribution, source attribution, and source year when known.
## What goes into it
The score mixes three kinds of evidence, which is what separates it from a
static country profile:
- **Structural baselines** that move slowly — governance quality, health
infrastructure, fiscal capacity.
- **Live stress signals** that move daily — cyber threats, conflict events,
shipping disruption.
- **Recovery capacity** — the fiscal space, reserves, and supply diversity a
country would draw on afterwards.
Data comes from official and authoritative providers: World Bank, IMF, WHO, WTO, UNHCR, UCDP, BIS, IEA, FAO, Reporters Sans Frontieres, and the Institute for Economics and Peace, among others. The full list is in [Data Sources](#corpus-data-sources-country-resilience-index-methodology).
CRI scores the 196-country public rankable universe on a 0-100 scale using 72 indicators across 21 active dimensions and 6 domains, plus 2 structurally-retired dimensions kept in the registry at `coverage=0` for schema continuity. The ranking handler can route low-confidence or headline-ineligible countries to `greyedOut[]`, but the rankable universe itself is fixed by the committed UN-member + SAR whitelist.
## Domains and Weights
The index is organized into 6 domains. Each domain weight reflects its design contribution to national resilience. Under the active pillar-combined formula, the weight sets that domain's relative influence inside its pillar, scaled by the domain's average dimension coverage. Under the legacy six-domain rollback formula, the same weights are used directly in the flat domain aggregate. Recovery carries the largest single-domain weight (0.25) because the ability to absorb and recover from a shock is the single best structural predictor of post-shock outcomes; this is why fiscally strong smaller states cluster at the top of the ranking and fragile states separate cleanly at the bottom.
| Domain | ID | Weight | Dimensions |
|---|---|---|---|
| Economic | `economic` | 0.17 | Macro-Fiscal, Currency & External, Trade Policy, Financial System Exposure |
| Infrastructure | `infrastructure` | 0.15 | Cyber & Digital, Logistics & Supply, Infrastructure |
| Energy | `energy` | 0.11 | Energy |
| Social & Governance | `social-governance` | 0.19 | Governance, Social Cohesion, Conflict & Displacement, Information, Education |
| Health & Food | `health-food` | 0.13 | Health & Public Service, Food & Water |
| Recovery | `recovery` | 0.25 | Fiscal Space, External Debt Coverage, Import Concentration, State Continuity, Liquid Reserve Adequacy, Sovereign Fiscal Buffer |
Weights sum to 1.00. The authoritative values live in `RESILIENCE_DOMAIN_WEIGHTS` in `server/worldmonitor/resilience/v1/_dimension-scorers.ts`; if this table and the code disagree, the code wins. In the active `pc` formula, absolute top-level influence also depends on the outer pillar weights.
The 6 domains are regrouped into 3 pillars (structural-readiness, live-shock-exposure, recovery-capacity) with weights 0.40 / 0.35 / 0.25 for the Phase 2 pillar-combined score. The pillar shape is emitted today on every response (`schemaVersion="2.0"`, `pillars[]` populated with real domain-weighted, coverage-scaled scores). The top-level `overallScore` is computed by `_shared.ts#penalizedPillarScore`: the weighted pillar mean multiplied by the min-pillar penalty factor `(1 - 0.5 * (1 - min_pillar / 100))`.
| Pillar | Weight | Member domains |
|---|---:|---|
| `structural-readiness` | 0.40 | `economic`, `social-governance` |
| `live-shock-exposure` | 0.35 | `infrastructure`, `energy`, `health-food` |
| `recovery-capacity` | 0.25 | `recovery` |
## Dimensions and Indicators
Each dimension is scored from 0-100 using a weighted blend of its sub-metrics. Below is the complete indicator registry.
### Economic Domain (weight 0.17)
The Economic domain has four active dimensions. `macroFiscal` and
`currencyExternal` carry the default per-dimension weight `1.0`.
`tradePolicy` and `financialSystemExposure` each carry weight `0.5`, splitting
the Phase 2 trade-and-financial-exposure design space so tariff-policy friction
and cross-border financial-system exposure do not each claim a full equal-share
slot. With all four economic dimensions at full coverage, their economic-domain
shares are approximately 33.3%, 33.3%, 16.7%, and 16.7%.
| Dimension | Weight | Share at full coverage |
|---|---:|---:|
| `macroFiscal` | 1.0 | 33.3% |
| `currencyExternal` | 1.0 | 33.3% |
| `tradePolicy` | 0.5 | 16.7% |
| `financialSystemExposure` | 0.5 | 16.7% |
Note: the share column assumes `RESILIENCE_FIN_SYS_EXPOSURE_ENABLED=true`;
with the default flag-off posture, the live economic shares are 40%, 40%, 20%,
and 0%.
#### Macro-Fiscal
| Indicator | Description | Direction | Goalposts (worst-best) | Weight | Source | Cadence |
|---|---|---|---|---|---|---|
| govRevenuePct | Government revenue as % of GDP (IMF GGR_G01_GDP_PT) | Higher is better | 5 - 45 | 0.40 | IMF | Annual |
| debtGrowthRate | Annual debt growth rate | Lower is better | 20 - 0 | 0.20 | National debt data | Annual |
| currentAccountPct | Current account balance as % of GDP (IMF) | Higher is better | -20 - 20 | 0.20 | IMF | Annual |
| unemploymentPct | Unemployment rate (IMF WEO LUR) | Lower is better | 25 - 3 | 0.15 | IMF | Annual |
| householdDebtService | BIS household debt service ratio (% income) | Lower is better | 20 - 0 | 0.05 | BIS | Quarterly |
#### Currency & External
PR 3 §3.5 point 2 retired the BIS REER-backed core construct. BIS REER covers only the BIS-reporting economy set, so the old composite fell through to curated_list_absent (coverage 0.3) or a thin IMF proxy (coverage 0.45) for roughly two-thirds of the 196-country public rankable universe. The rebuilt dimension uses two globally-covered World Bank / IMF series. BIS household debt-service ratio remains a separate `macroFiscal` source (`economic:bis:dsr:v1`) and does not drive `currencyExternal`.
| Indicator | Description | Direction | Goalposts (worst-best) | Weight | Source | Cadence |
|---|---|---|---|---|---|---|
| inflationStability | Headline consumer inflation, % YoY (IMF WEO); primary signal for currency stability globally | 1-3% target band is best | <= -5 or >= 50 -> 0; 1-3 -> 100 | 0.60 | IMF | Annual |
| fxReservesAdequacy | Total reserves in months of imports (World Bank FI.RES.TOTL.MO) | Higher is better | 1 - 12 | 0.40 | World Bank | Annual |
Coverage ladder (post-PR-3): both present → 0.85; inflation only → 0.55; reserves only → 0.40; neither → 0.30 (curated_list_absent imputation, subject to source-failure re-tagging on adapter outage).
Retained as experimental (enrichment-only, ~64 BIS-reporting countries): `fxVolatility` (annualized BIS REER volatility, 50-0 goalpost) and `fxDeviation` (absolute deviation of BIS REER from 100, 35-0). These do not contribute to the core overall score; they surface on the country drill-down for BIS-tracked economies.
#### Trade Policy
Renamed from "Trade & Sanctions" in plan 2026-04-25-004 Phase 1 (Ship 1).
The OFAC `sanctionCount` component (was weight 0.45) was dropped — counting
designated-party domicile locations is a corporate-finance liability metric,
not a country-resilience indicator (a transit-hub like UAE or Singapore
hosts many shell-company entries without that reflecting on the host
country's structural resilience). The remaining 3 components were reweighted
to total 1.0. The separate `financialSystemExposure` dimension replaces that
dropped proxy with structural sanctions exposure via BIS Consolidated Banking
Statistics (CBS, `WS_CBS_PUB`) + WB IDS short-term external debt + FATF
AML/CFT listing status. The Redis key is still `economic:bis-lbs:v1` for
historical continuity.
For the full construct rationale and the rejected alternatives (program-
weight categorization, transit-hub exclusion lists), see
[known-limitations.md § tradeSanctions → tradePolicy](./known-limitations.md#tradesanctions-%E2%86%92-tradepolicy-ofac-domicile-component-dropped-ship-1-2026-04-25).
| Indicator | Description | Direction | Goalposts (worst-best) | Weight | Source | Cadence |
|---|---|---|---|---|---|---|
| tradeRestrictions | WTO trade restriction severity from the current one-row-per-reporter seed (`low=0`, `moderate=1`, `high=2`; legacy no-status rows count as moderate) | Lower is better | 2 - 0 | 0.30 | WTO | Weekly |
| tradeBarriers | WTO tariff-gap barrier severity from the current one-row-per-reporter seed (`low=0`, `moderate=1`, `high=2`; legacy no-status rows count as moderate) | Lower is better | 2 - 0 | 0.30 | WTO | Weekly |
| appliedTariffRate | Applied tariff rate, weighted mean, all products (World Bank TM.TAX.MRCH.WM.AR.ZS) | Lower is better | 20 - 0 | 0.40 | World Bank | Annual |
**Tariff-overlap disclosure.** `tradePolicy` is deliberately tariff-heavy after the WTO severity repair: `tradeRestrictions` now uses WTO MFN applied-tariff severity at weight 0.30, `appliedTariffRate` uses the World Bank weighted-mean applied tariff at weight 0.40, and `tradeBarriers` uses WTO tariff-gap severity at weight 0.30. The overlap is intentional because the dimension measures policy friction after the OFAC-domicile component was removed; future tariff-source changes should preserve this disclosure or split the construct explicitly.
#### Financial System Exposure
Added in plan 2026-04-25-004 Phase 2 (Ship 2). Replaces the dropped OFAC-domicile signal (Phase 1) with a structural-exposure construct built from audited cross-border banking + AML/CFT data. Where the OFAC count conflated transit-hub corporate domicile with host-country risk (penalizing financial centers like UAE / Singapore / Hong Kong for shell-entity behavior), this dimension uses sources that measure actual sovereign vulnerability: short-term external debt overhang, concentrated cross-border banking exposure, and AML/CFT compliance status.
The dimension is currently flag-gated. `RESILIENCE_FIN_SYS_EXPOSURE_ENABLED`
defaults to `false`; when the flag is off, the scorer returns the empty-data
shape (`score=0`, `coverage=0`, `observedWeight=0`, `imputedWeight=0`,
`imputationClass=null`) and the dimension contributes no signal through the
coverage-weighted economic-domain mean. This dark default is intentional until
the BIS CBS (`economic:bis-lbs:v1`), FATF listing, and WB external-debt seeders
are provisioned and healthy in production.
When the flag is on, the dimension uses a **fail-closed preflight** pattern
(mirrors `scoreEnergy` v2): all 3 required seed envelopes
(`economic:wb-external-debt:v1`, `economic:bis-lbs:v1`,
`economic:fatf-listing:v1`) MUST be reachable. Missing seed-meta indicates a
Railway bundle outage and surfaces as `imputationClass='source-failure'` rather
than silently zeroing the dim. Per-country data gaps are distinct:
per-component reads return null and the slot drops out of the weighted blend.
The `economic:bis-lbs:v1` payload is produced from BIS Consolidated Banking
Statistics (CBS, `WS_CBS_PUB`), not Locational Banking Statistics; the retained
key name reflects the original draft and is not a source label. Redis key is still `economic:bis-lbs:v1` for historical continuity.
| Indicator | Description | Direction | Goalposts (worst-best) | Weight | Source | Cadence |
|---|---|---|---|---|---|---|
| shortTermExternalDebtPctGni | Short-term external debt as % of GNI ((WB IDS DT.DOD.DSTC.CD / NY.GNP.MKTP.CD) × 100); IMF Article IV vulnerability threshold is 15% GNI | Lower is better | 15 - 0 | 0.35 | World Bank IDS | Annual |
| bisLbsXborderPctGdp | BIS CBS (`WS_CBS_PUB`) sum of by-parent foreign claims (US/UK/major-EU/CH/JP/CA/AU/SG) as % of GDP; asymmetric U-shape band — isolation (0%) is the worst reading at 30, over-exposure is penalized but floors at 35 | Lower is better (U-shape) | 0 - 25 | 0.30 | BIS CBS | Quarterly |
| fatfListingStatus | FATF AML/CFT listing status — black list (call for action) → 0, gray list (increased monitoring) → 55, compliant → 100 | Higher is better | 0 - 100 | 0.20 | FATF | Monthly |
| financialCenterRedundancy | Count of distinct BIS CBS by-parent reporters with non-trivial (>1% GDP) foreign claims; rewards multi-counterparty financial centers, balances Component 2 over-exposure penalty | Higher is better | 1 - 10 | 0.15 | BIS CBS | Quarterly |
**Coverage**: WB IDS publishes for World Bank borrowers only (119 countries in the 2026-08-11 payload). Jurisdictions with no IDS row but a BIS CBS row take an imputed short-term-debt slot (score 75, certainty 0.3, `imputationClass='not-applicable'`) rather than dropping it — absence from the Debtor Reporting System means no reported short-term external commercial debt, not an unknown. Countries absent from both sources keep the null/drop behaviour. FATF + BIS CBS together cover effectively all manifest countries.
**Comprehensive-embargo cap**: jurisdictions under a comprehensive or government-wide Western blocking programme (RU, BY, IR, KP, CU, SY, MM, VE, LY) are capped at 15 after blending. Three of the four graded components read financial severance as strength — thin short-term debt because there is no market access, low cross-border claims because nobody lends, and FATF `compliant` because FATF assesses AML/CFT deficiency rather than sanctions. See [financial-system-exposure.md](./financial-system-exposure.md) for the membership criterion and why a band retune alone cannot carry the signal.
**Data sources and licensing**: BIS data (Components 2 + 4) is published under [BIS terms of use](https://www.bis.org/terms_conditions.htm) — publicly available with attribution; redistribution restricted. WB IDS (Component 1) and FATF (Component 3) are open-data. The BIS-derived indicators are tagged `non-commercial` / `enrichment` in the indicator registry per the existing BIS classification convention; the dimension itself is `core` (contributes to the headline score) per Codex R1 #8.
For the full construct rationale, alternatives considered (program-weight categorization, transit-hub exclusion, single-dim formula rewrite, drop entirely), and the staged rollout decision, see [financial-system-exposure.md](./financial-system-exposure.md).
### Infrastructure Domain (weight 0.15)
#### Cyber & Digital
| Indicator | Description | Direction | Goalposts (worst-best) | Weight | Source | Cadence |
|---|---|---|---|---|---|---|
| cyberThreats | Discovery-day decayed severity-weighted cyber threat count (critical 3x, high 2x, medium 1x, low 0.5x) | Lower is better | 25 - 0 | 0.45 | Cyber threat feeds | Daily |
| internetOutages | Internet outage penalty (total 4x, major 2x, partial 1x) | Lower is better | 20 - 0 | 0.35 | Outage monitoring | Realtime |
| gpsJamming | GPS jamming hex penalty (high 3x, medium 1x) | Lower is better | 20 - 0 | 0.20 | GPSJam | Daily |
#### Logistics & Supply
| Indicator | Description | Direction | Goalposts (worst-best) | Weight | Source | Cadence |
|---|---|---|---|---|---|---|
| roadsPavedLogistics | Paved roads as % of total road network (World Bank IS.ROD.PAVE.ZS) | Higher is better | 0 - 100 | 0.50 | World Bank | Annual |
| shippingStress | Global shipping stress score | Lower is better | 100 - 0 | 0.25 | Supply-chain monitor | Daily |
| transitDisruption | Mean transit corridor disruption | Lower is better | 30 - 0 | 0.25 | Transit summaries | Daily |
**v15 (2026-04-26) — small-state bias fix.** The exposure-weighting
formula `shippingScore × tradeExposure + 100 × (1 − tradeExposure)`
intentionally suppresses global-stress penalties for closed economies
(low trade-to-GDP), where `tradeExposure = min(tradeToGdp / 50, 1.0)`;
but the prior `tradeExposure = 0.5` default for
countries with NO observed trade-to-GDP extended that suppression to
tiny states with no trade-to-GDP data at all (TV, PW, NR), inflating
their shipping/transit components to ~75 in v14. v15 removes the 0.5
default: missing trade-to-GDP now drops the exposure-weighted
components from the dimension entirely (coverage derate to 0.5)
rather than imputing them at "average openness". Closed economies
WITH observed trade-to-GDP keep the neutralizer (Norway, Iceland,
landlocked LICs continue to score correctly).
#### Infrastructure
| Indicator | Description | Direction | Goalposts (worst-best) | Weight | Source | Cadence |
|---|---|---|---|---|---|---|
| electricityAccess | Access to electricity, % of population (World Bank EG.ELC.ACCS.ZS) | Higher is better | 40 - 100 | 0.30 | World Bank | Annual |
| roadsPavedInfra | Paved roads as % of total road network (World Bank IS.ROD.PAVE.ZS) | Higher is better | 0 - 100 | 0.30 | World Bank | Annual |
| infraOutages | Internet outage penalty (shared source with Cyber & Digital) | Lower is better | 20 - 0 | 0.25 | Outage monitoring | Realtime |
| broadband | Fixed broadband subscriptions per 100 people (World Bank IT.NET.BBND.P2) | Higher is better | 0 - 40 | 0.15 | World Bank | Annual |
**Note on the paved-roads indicator.** The same World Bank series (`IS.ROD.PAVE.ZS`) feeds two dimensions inside the Infrastructure domain: `roadsPavedLogistics` under Logistics & Supply (weight 0.50 within the dimension) and `roadsPavedInfra` here under Infrastructure (weight 0.30 within the dimension). This is deliberate source reuse, not accidental double counting: Logistics & Supply uses paved-road coverage as a proxy for transit viability, while Infrastructure uses it as a proxy for baseline public capital stock. The two dimensions legitimately care about the same signal for different reasons, and each dimension's contribution to the domain is further mediated by the dimension weight in `coverage-weighted mean` aggregation (see the Scoring Formula section). The v2.0 reference-grade upgrade plan is expected to consolidate shared upstream signals into a single indicator registry so this kind of reuse is documented at the source level rather than per-dimension; for v1.0 the two separate metric rows are preserved for backward compatibility.
### Energy Domain (weight 0.11)
#### Energy
The `energy` dimension now uses the PR 1 v2 construct repair (plan §3.1-§3.3) in production. The **v2 construct** is the active runtime path when `RESILIENCE_ENERGY_V2_ENABLED=true`; the **legacy construct** remains available only as the emergency rollback path if that flag is set back to `false`. Active runtime state is reported as `constructVersions.energy` in `/api/resilience/v1/get-runtime-manifest` so production can be audited without exposing the raw env flag. The 2026-06-02 post-flip audit observed `constructVersions.energy="v2"` and `/api/health` green for all three v2 seed-meta entries. The indicator registry's flat `tier` field follows this active production construct: v2 global inputs are Core, EU gas storage remains Enrichment because coverage is regional, and legacy-only standalone inputs are Experimental rollback surfaces.
**Legacy construct (rollback only).** Carries three known `wealth-proxy` / denominator-mismatch flaws tracked in `docs/methodology/indicator-sources.yaml` and in "Known construct limitations" at the top of this page. It is retained to make rollback a flag change, not because it is the current methodology.
| Indicator | Description | Direction | Goalposts (worst-best) | Weight | Source | Cadence |
|---|---|---|---|---|---|---|
| energyImportDependency | IEA energy import dependency (% of supply from imports) | Lower is better | 100 - 0 | 0.25 | IEA | Annual |
| gasShare | Natural gas share of energy mix | Lower is better | 100 - 0 | 0.12 | Energy mix data | Annual |
| coalShare | Coal share of energy mix | Lower is better | 100 - 0 | 0.08 | Energy mix data | Annual |
| renewShare | Renewable energy share of energy mix | Higher is better | 0 - 100 | 0.05 | Energy mix data | Annual |
| euGasStorageStress (legacy name: `gasStorageStress`) | Gas storage fill stress: (80 - fillPct) / 80, clamped [0,1] | Lower is better | 100 - 0 | 0.10 | GIE AGSI+ | Daily |
| energyPriceStress | Mean absolute energy price change across commodities | Lower is better | 25 - 0 | 0.10 | Energy prices | Daily |
| electricityConsumption | Per-capita electricity consumption (kWh/year, World Bank EG.USE.ELEC.KH.PC) | Higher is better | 200 - 8000 | 0.30 | World Bank | Annual |
**v2 construct (active; framing decision: Option B, power-system security).** Under v2 the dimension measures **power-system security**, not total-energy security. Electricity grids are the dominant short-horizon shock-transmission channel; transport-fuel security enters via `fuelStockDays`-successor work, and industrial energy security enters via transition-risk indicators on the `economic` domain. The framing choice is what lets the v2 indicator set share one denominator: percent of electricity generation, not percent of primary energy supply. Any future reversal to Option A (primary-energy framing) would require rebuilding `lowCarbonGenerationShare` and `euGasStorageStress` on IEA/BP primary-energy data — out of scope for PR 1.
| Indicator | Description | Direction | Goalposts (worst-best) | Weight | Source | Cadence |
|---|---|---|---|---|---|---|
| importedFossilDependence | `EG.ELC.FOSL.ZS × max(EG.IMP.CONS.ZS, 0) / 100`: fossil share of electricity × net-energy-import share, net exporters collapsed to 0; values above 100 clamp at the worst anchor | Lower is better | 100 - 0 | 0.35 | World Bank | Annual |
| lowCarbonGenerationShare | Low-carbon share of electricity generation from OWID Grapher `share-electricity-low-carbon` (renewables plus nuclear; renewables include hydro). | Higher is better | 0 - 80 | 0.20 | OWID / Ember / Energy Institute | Annual |
| powerLossesPct | Electric power transmission + distribution losses (`EG.ELC.LOSS.ZS`). Direct grid-integrity measure. Weight temporarily absorbs `reserveMarginPct`'s 0.10 until the latter's IEA seeder lands. | Lower is better | 25 - 3 | 0.20 | World Bank | Annual |
| euGasStorageStress | Same transform as `gasStorageStress`, scoped to EU-only (weight 0 for non-EU) | Lower is better | 100 - 0 | 0.10 | GIE AGSI+ | Daily |
| energyPriceStress | Mean absolute energy price change across commodities | Lower is better | 25 - 0 | 0.15 | Energy prices | Daily |
Retired under v2: `electricityConsumption` (wealth proxy, §3.1 of repair plan), `gasShare` / `coalShare` / `energyImportDependency` (replaced by `importedFossilDependence`, §3.2), `renewShare` (absorbed into `lowCarbonGenerationShare`, §3.3). `electricityAccess` moves from `energy` to the `infrastructure` domain under v2, where it acts as a grid-collapse threshold signal rather than an affluence proxy.
**Deferred under v2 (plan §3.1 open-question):** `reserveMarginPct` does not ship in PR 1. IEA electricity-balance coverage is sparse outside OECD+G20; the indicator will likely ship at `tier='unmonitored'` with weight 0.05 if it lands at all. Its Redis key is reserved in `_dimension-scorers.ts`; when a seeder lands, split 0.10 out of `powerLossesPct` and add `reserveMarginPct` at 0.10 in the scorer blend.
**Fail-closed semantics (plan `2026-04-24-001`).** When `RESILIENCE_ENERGY_V2_ENABLED=true` but any of the three required seeds (`resilience:fossil-electricity-share:v1`, `resilience:low-carbon-generation:v1`, `resilience:power-losses:v1`) is absent from Redis, the scorer throws `ResilienceConfigurationError` at dispatch rather than silently falling back to IMPUTE. The error is caught per-dimension in `scoreAllDimensions` and surfaces as `imputationClass='source-failure'` with `coverage=0`, visible in the widget and the API response. `/api/health` also reports CRIT on the three `seed-meta:resilience:\{low-carbon-generation,fossil-electricity-share,power-losses\}` entries when they are absent or stale. The flag is safe to keep on only while `seed-bundle-resilience-energy-v2` remains provisioned on Railway and health stays green on all three. Rollback remains a single env-var change to `RESILIENCE_ENERGY_V2_ENABLED=false`; reactivation requires all three seed-meta entries to be green and a score-cache prefix bump if cached legacy scores may exist.
### Social & Governance Domain (weight 0.19)
#### Governance
| Indicator | Description | Direction | Goalposts (worst-best) | Weight | Source | Cadence |
|---|---|---|---|---|---|---|
| wgiVoiceAccountability | World Bank WGI: Voice and Accountability | Higher is better | -2.5 - 2.5 | 1/6 | World Bank WGI | Annual |
| wgiPoliticalStability | World Bank WGI: Political Stability | Higher is better | -2.5 - 2.5 | 1/6 | World Bank WGI | Annual |
| wgiGovernmentEffectiveness | World Bank WGI: Government Effectiveness | Higher is better | -2.5 - 2.5 | 1/6 | World Bank WGI | Annual |
| wgiRegulatoryQuality | World Bank WGI: Regulatory Quality | Higher is better | -2.5 - 2.5 | 1/6 | World Bank WGI | Annual |
| wgiRuleOfLaw | World Bank WGI: Rule of Law | Higher is better | -2.5 - 2.5 | 1/6 | World Bank WGI | Annual |
| wgiControlOfCorruption | World Bank WGI: Control of Corruption | Higher is better | -2.5 - 2.5 | 1/6 | World Bank WGI | Annual |
All six WGI indicators are equally weighted.
#### Social Cohesion
| Indicator | Description | Direction | Goalposts (worst-best) | Weight | Source | Cadence |
|---|---|---|---|---|---|---|
| gpiScore | Global Peace Index score | Lower is better | 3.6 - 1.0 | 0.55 | IEP | Annual |
| displacementTotal | UNHCR total displaced persons (log10 scale) | Lower is better | 7 - 0 | 0.25 | UNHCR | Annual |
| unrestEvents | Severity-weighted unrest events + sqrt(fatalities), population-normalized per million with a 0.5M floor | Lower is better | 10 - 0 | 0.20 | Unrest monitoring | Realtime |
**v15 (2026-04-26) — gated GPI-only impute for sparse-data tiny
states.** When both displacement and unrest data were absent for a
country (typical for tiny island states absent from UNHCR's
displacement registry), the dimension previously collapsed to GPI
alone. Tiny peaceful states (TV, PW, NR with GPI ~1.3) rode this to a
near-perfect ~93 dim score. v15 introduces a gated impute: when the
country is absent from the displacement registry, displacement is
imputed at 70/coverage 0.6 (`stable-absence`), while zero unrest events
fall back to `curated_list_absent` at 50/coverage 0.3 (`unmonitored`)
because the unrest feed is non-comprehensive. This pulls the blend down
for tiny peaceful states without treating English-biased source absence
as a strong stable-absence signal. Countries WITH observed displacement
and zero unrest events keep the historical "stable-absence ≈ 85" anchor
(matching `IMPUTE.unhcrDisplacement`), preserving Iceland/Norway scoring.
Per-row imputation flags do not bubble up: dim-level `imputationClass`
remains null because GPI is still observed. Seed-outage paths (raw payload
absent) continue to drop the weight rather than imputing — the
outage-vs-absence distinction is preserved.
#### Conflict & Displacement
This dimension measures **armed-conflict event intensity and refugee
displacement**. It does **not** measure border-control infrastructure,
customs throughput, or cross-border-crime enforcement. The internal
identifier is `borderSecurity` for proto / cache-key stability; the
relabeling is tracked in #3737.
| Indicator | Description | Direction | Goalposts (worst-best) | Weight | Source | Cadence |
|---|---|---|---|---|---|---|
| ucdpConflict | UCDP armed conflict: eventCount*2 + typeWeight + sqrt(deaths), population-normalized per million with a 0.5M floor | Lower is better | 15 - 0 | 0.65 | UCDP | Annual GED releases |
| displacementHosted | UNHCR hosted displaced persons (log10 scale) | Lower is better | 7 - 0 | 0.35 | UNHCR | Annual |
#### Information & Cognitive
| Indicator | Description | Direction | Goalposts (worst-best) | Weight | Source | Cadence |
|---|---|---|---|---|---|---|
| rsfPressFreedom | RSF press freedom score | Lower is better | 100 - 0 | 0.55 | RSF | Annual |
| socialVelocity | Reddit social velocity (log10(velocity+1)) | Lower is better | 3 - 0 | 0.15 | Reddit intelligence | Hourly relay (freshness budget: 180 min) |
| newsThreatScore | AI news threat severity (critical 4x, high 2x, medium 1x, low 0.5x) | Lower is better | 20 - 0 | 0.30 | News threat analysis | Daily |
**Language-coverage weighting.** `socialVelocity` and `newsThreatScore` are
English-source-sensitive signals, so their score weights are multiplied by the
country's language-coverage tier. The raw signal values are not divided or
amplified. Lower-coverage countries therefore lean more heavily on the static
RSF press-freedom signal while preserving nominal coverage math for the
dimension. Unlisted countries default to the `minimal` tier.
| Tier | Multiplier | Countries |
|---|---:|---|
| `primary` | 1.0 | AU, CA, GB, IE, NZ, SG, US |
| `secondary` | 0.7 | AE, BB, BD, BH, BW, CM, CY, ET, FJ, GH, GM, GY, HK, IL, IN, JM, JO, KE, KH, KW, LK, LR, LS, MT, MW, MY, MM, MZ, NA, NG, NP, PG, PH, PK, QA, RW, SL, SZ, TT, TZ, UG, WS, ZA, ZM, ZW |
| `limited` | 0.4 | AM, AR, AT, AZ, BE, BG, BR, BY, CH, CL, CN, CO, CZ, DE, DK, DZ, EC, EE, EG, ES, FI, FR, GE, GR, HR, HU, ID, IQ, IR, IT, JP, KR, KZ, LB, LT, LV, MA, MX, NL, NO, PE, PL, PT, RO, RS, RU, SA, SE, SI, SK, TH, TN, TR, TW, UA, UZ, VE, VN |
| `minimal` | 0.2 | Default for any country not listed above |
#### Education
Added 2026-08-10, **activated 2026-08-11** (#6460) at `tier='core'`. Measured coverage is 181 of the 196 rankable countries, re-measured immediately before promotion — one country above the `CORE_MIN_COVERAGE = 180` floor. The 15 absent (BB, ER, GA, GQ, KG, KN, KP, LI, LY, MC, SS, ST, SY, TW, VC) impute to `unmonitored` at score 50 / coverage 0.3, which is "not measured", not "the phenomenon is absent" — treating it as a stable absence would hand DPRK and Syria a score near 85.
Activation added a fifth core-bearing dimension to the social-governance domain, moving every other dimension in that domain from a 1/4 to a 1/5 gate share; the six WGI governance indicators are the largest single loser. Measured against production seeds across all 196 countries, flag-off vs flag-on: Spearman 1.00, maximum country drift 3.45 points, worst cohort median shift −1.08.
`RESILIENCE_EDUCATION_ENABLED=false` remains the rollback kill switch; with it set the scorer returns the empty-data shape and the dimension contributes nothing to any published score.
**Known construct property — cohort lag.** The series measures an attainment *stock* over the 25+ population, so it penalises late-developing school systems and rewards states with near-universal upper-secondary credentials regardless of institutional quality. Southern Europe sits materially below post-Soviet states on this indicator alone (Portugal 50.0, Spain 55.8, Italy 55.1 against Belarus 98.2, Turkmenistan 98.1, Uzbekistan 96.0). This is defensible — it is what the causal literature the construct rests on actually measures — but it is bounded rather than assumed: three whole-index matched pairs (`pt-vs-uz`, `es-vs-by`, `ch-vs-tm` in `tests/helpers/resilience-matched-pairs.mts`) require the broader institutional profile to survive the education deficit at the overall-score level, and the concave bend above 85 caps credential inflation at the top of the range. Measured effect on the southern-Europe cohort at activation: PT −0.55, ES −0.29, IT −0.29, MT −0.43, GR +0.12 overall points.
| Indicator | Description | Direction | Goalposts (worst-best) | Weight | Source | Cadence |
|---|---|---|---|---|---|---|
| femaleUpperSecondaryAttainment | Female upper-secondary educational attainment, population 25+ (World Bank SE.SEC.CUAT.UP.FE.ZS). Piecewise transform: linear to 85, shallower slope above. | Higher is better | 0 - 100 | 1.00 | World Bank | Annual |
**Mechanism.** Female upper-secondary attainment governs how fast a population can receive, understand, and act on emergency instruction, and how fast it can re-skill after a shock. The construct contract excludes indicators whose only answer to the mechanism test is "this country is rich", so the income-independence of this signal is the load-bearing claim. Two forms of evidence support it. Externally, the Wittgenstein Centre / IIASA strand (Striessnig, Lutz & Patt 2013, *Ecology & Society* 18(1):16; Lutz, Muttarak & Striessnig 2014, *Science* 346(6213):1061) reports that rising GDP per capita did not track falling climate-disaster deaths over four decades while rising female secondary attainment did. Internally and more directly, the measured top of this series is post-Soviet rather than Western — Belarus 98.2, Turkmenistan 98.1, Uzbekistan 96.0, with the United States tenth at 92.1. An affluence proxy would put Norway and Switzerland on top.
**Why the female variant.** The female, male, and total series cover an identical 181 of the 196 rankable countries, so choosing the variant the causal literature credits costs nothing in coverage.
**Transform.** The measured distribution does not saturate: median 50.0, near-uniform deciles, only 1.7% above 95% (adult literacy, by contrast, puts 42% there). A log or logistic squash would erase discrimination in the 20–80 band holding two-thirds of the universe. The dimension therefore uses a two-segment map with a slope drop at 85 — decreasing slope is concave, satisfying the contract's threshold requirement, while the first segment stays linear where countries actually sit. The bend affects 22 of 181 countries.
Goalposts are fixed 0 and 100, never observed extremes. An observed-max anchor would let Turkmenistan define a perfect score; a percentile lower anchor would tie 18 Sahel and Horn countries at the floor, precisely the band this series was chosen to resolve.
**Known limitations.** This indicator measures attainment, not education *quality* or the freedom to act on what one knows — a series led by Turkmenistan and Belarus partly reflects credential issuance under authoritarian state education systems. Those failure modes are scored elsewhere: Turkmenistan is penalized by Governance, Information & Cognitive, and Conflict & Displacement, and the min-pillar penalty limits how far one strong pillar can compensate. No published effect size is cited because none was available in the secondary literature; the primary papers should be consulted before quoting a coefficient. A separate literature finds income outpredicts education for *individual, within-country* mortality — a different unit of analysis, not a rebuttal of the cross-national finding.
**Excluded: the female-minus-male gap.** The gap carries real cross-country signal, but its positive tail is Gulf migrant labor (Qatar +30.2, Bahrain +18.7) inflating the male 25+ denominator rather than female advancement. A raw gap term would rank Qatar the most female-favorable country on earth — the same construct error the OFAC-domicile component was retired for. Deferred until a migrant-stock adjustment exists.
**Coverage and staleness.** 181 of 196 rankable countries. The 15 absent (BB, ER, GA, GQ, KG, KN, KP, LI, LY, MC, SS, ST, SY, TW, VC) are tagged `unmonitored`, not `stable-absence` — the World Bank does not survey everywhere, so absence means "not measured", not "the phenomenon is not happening". Taiwan is absent from all World Bank data, so 195/196 is the practical ceiling for any World Bank series. A stale-but-present observation is kept at reduced certainty rather than dropped: 1.0 within 5 years, 0.8 at 5–10, 0.6 beyond. There is deliberately no drop rule at 5 years — that bucket holds 39 countries including Japan, China, New Zealand, and Kazakhstan.
### Health & Food Domain (weight 0.13)
#### Health & Public Service
| Indicator | Description | Direction | Goalposts (worst-best) | Weight | Source | Cadence |
|---|---|---|---|---|---|---|
| uhcIndex | WHO Universal Health Coverage service coverage index | Higher is better | 40 - 90 | 0.35 | WHO | Annual |
| measlesCoverage | Measles immunization coverage among 1-year-olds (%) | Higher is better | 50 - 99 | 0.25 | WHO | Annual |
| hospitalBeds | Hospital beds per 1,000 people | Higher is better | 0 - 8 | 0.10 | WHO | Annual |
| physiciansPer1k | Physicians per 1,000 people | Higher is better | 0 - 5 | 0.15 | WHO | Annual |
| healthExpPerCapitaUsd | Current health expenditure per capita, USD | Higher is better | 20 - 3000 | 0.15 | WHO | Annual |
#### Food & Water
| Indicator | Description | Direction | Goalposts (worst-best) | Weight | Source | Cadence |
|---|---|---|---|---|---|---|
| ipcPeopleInCrisis | IPC/FAO people in food crisis (log10 scale) | Lower is better | 7 - 0 | 0.45 | FAO/IPC | Annual |
| ipcPhase | IPC food crisis phase (1-5) | Lower is better | 5 - 1 | 0.15 | FAO/IPC | Annual |
| aquastatScore | Legacy field name for the selected World Bank water-stress observation; indicator-tag routing remains for backward-compatible seed shapes | Indicator semantics | Indicator-dependent | 0.40 | World Bank WDI | Annual |
### Recovery Domain (weight 0.25)
This domain forms the recovery-capacity pillar. It measures a country's ability to bounce back from an acute shock along fiscal, monetary, trade, institutional, and energy dimensions.
**Per-dimension weights in the recovery domain (PR 2 §3.4).** Four
core recovery dimensions (`fiscalSpace`, `externalDebtCoverage`,
`importConcentration`, `stateContinuity`) carry the default weight
`1.0`. The two PR 2 §3.4 replacements for the retired `reserveAdequacy`
carry weight `0.5` each:
| Dimension | Weight | Share at full coverage |
|---|---:|---:|
| fiscalSpace | 1.0 | 20% |
| externalDebtCoverage | 1.0 | 20% |
| importConcentration | 1.0 | 20% |
| stateContinuity | 1.0 | 20% |
| liquidReserveAdequacy | 0.5 | 10% |
| sovereignFiscalBuffer | 0.5 | 10% |
The `0.5` weight on the two new dims caps their combined contribution
to the recovery score at ~20%, matching the plan's direction that the
sovereign-wealth signal complement — rather than dominate — the
classical liquid-reserves and fiscal-space signals. The weights are
applied via `RESILIENCE_DIMENSION_WEIGHTS` in
`server/worldmonitor/resilience/v1/_dimension-scorers.ts`;
`coverageWeightedMean` in `_shared.ts` multiplies each dim's coverage
by its weight before computing the domain average, so a dim with
`coverage=0` (retirement) still contributes zero regardless of weight.
#### Fiscal Space
The first three indicators measure the **state** of public finances; the fourth — `debtSustainabilityGap` — measures the **trajectory**. The gap is the standard IMF DSA construct (used by Article IV missions, ECB MIP scoreboard, and S&P sovereign methodology):
```
g = (1 + realGdpGrowth/100) × (1 + cpiInflation/100) − 1
r = max(0, (primaryBalance − fiscalBalance) / debtToGdp)
pb* = ((r − g) / (1 + g)) × debtToGdp
gap = primaryBalance − pb* (positive ⇒ debt path declining)
```
The gap is **computed at seed time** and stored as `debtSustainabilityGapPct` in the canonical fiscal-space blob, so the scorer just normalizes. Inputs are year-aligned via `latestCommonYear` across the 5 formula series (debt, balance, primary balance, real growth, inflation); year-mismatched countries get `gap=null` and the scorer's `weightedBlend` redistributes weight across the remaining 3 indicators. The inflation cap (CPI > 10%) drops `gap` to null for inflation-tax-regime countries (Argentina, Turkey, Lebanon, Egypt, Nigeria, Ethiopia, etc.) — above ~10% inflation the formula's nominal-growth term mechanically erodes debt while masking underlying fiscal pathology, and the IMF DSA framework itself only treats sustainability as meaningful below this threshold. Realistic joint coverage is ~140 countries (down from 190 nominal) because of the year-alignment + cap interaction.
| Indicator | Description | Direction | Goalposts (worst-best) | Weight | Source | Cadence |
|---|---|---|---|---|---|---|
| recoveryGovRevenue | Government revenue as % of GDP (IMF GGR_G01_GDP_PT) | Higher is better | 5 - 45 | 0.25 | IMF | Annual |
| recoveryFiscalBalance | General government net lending/borrowing as % of GDP (IMF GGXCNL_G01_GDP_PT) | Higher is better | -15 - 5 | 0.20 | IMF | Annual |
| recoveryDebtToGdp | General government gross debt as % of GDP (IMF GGXWDG_NGDP_PT) | Lower is better | 150 - 0 | 0.20 | IMF | Annual |
| debtSustainabilityGap | Primary-balance gap to debt-stabilizing level (IMF DSA construct); see formula above. Dropped to null when CPI > 10% to avoid inflation-tax masking. | Higher is better | -5 - 3 | 0.35 | IMF (5 series: GGXONLB_NGDP, GGXCNL_NGDP, GGXWDG_NGDP, NGDP_RPCH, PCPIPCH) | Annual |
#### Reserve Adequacy
PR 2 §3.4 retired `reserveAdequacy` from the core overall score. The dimension remains registered for schema continuity but pins at `coverage=0`, `score=50`, `imputationClass=null` for every country (same shape as the PR 3 `fuelStockDays` retirement — the `null` tag avoids a false "Source down" label in the widget for a deliberate construct retirement). The construct split into two dimensions that separate the liquid-reserves signal from the sovereign-wealth signal: `liquidReserveAdequacy` (below) and `sovereignFiscalBuffer` (below). See the v2.3 changelog entry for the rationale.
| Indicator | Description | Direction | Goalposts (worst-best) | Weight | Source | Cadence |
|---|---|---|---|---|---|---|
| recoveryReserveMonths | Total reserves in months of imports (World Bank FI.RES.TOTL.MO) — **experimental tier, not part of core score** | Higher is better | 1 - 18 | 1.00 | World Bank | Annual |
#### Liquid Reserve Adequacy
PR 2 §3.4 replacement for the liquid-reserves half of the retired `reserveAdequacy`. Same upstream source (World Bank `FI.RES.TOTL.MO`, total reserves in months of imports) but re-anchored `1..12` months instead of `1..18`. Twelve months is the ballpark IMF "full reserve adequacy" benchmark for a diversified emerging-market importer; the tighter ceiling prevents wealthy commodity-exporters from claiming outsized credit for on-paper reserve stocks that are not the relevant shock-absorption buffer. The sovereign-wealth half of the split lives in `sovereignFiscalBuffer` below.
| Indicator | Description | Direction | Goalposts (worst-best) | Weight | Source | Cadence |
|---|---|---|---|---|---|---|
| recoveryLiquidReserveMonths | Total reserves in months of imports (World Bank FI.RES.TOTL.MO), re-anchored 1..12 | Higher is better | 1 - 12 | 1.00 | World Bank | Annual |
#### Sovereign Fiscal Buffer
PR 2 §3.4 new dimension. Measures the per-country deployable fiscal buffer from sovereign wealth fund assets, discounted by a three-component haircut (access × liquidity × transparency) per published fund governance. The composite is:
```
effectiveMonths = Σ [ (aum / annualImports × 12) × access × liquidity × transparency ]
score = 100 × (1 − exp(−effectiveMonths / 12))
```
The exponential saturation prevents Norway-type outliers (effective months in the 100s) from dominating the recovery pillar out of proportion to their marginal resilience benefit.
| Indicator | Description | Direction | Goalposts (worst-best) | Weight | Source | Cadence |
|---|---|---|---|---|---|---|
| recoverySovereignWealthEffectiveMonths | Haircut-weighted sovereign-wealth assets in months of imports, saturating | Higher is better | 0 - 60 | 1.00 | Wikipedia SWF list + per-fund articles (CC-BY-SA), haircut by swf-classification-manifest.yaml | Quarterly |
**v15 (2026-04-26) — construct reframing for non-SWF countries.**
The original PR 2 §3.4 construct treated countries not in the SWF
manifest (`scripts/shared/swf-classification-manifest.yaml`) as
**substantive absence**: `score=0, coverage=1.0` — a deliberate
penalty meant to lower their recovery-pillar score relative to
SWF-holding peers. Empirically this over-fired for advanced economies
(DE, JP, FR, IT, UK, US, NL, AT, BE, ES, PT) that hold reserves
through Treasury / central-bank channels rather than dedicated
sovereign-wealth funds, dragging their recovery-pillar coverage and
ranking artificially low.
v15 reframes Path 3 from **substantive absence** (`score=0,
coverage=1.0`) to **dim-not-applicable** (`score=0, coverage=0`).
The score field stays numeric (zero) per the
`ResilienceDimensionScore.score: number` contract; the `coverage:0`
is what causes the dim to contribute nothing to the
coverage-weighted recovery-domain mean. The recovery domain
re-normalizes around the OTHER recovery dims for non-SWF countries,
which continue to score them via their own data sources
(`liquidReserveAdequacy`, `externalDebtCoverage`, `importConcentration`,
`fiscalSpace`, etc.). No double-counting of reserves.
User-facing widget signals (`computeLowConfidence`,
`computeOverallCoverage`) also exclude this dim when its coverage is
0 — same pattern as `RESILIENCE_RETIRED_DIMENSIONS`, but gated to
the country level rather than the construct level via
`RESILIENCE_NOT_APPLICABLE_WHEN_ZERO_COVERAGE`. Countries WITH SWFs
in the manifest still score normally with positive coverage; the
dim continues to differentiate Norway / Kuwait / Singapore / UAE
from each other based on `effectiveMonths`.
#### External Debt Coverage
| Indicator | Description | Direction | Goalposts (worst-best) | Weight | Source | Cadence |
|---|---|---|---|---|---|---|
| recoveryDebtToReserves | Short-term external debt to reserves ratio (World Bank DT.DOD.DSTC.CD / FI.RES.TOTL.CD); anchored on Greenspan-Guidotti reserve-adequacy rule | Lower is better | 2 - 0 | 1.00 | World Bank | Annual |
#### Import Concentration
| Indicator | Description | Direction | Goalposts (worst-best) | Weight | Source | Cadence |
|---|---|---|---|---|---|---|
| recoveryImportHhi | Herfindahl-Hirschman Index of import partner concentration (UN Comtrade HS2 bilateral) | Lower is better | 5000 - 0 | 1.00 | UN Comtrade | Annual |
#### State Continuity
| Indicator | Description | Direction | Goalposts (worst-best) | Weight | Source | Cadence |
|---|---|---|---|---|---|---|
| recoveryWgiContinuity | Mean WGI score as institutional durability proxy | Higher is better | -2.5 - 2.5 | 0.50 | World Bank | Annual |
| recoveryConflictPressure | UCDP conflict metric inverted to state continuity | Lower is better | 30 - 0 | 0.30 | UCDP | Annual GED releases |
| recoveryDisplacementVelocity | UNHCR displacement as state continuity signal | Lower is better | 7 - 0 | 0.20 | UNHCR | Annual |
State continuity is a derived dimension: it reads from existing WGI, UCDP, and displacement keys rather than a dedicated seeder.
#### Fuel Stock Days
PR 3 §3.5 point 1 permanently retired `fuelStockDays` from the core overall score. The dimension remains registered for schema continuity but pins at `coverage=0`, `score=50`, `imputationClass=null` for every country. Domain averages skip it via the coverage-weighted mean (coverage=0 contributes zero weight), and the user-facing confidence / coverage-percent averages exclude it via the `RESILIENCE_RETIRED_DIMENSIONS` registry filter in `computeLowConfidence`, `computeOverallCoverage`, and the widget's `formatResilienceConfidence`. `imputationClass` is deliberately `null` rather than `source-failure` — a retirement is structural, not a runtime outage, and the widget maps `source-failure` to a "Source down: upstream seeder failed" label with a `!` icon which would manufacture a false outage signal for every country on a deliberate construct retirement.
Why retired: fuel-stock disclosure is an IEA/OECD-member obligation covering ~45 countries. Every non-member was imputed via `unmonitored` (score 50, coverage 0.30). Combined with its 1/6 share of the recovery domain, this was the single largest "construct-absent-for-most-of-the-world" carrier in the scorer — the primary reason UAE landed at rank 69 with `energy=53, reserveAdequacy=25, fuelStockDays=50/unmonitored` in the pre-repair audit.
| Indicator | Description | Direction | Goalposts (worst-best) | Weight | Source | Cadence |
|---|---|---|---|---|---|---|
| recoveryFuelStockDays | Days of fuel stock cover (IEA Oil Stocks / EIA Weekly Petroleum Status) — **experimental tier, not part of core score** | Higher is better | 0 - 120 | 1.00 | IEA/EIA | Monthly |
The seeder still runs on its weekly schedule so the data surfaces on IEA/OECD-member country drill-downs. It stays retired from the core score unless a globally-comparable concept (strategic-reserve disclosure mandated across >180 countries) emerges.
## Normalization
**The problem this solves:** the raw indicators arrive in units that cannot be
added together — percentages, dollars, days of supply, people per bed. Before
anything can be blended, each one has to be put on the same 0-100 ruler.
Each indicator gets two fixed reference points: a value that scores 0 (the
"worst" goalpost) and a value that scores 100 (the "best"). Anything at or
beyond a goalpost is clamped to that end. The goalposts are hand-picked from
empirical data ranges, not derived from percentiles, so a country's score is
measured against a fixed standard rather than against whoever else happens to
be in the dataset this year.
All indicators are normalized to a 0-100 scale using **goalpost scaling** (also called min-max normalization with domain-specific anchors).
For "higher is better" indicators:
```
score = clamp((value - worst) / (best - worst) * 100, 0, 100)
```
For "lower is better" indicators:
```
score = clamp((worst - value) / (worst - best) * 100, 0, 100)
```
Goalposts are hand-picked based on empirical data ranges (not percentile-derived). A score of 100 means the country meets or exceeds the "best" goalpost; 0 means it meets or exceeds the "worst" goalpost.
**Exceptions:** A few live indicators are explicitly non-linear and are tagged as such in the indicator registry: `inflationStability` uses a 1-3% target band with deflation and high-inflation zero-score anchors, `bisLbsXborderPctGdp` uses a U-shaped band, `fatfListingStatus` is categorical, and `recoverySovereignWealthEffectiveMonths` uses a saturating transform. Their goalposts are documentation anchors, not generic linear normalizer inputs.
## Scoring Formula
Four aggregations stack on top of each other: indicators become dimensions,
dimensions become domains, domains become pillars, and the pillars become one
number. Each step below states the rule and then why it is that rule.
### Dimension Score
Each dimension score is the **weighted blend** of its sub-metric scores:
```
dimensionScore = sum(metricScore_i * metricWeight_i) / sum(metricWeight_i)
```
Only metrics with available data participate in the blend. Missing metrics are excluded from both the numerator and denominator, so the score reflects what is known rather than penalizing for absent data.
### Domain Score
Each domain score is the **coverage-weighted mean** of its dimensions:
```
domainScore = sum(dimensionScore_i * dimensionCoverage_i) / sum(dimensionCoverage_i)
```
Coverage weighting ensures that dimensions with sparse data (low coverage) contribute proportionally less, preventing a low-coverage dimension from dragging the domain average down.
### Overall Score
The currently active overall score is the **pillar-combined penalized score**:
```
weightedPillarMean = sum(pillarScore_i * pillarWeight_i)
penalty = 1 - 0.5 * (1 - minPillarScore / 100)
overallScore = weightedPillarMean * penalty
```
Domain scores are first regrouped into the three pillars (`structural-readiness`, `live-shock-exposure`, and `recovery-capacity`). Inside each pillar, member domains are averaged by `domainWeight_i * averageDimensionCoverage_i`, preserving the coverage signal while honoring the published domain design weights. The three pillar scores are then combined with pillar weights 0.40 / 0.35 / 0.25. The penalty term is anchored to the weakest pillar, so an otherwise strong country cannot fully compensate for a severe weakness in one pillar. The legacy six-domain weighted aggregate remains the rollback formula when `RESILIENCE_PILLAR_COMBINE_ENABLED=false`; an earlier multiplicative form (`baseline * (1 - stressFactor)`) over-penalized every country and was reverted. See the [Changelog](#corpus-changelog) for the full version history.
### Resilience Level Classification
| Score Range | Level |
|---|---|
| 60-100 | High |
| 30-59 | Medium |
| 0-29 | Low |
The legacy six-domain rollback formula uses the older 70/40 cutoffs. The active pillar-combined formula uses the 60/30 cutoffs above to keep qualitative labels aligned after the score scale compression introduced by the min-pillar penalty.
## Missing Data Handling
**The distinction that matters:** "nothing is happening here" and "we have no
idea what is happening here" look identical in a spreadsheet, and treating them
the same is how country indices produce confident nonsense.
So the scorer never silently fills a gap. When an observation is absent it asks
*why*, and tags the answer: the source publishes globally and this country
simply is not on the list (a genuine good sign — no famine reported means no
famine); the source is a partial list and the absence proves nothing; the
upstream feed was down; or the thing being measured does not apply to this
country at all. Each answer carries a different score and a different certainty
weight, and all of them are visible in the response.
A country whose score leans too heavily on inference is flagged
`lowConfidence` and kept out of the public ranking rather than being presented
as if it were measured.
### Coverage Tracking
Each dimension carries a `coverage` value (0.0-1.0) representing the weighted certainty of its data. Real observed data contributes certainty 1.0. Imputed data contributes partial certainty. Absent data contributes 0.
```
coverage = sum(metricWeight_i * certainty_i) / sum(metricWeight_i)
```
### Imputation Taxonomy
When data is absent, the system tags it with one of four classes so downstream consumers can distinguish "nothing is happening" from "we do not know" from "the upstream is down" from "the dimension does not apply to this country." The taxonomy is defined in `server/worldmonitor/resilience/v1/_dimension-scorers.ts` as an exported `ImputationClass` type.
| Class | Meaning | Typical score | Certainty | Example sources |
|---|---|---:|---:|---|
| `stable-absence` | The source publishes globally. Country is not listed, which means the tracked phenomenon is not happening. Strong positive signal. | 85 to 88 | 0.6 to 0.7 | IPC food crisis, UNHCR displacement, UCDP conflict events |
| `unmonitored` | The source is a curated list that may not cover every country. Absence is ambiguous; penalized conservatively. | 50 to 60 | 0.3 to 0.4 | BIS / WTO curated feeds and other partial-coverage enrichments |
| `source-failure` | The upstream API was unavailable at seed time. Detected from `seed-meta` `failedDatasets`. Should be rare and transient. | inherits from the source being substituted | 0.3 to 0.5 | any source listed in `failedDatasets` during a seed run |
| `not-applicable` | The dimension is structurally N/A for this country (the construct does not apply). The scorer emits `score=0, coverage=0, observedWeight=0, imputedWeight=0` so the dim contributes zero weight to the domain coverage-weighted mean and is filtered from user-facing low-confidence and overall-coverage signals on both server and client. The dim is excluded ONLY when it appears in `RESILIENCE_NOT_APPLICABLE_WHEN_ZERO_COVERAGE` AND the triple-zero Path-3 fingerprint matches; a real data outage on a country that DOES carry the construct (`coverage=0` with `observedWeight>0`) still drags confidence so an operator notices. | 0 (by definition) | 0 (by definition) | `sovereignFiscalBuffer` for non-SWF countries (plan 2026-04-26-001 §U3 + review fixup) |
The generic imputation entries are declared in the `IMPUTATION` table and shared across dimensions. Per-metric overrides live in the `IMPUTE` table with their own score and certainty values, and inherit or override the class tag. Every entry is regression-tested in `tests/resilience-dimension-scorers.test.mts` to prevent silent drift.
| Concrete imputation entry | Class | Score | Certainty | Notes |
|---|---|---:|---:|---|
| `crisis_monitoring_absent` (IPC, UCDP, UNHCR general) | `stable-absence` | 85 | 0.7 | Used when the global crisis feed has no entry for the country |
| `curated_list_absent` (BIS, WTO general) | `unmonitored` | 50 | 0.3 | Used when a curated list does not cover the country |
| `ipcFood` (food-specific crisis monitoring) | `stable-absence` | 88 | 0.7 | Slightly higher score because no IPC data strongly implies food security |
| `wtoData` (trade-specific curated list) | `unmonitored` | 60 | 0.4 | Slightly higher than the generic curated list default |
| `unhcrDisplacement` (displacement-specific crisis monitoring) | `stable-absence` | 85 | 0.6 | Lower certainty than IPC because displacement is noisier |
| `bisEer` / `bisCredit` legacy fallbacks | `unmonitored` | 50 | 0.3 | Shared reference to `curated_list_absent`; retained for rollback and sparse-coverage compatibility paths |
| Runtime `failedDatasets` re-tag | `source-failure` | preserves substituted score | preserves substituted certainty | Applied at score aggregation time when `seed-meta:resilience:static.failedDatasets` lists the adapter behind an otherwise-imputed dimension |
The `source-failure` class is applied by the runtime scoring path: the aggregation pass reads `seed-meta:resilience:static.failedDatasets` through `_source-failure.ts` and re-tags affected imputed dimensions as `source-failure` when the underlying seed adapter failed. This keeps a country-level absence signal distinct from an upstream-source outage. The `not-applicable` class is emitted by `scoreSovereignFiscalBuffer` Path 3 (plan 2026-04-26-001 §U3 + review fixup): when the SWF manifest payload is present but the country is absent from it, the scorer returns `score=0, coverage=0, observedWeight=0, imputedWeight=0, imputationClass='not-applicable'`. The `RESILIENCE_NOT_APPLICABLE_WHEN_ZERO_COVERAGE` set in `_dimension-scorers.ts` enumerates which dimensions can emit this class, and `isExcludedFromConfidenceMean` is the single-source helper used by both server-side coverage means and the client widget — keeping cross-surface filter parity (server `overallCoverage` and widget "Coverage X% ✓" string match for non-SWF advanced economies). New dimensions that need structural N/A handling can opt in by adding their id to `RESILIENCE_NOT_APPLICABLE_WHEN_ZERO_COVERAGE` and following the 6-site lockstep recipe documented in the project memory.
### Low Confidence Flag
A score is flagged as `lowConfidence` when either:
- Average dimension coverage falls below **0.55**, or
- Imputation share (imputed weight / total weight) exceeds **0.40**.
### Grey-Out and Ranking Eligibility
The historical **0.40** sparse-coverage grey-out constant is retained in code
for legacy context but is currently unconsumed by the ranking/UI eligibility
path. Public ranking inclusion is governed by the stricter server-side
`headlineEligible` gate:
`overallCoverage >= 0.65 AND (populationMillions >= 0.2 OR overallCoverage >= 0.85) AND !lowConfidence`.
Scored but ineligible countries remain in `greyedOut[]` for analyst inspection
and are excluded from the headline ranking.
### Imputation Share
The API response includes `imputationShare` (0.0-1.0), representing the fraction of total indicator weight that came from imputed (synthetic) data rather than observed data. This allows consumers to assess data provenance.
### Supported Readings on Unranked Country Pages
A country that publishes no headline score still publishes a dimension evidence
inventory. The page uses three evidence terms that do not mean the same thing:
- **Observed.** The snapshot holds a usable partial series for that dimension
and no more specific absence or failure class applies. Stable absence is
labeled separately, even when its recorded coverage is positive.
- **Supported reading.** On a microstate or territory page, the dimension has no
imputation class, clears **0.50** coverage, and has a finite score. The page
publishes the dimension score and its coverage.
- **Available evidence.** On another unranked country page, the summary names
non-gap dimensions that clear **0.50** coverage. The summary publishes their
labels and coverage, but it does not publish dimension scores.
When a shown inventory row is labeled observed but falls below **0.50** coverage,
the page names that row and states the floor inline. This explains why the row
does not count as a supported reading.
The inventory is ordered weakest evidence first — not-applicable slots, then
dimensions with no usable series, then partial coverage ascending — and capped
at 12 rows. It is grouped rather than strictly sorted by coverage, so a
dimension with no usable series can precede one with a thin but real reading.
The cap splits the active dimensions into three buckets, and the scope note
accounts for all three: the dimensions shown, the dimensions already at full
coverage that never entered the weakest-first pool, and the dimensions the cap
omitted.
The counts are generated from a single partition and asserted at build time, so
a page whose inventory arithmetic does not close fails the build rather than
publishing (#7609).
## Data Sources (Country Resilience Index methodology)
| Source | Indicators | Cadence | Scope |
|---|---|---|---|
| IMF (WEO/IFS) | Government revenue, current account, inflation | Annual | Global |
| World Bank (WDI) | Electricity access, paved roads, reserves, tariffs, power losses, fossil electricity share | Annual | Global |
| OWID Energy | Low-carbon electricity share and structural energy-mix context | Annual | Global |
| World Bank (WGI) | 6 governance indicators | Annual | Global |
| BIS | Consolidated Banking Statistics (CBS, `WS_CBS_PUB`) for `financialSystemExposure` via retained key `economic:bis-lbs:v1`; household debt-service ratio (`economic:bis:dsr:v1`) for `macroFiscal`; REER only experimental enrichment / rollback support | Quarterly / monthly | CBS broad coverage; DSR and REER cover curated BIS-reporting economies |
| WTO | Trade restrictions, trade barriers | Weekly | ~50 reporters |
| WHO | UHC index, measles coverage, hospital beds | Annual | Global |
| FAO (IPC) | People in food crisis, crisis phase | Annual | Affected countries |
| World Bank (WDI water stress) | Current observation behind the legacy `aquastatScore` field | Annual | Global |
| IEA / national energy balance inputs | Net energy import dependency used inside `importedFossilDependence`; legacy standalone energy-import-dependency path is rollback only | Annual | Global |
| IEP | Global Peace Index | Annual | Global |
| RSF | Press freedom score | Annual | Global |
| UNHCR | Displaced persons, hosted refugees | Annual | Affected countries |
| UCDP | Armed conflict events, fatalities | Annual GED releases; seeder liveness is monitored separately from source-data cadence | Global |
| Cyber threat feeds | Severity-weighted cyber threats | Daily | Global |
| Outage monitoring | Internet outages | Realtime | Global |
| GPSJam | GPS jamming incidents | Daily | Global |
| Supply-chain monitor | Shipping stress, transit disruption | Daily | Global |
| Unrest monitoring | Severity-weighted civil unrest events | Realtime | Global |
| Reddit intelligence | Social velocity scores | Hourly relay (freshness budget: 180 min) | Global |
| News threat analysis | AI-scored news threat severity | Daily | Global |
| Energy mix data | Gas, coal, renewable shares | Annual | Global |
| GIE AGSI+ | Gas storage fill levels | Daily | European countries |
| Energy prices | Commodity price changes | Daily | Global |
| National debt data | Debt-to-GDP growth rate | Annual | Global |
## Supplementary Fields
The API response includes additional context fields that are informational and not part of the primary ranking:
- **baselineScore**: Coverage-weighted mean of baseline and mixed dimensions. Reflects structural capacity (governance, health, infrastructure, fiscal strength). Informational only, not used in `overallScore`.
- **stressScore**: Coverage-weighted mean of stress and mixed dimensions. Reflects current threat environment (cyber, conflict, energy stress, supply disruption). Informational only, not used in `overallScore`.
- **trend**: Direction of score movement over the last 30 days (`rising`, `stable`, or `falling`), based on daily score history.
- **change30d**: Numeric score change over 30 days.
- **imputationShare**: Fraction of indicator weight from imputed (synthetic) data.
- **lowConfidence**: Boolean flag when data coverage or imputation thresholds are breached.
## For developers
The index versions along two independent axes — the shape of the response, and the formula that produces the score. Both are documented here so a client can tell which it is reading.
### Response shape
`schemaVersion: "2.0"` is the current default. Every response carries a real `pillars[]` array regrouping the six domains into structural readiness / live shock exposure / recovery capacity. Pillar scores use each member domain's published design weight scaled by that domain's average dimension coverage. The legacy `schemaVersion: "1.0"` shape (pillars empty) remains available via the `RESILIENCE_SCHEMA_V2_ENABLED=false` env flag for one release cycle.
### Active formula and rollback path
The top-level `overall_score` is the v2 non-compensatory pillar-combined formula with a min-pillar penalty. The legacy six-domain weighted aggregate remains in code as the rollback path when `RESILIENCE_PILLAR_COMBINE_ENABLED=false`, but production and validation cron are activated on the pillar-combined formula. The annual Reference Edition is a frozen, citation-quality artifact; it is intentionally separate from the live deployment manifest.
The subsection on [Pillar-combined score activation](#corpus-pillar-combined-score-activation-active) records the activation evidence and rollback mechanics. The live runtime manifest reported `formulaTag="pc"` and `constructVersions.energy="v2"` on 2026-06-02, with `/api/health` reporting `OK` for the three required energy v2 seed checks (`lowCarbonGeneration`, `fossilElectricityShare`, and `powerLosses`).
### Runtime manifest
For the live deployment state, use the [runtime manifest](https://www.worldmonitor.app/api/resilience/v1/get-runtime-manifest). It reports the active formula tag, static `dataVersion`, ranking-cache metadata, and safe derived construct versions: `constructVersions.energy` (`legacy` or `v2`) and `constructVersions.education` (`active` or `rollback`). It also reports `intervals` availability metadata for the public `scoreInterval`/`rankStable` support path without exposing deploy identifiers, raw `RESILIENCE_*` flag states, or internal cache keys. The Reference Edition remains a frozen shipped bundle; it should not be treated as proof of the runtime state currently active in production.
### Cache versioning
Cache keys include a versioned suffix that is bumped on formula changes. This invalidates stale caches and ensures all scores reflect the updated methodology. Score cache TTL is 6 hours.
## Reproducibility Appendix
The CRI is designed to be auditable end-to-end: given the Redis snapshot at any point in time, a reader should be able to reproduce any published country score from the documented formulas without running the live service.
### Redis keys used by the scorer
| Key | Type | TTL | Written by | Read by |
|---|---|---|---|---|
| `resilience:score:v28:{countryCode}` | JSON | 6 hours | `buildResilienceScore` in `server/worldmonitor/resilience/v1/_shared.ts` | `getResilienceScore` handler |
| `resilience:ranking:v28` | JSON | 12 hours | `getResilienceRanking` warm path, only when at least 90% of countries are scored (`RANKING_CACHE_MIN_COVERAGE = 0.90`) | `getResilienceRanking` handler |
| `resilience:history:v22:{countryCode}` | sorted set | indefinite, trimmed to 30 days | `appendHistory` during scoring | trend and `change30d` computation |
| `resilience:intervals:v11:{countryCode}` | JSON | 7 days; freshness monitored via `seed-meta`/health cadence | `scripts/seed-resilience-scores.mjs` | `getResilienceScore` (optional `scoreInterval` field) and `getResilienceRanking` (`rankStable`) |
| `seed-meta:resilience:static` | JSON | 400 days | `scripts/seed-resilience-static.mjs` at the end of each successful seed run | scorer for `dataVersion` population, health checks |
| `resilience:static:{countryCode}` | JSON | 400 days | `scripts/seed-resilience-static.mjs` | scorer for all baseline signals (WGI, WHO, FAO, GPI, RSF, and so on) |
| `resilience:static:index:v1` | JSON | 400 days | `scripts/seed-resilience-static.mjs` | warmup path to enumerate countries |
The public runtime manifest intentionally does not echo these Redis key names. Its `intervals` object reports a derived availability check using a fixed public sample country, the current interval methodology tag, and the latest safe observed timestamp from interval freshness metadata or the sample interval payload. `intervals.available` is `true` only when the sample payload matches the active formula, the active education construct version, and the interval methodology. If any tag is missing or different, or the interval data is missing or stale, `intervals.available` is `false` instead of throwing. This is the public audit signal that user-facing `scoreInterval` and `rankStable` support is not currently backed by readable intervals for the complete active scoring construct.
### dataVersion semantics
The `dataVersion` field on every `GetResilienceScoreResponse` is the ISO date of the `fetchedAt` timestamp stored in `seed-meta:resilience:static`. It reflects the most recent successful run of the Railway static-seed job; the widget renders it in the footer as `Seed date YYYY-MM-DD`. The label is narrower than "Data" because rolling inputs (annual UCDP GED conflict releases, outages, prices) can refresh at their own cadence after the static bundle runs — per-dimension freshness is surfaced separately via the freshness badge in the confidence grid.
### Reproducing a score by hand
Given a Redis snapshot at time T:
1. Read `seed-meta:resilience:static` for the `dataVersion`.
2. Read `resilience:static:{cc}` for the country's baseline record (WGI, WHO, GPI, RSF, FAO, IEA, and so on).
3. Read the rolling signal keys (annual UCDP GED releases, UNHCR, outages, cyber threats, prices, shipping stress, and so on) for the country's slice.
4. For each of the 21 active dimensions, apply the formulas in the Scoring Formula section with the goalposts from the Dimensions and Indicators tables. For missing signals, consult the Imputation Taxonomy table in this document.
5. Aggregate dimension scores into domain scores via coverage-weighted mean.
6. Aggregate domain scores into the three pillar scores using `domainWeight * averageDimensionCoverage` as each member domain's pillar-score influence, then compute the overall score with the pillar-combined penalized formula used by the production `pc` cache tag.
The reference-edition bundle under `docs/methodology/country-resilience-index/reference-edition/2026/` includes a frozen country-sliced Redis input manifest, the production score-cache values used as the published baseline, and a deterministic recompute script for the sampled published score run. The manifest records which large global feeds were pruned to the sampled countries so the artifact remains auditable without committing full live-event dumps.
## Construct repair history
The first-publication repair plan started with a diagnostic freeze, then sequenced energy repair, dead-signal cleanup, reserve/SWF split, and remaining health-domain follow-up. The current state is:
1. **`electricityConsumption` was a wealth proxy, not a resilience signal.** Landed in PR 1 and activated in production by the 2026-06-02 post-flip audit: the v2 construct replaces it with `powerLossesPct` (absorbing the full 0.20 grid-integrity share temporarily) plus the indirect effect via `accessToElectricityPct` (moved to the `infrastructure` domain). A second grid-integrity signal `reserveMarginPct` is deferred per plan §3.1 open-question (IEA electricity-balance coverage too sparse); when its seeder ships, 0.10 splits back out of `powerLossesPct`.
2. **Gas and coal penalized as vulnerability even when domestic.** The legacy `gasShare` / `coalShare` penalties conflate fossil-dominance with fossil-import-dependence. The v2 energy construct replaces them with a single `importedFossilDependence` composite using World Bank `EG.IMP.CONS.ZS` × `EG.ELC.FOSL.ZS` under the **Option B (power-system framing)** decision documented in the Energy Domain section.
3. **No nuclear credit in the legacy `scoreEnergy` path.** The v2 construct credits firm low-carbon generation by collapsing `renewShare` + new nuclear share + hydroelectric into a single `lowCarbonGenerationShare` indicator. The active seeder sources OWID Grapher `share-electricity-low-carbon`, a pre-aggregated renewables-plus-nuclear share of electricity generation. OWID renewables already include hydropower, so the seeder does not add hydro again; hydro-heavy countries (Norway, Paraguay, Brazil, Canada) retain their low-carbon grid credit without double-counting. The WB→OWID source swap was validated against the v2.1 acceptance gates over the full scorable universe (Spearman 0.99758, max overall move 4.04 pts, 0 countries >5 pts) — see `docs/snapshots/resilience-low-carbon-owid-migration-2026-06-10.json`. The swap also corrects WB-composite over-counting that had reported many developing-country grids at ~75-100% low-carbon (Mali 100→19.5%, Cambodia 100→40.9%, Honduras 98.5→55.4%).
4. **Sovereign-wealth buffers invisible to `reserveAdequacy`.** Fixed in PR 2 by retiring `reserveAdequacy` from the active score and splitting the construct into `liquidReserveAdequacy` + `sovereignFiscalBuffer` with a three-component haircut (access × liquidity × transparency) and a saturating transform.
5. **Dead and regional-only signals in the global core score.** ~~`fuelStockDays` (100% imputed globally), `euGasStorageStress` (EU-only), and `currencyExternal` (BIS 64-economy coverage) currently carry material weight despite insufficient coverage for a world ranking.~~ **Landed in PR 3 §3.5**: `fuelStockDays` permanently retired (coverage=0, imputationClass=null for every country — the scorer tags `null` rather than `source-failure` so the widget does not render a false "Source down" label, and the dimension is excluded from confidence/coverage averages via the `RESILIENCE_RETIRED_DIMENSIONS` registry); `currencyExternal` rebuilt on IMF inflation + WB reserves (no BIS); BIS `fxVolatility` + `fxDeviation` demoted to experimental tier; `externalDebtCoverage` re-goalposted from (0..5) to (0..2) per Greenspan-Guidotti to stop saturating at 100.
6. **No coverage-based weight cap.** ~~A dimension at 30% observed coverage carries the same weight as one at 95%.~~ **Landed in PR 3 §3.6**: CI-enforced gate (`tests/resilience-coverage-influence-gate.test.mts`) fails the build if any core indicator below the committed 70% coverage floor for the rankable universe carries more than 5% nominal weight in the overall score. The effective-influence half runs via `scripts/validate-resilience-sensitivity.mjs` as a committed artifact.
Items 1-3 are the now-active energy v2 repair; items 4-6 are landed repairs preserved here as the historical record for why the active registry has 20 scored dimensions plus 2 retired dimensions kept for schema continuity.
## Changelog
### v17 (April 2026) — universe + coverage rebuild (plan 2026-04-26-002)
**Current published shape.** Eight-PR sequence (PRs #3425, #3426, #3427, #3432, #3452, #3457, #3469, #3472, #3477) addressing the small-state inflation defect that surfaced after PR #3427's cohort dry-run: the high-income-country (HIC) cohort dropped on rank as designed (FR -33, SG -30, JP -23, AE -18, US -16, DE -13), but the tiny-state cohort still climbed (TV +6, PW +7, NR +22, MC +22). The rebuild attacks the structural cause: the index was treating microstates with thin data the same way it treated countries with full coverage.
**The five mechanisms now in the score:**
1. **Source-comprehensiveness flag (PR #3452, §U5).** 20 indicators are tagged `comprehensive: false` because their absence does not imply "nothing is happening" — event-only or sensor feeds (GPS jamming, internet outages, port activity), curated lists with partial coverage (BIS CBS/DSR, BIS REER, WTO), LMIC-only or bilateral series, and retired/rollback-only constructs. For these, `IMPUTE` swaps from the optimistic `stable-absence` (85, certainty 0.6) to the conservative `unmonitored` (50, certainty 0.3). Microstates that previously rode an "absence is good news" assumption no longer get the free lift. UCDP, IPC, and FATF are not examples here in the current registry.
2. **Coverage penalty multiplier (PR #3452, §U4).** Imputed indicators carry a 0.5× weight in the dimension blend. The dimension still scores, the imputed value still influences the result, but it does so at half-strength. Combined with the comprehensiveness flag this means a country whose dimension is entirely curated-list-absent contributes weight 0.15 (0.3 × 0.5) instead of weight 1.0 — the dim is functionally informational, not load-bearing.
3. **Per-capita normalization with 0.5M tiny-state floor (PR #3452, §U6).** `unrestEvents` and `ucdpConflict` divide by `max(populationMillions, 0.5)`. Tiny states with absolute event counts of zero used to score the same as large states with zero events; now the per-capita event rate is what enters normalization, and the floor caps the divisor so a country at 0.05M doesn't get a 200× artificial boost. UNHCR `displacementTotal` and `displacementHosted` are still scored on log10 absolute displaced-person counts, not population-normalized rates. The IMF labor seeder writes population to the static record (PR #3452 review-round-1 fix corrected a 1e6× units bug — the field is `populationMillions` but the upstream IMF `LP` series is in raw persons; fixed in commit 724dd4e95).
4. **Headline-eligible gate (PR #3469, §U7).** A country is `headlineEligible: true` only if `overallCoverage >= 0.65 AND (populationMillions >= 0.2 OR overallCoverage >= 0.85) AND !lowConfidence`. Ineligible countries surface in `greyedOut[]` (still served via the raw API for analysts who want them) but are excluded from the public ranking. This is the single change that solved the inflation defect end-to-end: the previously-inflated PW, NR, AD, FM, KI, GD, GQ, ER cohort is now routed by the headline-eligible gate instead of being described as part of the headline ranking.
5. **Symmetric gate filtering at the cache-hit path (PRs #3472, #3477, §U7 follow-up).** The gate had to be the single source of truth on every code path that returns a ranking, including the read-time path that hits cache. PR #3472 wired the gate into the cache-hit branch (the recompute path already filtered correctly); PR #3477 made it bidirectional (cached `greyedOut[]` entries with `headlineEligible: true` get promoted to `items[]` on read) and re-sorted post-promotion so a high-score promoted item lands at its correct rank, not appended at the end.
**Cache prefix bumps.** `resilience:score:v15:` → `:v16:` → `:v17:` → `:v18:` → `:v19:` → `:v20:` → `:v21:` → `:v22:` → `:v23:` → `:v24:` → `:v25:`; `resilience:ranking:v15` → `v16` → `v17` → `v18` → `v19` → `v20` → `v21` → `v22` → `v23` → `v24` → `v25`; `resilience:history:v10:` → `:v11:` → `:v12:` → `:v13:` → `:v14:` → `:v15:` → `:v16:` → `:v17:` → `:v18:` → `:v19:` → `:v20:`. The v17 bump shipped with the headline-eligible gate (PR #3469) because `headlineEligible` became a required field; cached v16 entries omitted it, and the conservative defensive default at v17 is `headlineEligible: false` (anomalous-missing → demoted) to match v17's "every legitimate writer stamps the field" contract. The v18 bump shipped with §U8.1 (net-imports denominator extended to `liquidReserveAdequacy`), v19 with the cyberDigital per-snapshot cap, v20 is reserved for the staleness-derate rollout, v21 ships the P1-1 pillar aggregation fix that applies domain design weights inside the active `pc` formula, v22 ships the round-2 inflation-stability and NaN-safe blend fixes, v23 ships the import-HHI stale/missing source-year certainty derate, the P3-8 outage-feed observed-quiet semantics, and the WTO trade-policy severity scorer fix (all batched into the same generation), and v24 ships the round-5 R5-2 / PR #4101 governance WGI indicator-slot semantics fix. v25 ships the #4009 cyberDigital discovery-day smoothing. v26 ships the flag-dark `education` scaffold so cached score payloads carry the serialized education row (#6450). **v27 ships the education activation itself (#6460)** — the flip adds a fifth core-bearing dimension to the social-governance domain, which moves every other dimension in that domain from a 1/4 to a 1/5 gate share and changes the published score for all 196 countries. Because the flip changes scores, `resilience:history:` also rotates `v20` → `v21` and the interval cache `v9` → `v10`: mixing pre- and post-flip history points would manufacture false trends, and stale sensitivity bands would produce stale `rankStable` verdicts. The interval cache was previously rotated to `resilience:intervals:v9:` so old sensitivity bands were not served alongside v25 scores. **v28 ships the production activation of `financialSystemExposure` (#6511)** — the score/ranking namespaces rotate `v27`→`v28`, history `v21`→`v22`, and intervals `v10`→`v11` so education-only and finance-on scores, trends, rankings, and stability bands do not mix.
**Empirical anchor (live `resilience:ranking:v17` captured 2026-04-28, post-#3477 merge):**
| Plan-002 anti-inversion target | v17 result | Status |
|---|---|---|
| `median(Nordics) >= median(GCC) − 5pt` | gap = +7.98 (Nordics 78.52, GCC 70.53) | **PASS** |
| `min(G7) >= max(LIC) − 10pt` | gap = +10.58 (CA 64.31, max-LIC 53.73) | **PASS** |
| `count(microstate in top 20) <= 1` | 1 (MO Macao at #4 — wealthy financial-hub case) | **PASS** |
| `median(G7) > median(microstate) + 15pt` | gap = -3.87 (G7 69.47, micro 73.34, n=2) | **margin** — only 2 microstates pass §U7 (MO + 1), and they're high-coverage hubs; the 11 demoted microstates are in `greyedOut[]` exactly as designed |
The "margin" miss on the fourth target is a measurement artifact of the gate working: the original target was calibrated against the *full* 13-state microstate cohort, but §U7 routes 11 of those 13 to `greyedOut[]` because they fail the coverage / population thresholds. The 2 microstates that pass (MO + IS) are exemplars, not the inflated cases. The defect the plan was scoped to fix — PW/NR/TV/AD class climbing into the top 30 — is solved.
**Top-20 cohort makeup at v17 publish:** 5 Nordics in top 12 (NO #2, IS #3, DK #5, SE #7, FI #12), 3 GCC in top 17 (KW #6, QA #10, AE #17), one wealthy microstate (MO #4), the rest distributed as expected (CH #1, UY #8, AT #9, NZ #11, LU #13, JP #14 — the only G7 in the top 20, PT #15, SR #16, CZ #18, WS #19, SI #20).
**v17.1 — Net-imports denominator parity for `liquidReserveAdequacy` (U8.1).** PR #3380 (Apr 24) shipped re-export-adjusted denominators for `sovereignFiscalBuffer` via the SWF seeder's `computeNetImports(grossImports, reexportShareOfImports) = grossImports × (1 − reexportShare)` helper, sourced from `resilience:recovery:reexport-share:v1` (Comtrade-backed, PR #3385). The same correction was structurally needed on the sibling `liquidReserveAdequacy` dimension — a re-export hub that consumes World Bank `FI.RES.TOTL.MO` (reserves in months of imports) gets penalized for goods that flow through its territory without settling as domestic consumption, artificially shortening the implied buffer runway.
v17.1 extends the fix to `liquidReserveAdequacy` at score time (no seeder change): the scorer reads the existing `resilience:recovery:reexport-share:v1` map and multiplies WB's pre-computed months by `1 / (1 − reexportShare)` for hub countries (today: AE at 35.5% share, PA similar). This is the algebraic inverse of dividing the denominator by `(1 − share)` — yields the same adjusted-months a custom `reserves / (net-imports / 12)` calc would produce, without re-fetching raw `FI.RES.TOTL.CD` + `BM.GSR.GNFS.CD` series. Non-hub countries (no entry in the reexport-share map) keep the raw WB value — status-quo behaviour preserved.
The fix ships with a cache-prefix bump (`v17` → `v18` for both `resilience:score:` and `resilience:ranking:`, plus `v12` → `v13` for `resilience:history:`). The `_formula` tag in cache payloads is binary `'d6' | 'pc'` and does NOT detect intra-`d6` scorer changes, so without the prefix bump cached `v17` AE/PA scores (gross-imports-denominated) would continue to serve until TTL expiry post-deploy, defeating the construct fix. History bumps in lockstep so the rolling 30-day window doesn't mix pre-fix and post-fix points and manufacture a false "improving" trend on day one. Same pattern as PR 3A's `v11` → `v12` lockstep when the SWF-side fix landed.
Expected impact at next ranking refresh (within the 6h cache TTL after deploy): AE `liquidReserveAdequacy` ≈ 38 → ≈ 64 (a +26-point dim swing); PA similar magnitude. Trend metric will show a one-time step at deploy time for these two countries; this is the corrected baseline going forward.
**v17.2 — `cyberDigital` per-snapshot burst cap (#3971).** The scorer caps each country's severity-weighted cyber-threat count at 8 before applying the existing `normalizeLowerBetter(weightedCount, 0, 25)` transform, so a same-day spike in `cyber:threats:v2` can no longer saturate the cyber sub-component to 0 and swing a country 5+ rank positions. The original fix was deliberately point-in-time because the live feed did not yet expose a usable `firstSeenAt`; the #4008 cyber seeder now persists a stable WorldMonitor-observed first-seen timestamp per indicator, enabling the #4009 discovery-day smoothing described below. The cap fix shipped with a cache-prefix bump (`v18` → `v19` for both `resilience:score:` and `resilience:ranking:`, plus `v13` → `v14` for `resilience:history:`) so cached uncapped scores and 30-day trend points do not mix with capped scores.
**v17.3 — stale observed data derates confidence coverage (P1-3).** Freshness is no longer observability-only for confidence semantics: observed dimensions marked `aging` or `stale` reduce confidence coverage for `lowConfidence`, `overallCoverage`, and headline eligibility, while the score aggregation weights remain unchanged. Expected impact at the next ranking refresh is limited to confidence badges and headline eligibility during source-specific seeder outages; steady-state annual or slow-cadence sources remain `fresh` when their seeders are running on schedule. The fix ships with a score/ranking cache-prefix bump (`v19` → `v20`) so cached `overallCoverage` and `headlineEligible` values cannot mix pre-fix full-confidence stale observations with post-fix derated confidence coverage.
**v17.4 — inflation-stability and NaN-safe blending (round 2 P2-N2/P2-N3).** `currencyExternal` now scores inflation stability around a 1-3% low-positive target band. Deflation below 0% and zero inflation no longer score as perfect; inflation above the band is penalized toward a 50% cap. The generic weighted blend helper now admits only finite numeric scores, so `NaN` cannot consume a metric's full weight and then collapse to zero. The fix ships with score/ranking cache-prefix bumps (`v21` → `v22`), history (`v16` → `v17`), and interval (`v5` → `v6`) so published scores, ranking aggregates, 30-day trends, and sensitivity bands all recompute from the same scorer math.
**v17.5 — import-HHI source-year certainty derating (#4088).** `importConcentration` keeps the Comtrade HHI score magnitude unchanged, but source years older than the normal four-year window, missing years, and malformed years now derate certainty coverage to the stale floor. Because coverage participates in the coverage-weighted recovery-domain aggregate, the fix ships with score/ranking cache-prefix bumps (`v22` → `v23`), history (`v17` → `v18`), and interval (`v6` → `v7`) so published scores, ranking aggregates, 30-day trends, and sensitivity bands do not mix pre-derate and post-derate values.
**v17.6 — outage-feed observed-quiet semantics (audit P3-8).** `infrastructure` now treats a loaded outage feed with an empty `outages[]` array as observed quiet (score 100), matching `cyberDigital`'s no-event semantics for the same upstream feed. The previous infrastructure scorer dropped the outage component when the penalty was zero, so countries with no current outage events lost the 0.25 component instead of receiving credit for observed absence. This ships in the same `v23` score / `v23` ranking / `v18` history / `v7` interval cache generation as the import-HHI derate above — both are coverage- and score-affecting freshness fixes batched into v23, so published scores, ranking aggregates, 30-day trends, and sensitivity bands recompute from the same scorer math.
**v17.7 — WTO trade-policy severity scoring (audit P2-1).** `tradePolicy` now scores WTO restriction and barrier feeds as the current one-row-per-reporter severity payload written by `scripts/seed-supply-chain-trade.mjs`: `low=0`, `moderate=1`, `high=2`, with legacy missing-status rows treated as moderate. The old count-based scorer normalized row counts against 30/40 anchors even though the seed emits at most one current row per reporter/country; that made ordinary WTO rows near-inert and never exercised the historical `IN_FORCE` multiplier. This ships in the same `v23` score / `v23` ranking / `v18` history / `v7` interval generation as the import-HHI derate and outage semantics above, so published scores, ranking aggregates, 30-day trends, and sensitivity bands recompute from the same severity-based trade-policy baseline.
**v17.8 — `cyberDigital` discovery-day smoothing (#4009).** With #4008's stable per-indicator `firstSeenAt`, `summarizeCyber` now buckets each country's severity-weighted cyber threats by discovery age (whole days), caps each discovery-day bucket at `CYBER_SNAPSHOT_WEIGHT_CAP` (8), decays older buckets with a one-day half-life (`CYBER_DISCOVERY_HALF_LIFE_DAYS = 1`), sums the decayed buckets, and re-caps the total at 8 before `normalizeLowerBetter(weightedCount, 0, 25)`. A one-off burst therefore fades to ~half after a day and ~quarter after two, while sustained day-over-day *new* discoveries can still reach the full cap. The decay is keyed on **discovery day (`firstSeenAt`), not last-active day (`lastSeenAt`)** — the feed re-stamps `lastSeenAt` toward fetch time and exposes no usable cross-day spread there, so `firstSeenAt` is the only stable axis. The honest consequence: a long-lived threat re-listed across many fetches still decays by its *original* discovery age unless the feed keeps surfacing genuinely new indicators, and upstream-dated IOCs (feodo/URLhaus/OTX `first_seen`) can enter already partly decayed. Missing, zero, malformed, or Unix-seconds `firstSeenAt` values fall back to the current-snapshot bucket, so legacy rows stay bounded rather than silently disappearing — pre-#4008 snapshots (all `firstSeenAt: 0`) score identically to the v17.2 per-snapshot cap. Expected impact at the next ranking refresh (within the 6h cache TTL after deploy): cyber-heavy countries whose `cyber:threats:v2` profile is dominated by older-`firstSeen` indicators see a one-time cyber sub-component improvement; this is the corrected baseline going forward. The fix ships with score/ranking cache-prefix bumps (`v24` → `v25`), history (`v19` → `v20`), and interval (`v8` → `v9`) so published scores, ranking aggregates, 30-day trends, and sensitivity bands recompute from the same discovery-decayed scorer math.
**Open construct gaps and operational caveats (documented honestly, not silently deferred):**
- **Economic-complexity / industrial-base indicator.** The index measures shock-absorption mechanisms (the construct test at the top of this document); it does not measure structural diversification. A country with monoculture exports + a strong central-government balance sheet can outscore a more diversified peer with weaker fiscal headroom. Adding an Atlas-of-Economic-Complexity (Hidalgo–Hausmann ECI) or manufacturing-value-added share would be a deliberate construct *expansion*, not a *correction* — flagged as a candidate for the v18 plan.
- **`importConcentration` seeder coverage gaps.** UN Comtrade HS2 bilateral can fall through to the `curated_list_absent` impute (50 / 0.3 / unmonitored) for countries whose data is available but not landing in the import-HHI cache. Known reporter-code drift is handled in the shared Comtrade reporter override map, and Russia uses a seed-only stale-period fallback because the standard four-year window currently returns no annual import rows. If valid-code reporters such as AE/RU/NO/CH remain absent after a force-refresh, treat HTTP 429s and quota-exhausted HTTP 403s as an operational Comtrade key-budget problem first: widen `IMPORT_HHI_PER_KEY_DELAY_MS`, add `COMTRADE_API_KEYS`, or lower `IMPORT_HHI_MAX_CONCURRENCY` per `docs/railway-seed-consolidation-runbook.md`. This is a seeder coverage and freshness issue, not a scoring construct issue.
- **`cyberDigital` measures discovery rate, not active stock.** Discovery-day smoothing (v17.8 / #4009, mechanics above) bounds same-day bursts and lets sustained *new-discovery* pressure reach the cap, but because decay is keyed on `firstSeenAt`, a steady-state attack from persistent infrastructure that stops surfacing new indicators fades even while still active — the dimension is a proxy for the *flow* of newly-observed threats, not the *stock* of active ones. Blending a last-active recency signal would require `cyber:threats:v2` to carry a stable, non-fetch-time `lastSeenAt`, which it currently does not. Until then this residual limitation is accepted, not silently deferred. The smoothing is scorer-side, not a separate resilience-owned EWMA key.
### v1.0 (April 2026)
**Baseline.** Scored on domain-weighted average of 5 domains and 13 dimensions (pre-Recovery domain).
- PR #2821: added the baseline-vs-stress engine and the `dataVersion` field on the response.
- PR #2847: reverted the overall-score formula from `baseline * (1 - stressFactor)` (which over-penalized every country) to a domain-weighted sum; fixed the RSF press-freedom direction so a low RSF abuse-index value maps to higher resilience.
- PR #2858: seed script now computes missing country scores directly via the scorer import path instead of relying on a separate ranking writer.
### v1.1 (April 2026) — Phase 1 reference-grade upgrade
**Previous published version.** Phase 1 of the reference-grade upgrade plan (`docs/internal/country-resilience-upgrade-plan.md`). Methodology surface reorganized for full reproducibility without changing the top-line domain weights or scoring formula.
- **T1.1** (#2941): regression test pins the Norway/US top-of-ranking ordering after an origin-document claim of a 100-point ceiling did not reproduce. Failing-then-passing test guards the invariant.
- **T1.2** (#2847, #2858): pre-existing fixes from the 2026-04-07 and 2026-04-09 origin-doc reviews that were already in main at the start of Phase 1. Re-verified no additional action needed.
- **T1.3** (#2945): methodology page promoted to `.mdx` at CII parity with the required sections (Framework / Domains / Dimensions / Normalization / Weighting / Missing-data / Confidence / Ranking / Reproducibility appendix).
- **T1.4** (#2943): `dataVersion` field wired end-to-end from `seed-resilience-static:v7.dataVersion` through the scorer to the widget footer so analysts see the exact ISO date of the underlying source data.
- **T1.5** (#2947 foundation, #2961 propagation): three-level staleness classifier (`fresh`, `aging`, `stale`) driven by the per-indicator cadence in the registry. Propagated through `scoreAllDimensions` and exposed as `ResilienceDimension.freshness.{lastObservedAtMs, staleness}` on the response.
- **T1.6** (#2949 scaffold, #2962 full grid): per-dimension confidence grid in the widget. The full grid adds an imputation-class icon column (consuming T1.7 schema) and a freshness-badge column (consuming T1.5 propagation). 5-column layout with mobile responsive breakpoint.
- **T1.7** (#2944 foundation, #2959 schema, #2964 source-failure wiring): four-class imputation taxonomy `stable-absence` / `unmonitored` / `source-failure` / `not-applicable` exposed on `ResilienceDimension.imputationClass`. The scorer aggregation pass consults `seed-meta:resilience:static.failedDatasets` and re-tags imputed dimensions as `source-failure` when the underlying adapter fetch failed. Deleted the last absence-based return branch in `scoreCurrencyExternal` so the taxonomy is the single source of truth for every imputed path.
- **T1.8** (#2946): methodology doc linter enforces dimension parity between this document and `_indicator-registry.ts`. CI fails if any dimension drifts.
- **T1.9** (this PR): cache-key / health-registry sync regression test so future version bumps in `_shared.ts` cannot silently break health probes. No cache keys were bumped in Phase 1 because every schema addition was additive with default fallbacks on the existing `resilience:score:v7` and `resilience:ranking:v9` keys.
**What did not change in v1.1**: the domain-weighted aggregation formula, the 5-domain / 13-dimension structure as of v1.1, the goalpost ranges, the per-dimension weights. (Phase 2 below added the Recovery domain + 6 new recovery dimensions for the current 6/19 shape and rewired domain weights; the aggregation formula itself was unchanged.) Phase 2 owns the structural three-pillar rebuild; v1.1 is the methodology-surface and observability lift only.
### Scorecard (v1.1 self-assessment)
Self-assessed against the standard composite-indicator review axes on a 0-10 scale. This is the Phase 1 acceptance gate defined in the upgrade plan (`Methodology ≥7.5`, `Explainability ≥7.5`). An external expert review (Phase 3 T3.8b) will supersede these self-ratings once it completes.
| Axis | Score | Rationale |
|---|---|---|
| **Methodology** | 7.5 | Every dimension has a named source, direction, goalpost range, weight, cadence, and imputation class. Missing-data rules are explicit and tagged with a 4-class taxonomy. The aggregation formula is a simple domain-weighted average, auditable from first principles. Gap: the overall-score formula is still single-axis compensatory (a strong institutional score can wash out a weak exposure score), which Phase 2 replaces with a partly non-compensatory three-pillar form. |
| **Explainability** | 7.5 | Per-dimension confidence grid in the widget shows coverage %, imputation class, and freshness for every dimension on every country. Tooltip text is generated from the taxonomy so analysts can click through to the meaning without reading this document. Gap: no waterfall chart of individual signal contributions yet, that lands in Phase 3 T3.3. |
| **Reproducibility** | 8.0 | Every dimension's sourceKey, cadence, and goalpost lives in `_indicator-registry.ts` and is linted against this doc. Cache keys were already versioned in the v1.1 implementation; see the Redis keys table above for the current score, ranking, history, and interval prefixes. `dataVersion` is written by the seed and plumbed to the widget footer. Gap: the benchmark and backtest scripts do not yet run on a CI cron; those land in Phase 2 T2.7. |
| **Source quality** | 7.0 | World Bank, IMF, WHO, IEA, UNHCR, UCDP, IPC, BIS, FAO, RSF, GPI: all authoritative. Gap: curated-list sources (BIS ~40 economies, WTO) do not cover the full WorldMonitor country set, which is why the `unmonitored` imputation class exists. Phase 2 T2.9 adds language-normalized information signal to reduce English-press bias. |
| **Timeliness** | 6.5 | Structural sources are annual (WGI, GPI, RSF, WHO, IMF macro) and dominate the total weight of the index. BIS EER is monthly. The Freshness classifier (T1.5) surfaces this at the dimension level so users can see which parts of a country score are 12 months old. The stress-side stack already includes realtime/hourly or daily inputs (`internetOutages`, `infraOutages`, `unrestEvents` at realtime; `socialVelocity` via the hourly Reddit relay with a 180-minute health budget; `cyberThreats`, `gpsJamming`, `shippingStress`, `transitDisruption`, `euGasStorageStress`, `energyPriceStress`, `newsThreatScore` at daily), while `ucdpConflict` follows annual UCDP GED releases with separate seeder-liveness monitoring. Gap: the live-shock pillar relies on those signals but the structural pillar is still capped by annual sources; Phase 2 T2.2 adds FX volatility at daily cadence to narrow the cadence gap on the currency-external dimension and the Phase 3 reference-edition split will formalize annual vs rolling cadences per pillar. |
| **Sensitivity** | 7.0 | Weight-perturbation Monte Carlo sensitivity (#2823) exists in the backtesting layer. Phase 1 did not add new sensitivity work. Overall p5/p95 score sensitivity bands are computed under the active score formula and exposed (#2877, #2885, #3967), and the widget renders the overall `[p05–p95]` range next to the score. The band is a formula-aware weight-perturbation sensitivity range, not an input-data uncertainty interval. Gap: no waterfall chart of individual signal contributions yet; that lands in Phase 3 T3.3. |
**Phase 1 acceptance gate status: met.** Both required thresholds (Methodology ≥7.5, Explainability ≥7.5) are satisfied with honest rationales. The two gaps flagged in each axis are tracked against Phase 2 and Phase 3 tasks in the upgrade plan.
### v2.0 (April 2026) — Phase 2 structural rebuild
**Current published version**. Phase 2 of the reference-grade upgrade plan (`docs/internal/country-resilience-upgrade-plan.md`). The response-shape rebuild is live: every response now carries a real domain-weighted, coverage-scaled `pillars[]` array regrouping the six domains into structural readiness, live shock exposure, and recovery capacity. The recovery domain adds six new dimensions, and the validation suite (cross-index benchmark, outcome backtest, sensitivity analysis) gates the activated pillar-combined formula. The top-level `overall_score` is now the partly non-compensatory pillar-combined score (see [Pillar-combined score activation](#corpus-pillar-combined-score-activation-active)); the six-domain weighted aggregate remains available only as the rollback path when `RESILIENCE_PILLAR_COMBINE_ENABLED=false`.
- **T2.1** (#2977): Three-pillar schema added to proto and OpenAPI. `schemaVersion: "2.0"` feature flag introduced with backward-compatible `"1.0"` fallback path for one release cycle. Response now carries a `pillars` array alongside existing `domains`.
- **T2.2a** (#2979): Signal tiering registry committed. Every indicator tagged Core, Enrichment, or Experimental with per-signal coverage percentage and license audit status. Registry enforced by CI linter.
- **T2.2b** (#2987): Recovery capacity pillar with new dimensions across a new `recovery` domain. The plan originally named hospital surge capacity, but the active recovery dimensions are fiscal space, the liquid-reserve / sovereign-fiscal-buffer split, external debt coverage, import concentration (HHI), and state continuity composite (WGI subset). Hospital capacity remains part of `healthPublicService`, not an active recovery-domain dimension. Five new seeders followed the Railway gold-standard pattern (3 real data sources, 2 stubs pending source configuration). Cache key bumped to the current version.
- **T2.3** (#2990/#3954): Three-pillar aggregation shape shipped and activated. Every response now carries real domain-weighted, coverage-scaled pillar scores and pillar coverage at `pillars[]`. Pillar weights: structural readiness 0.40, live shock exposure 0.35, recovery capacity 0.25. A penalty factor `(1 − α × (1 − min_pillar / 100))` with α = 0.5 is implemented as `penalizedPillarScore` in `server/worldmonitor/resilience/v1/_shared.ts` and is exercised by the sensitivity suite. The **top-level `overall_score` is the penalized pillar-combined form** in production; the six-domain weighted aggregate is retained as the flag-off rollback path.
- **T2.4** (#2985): Cross-index benchmark script validates the overall resilience score against three current public comparators: INFORM Risk Index, UNDP HDI, and the WorldRiskIndex vulnerability component. ND-GAIN is deferred until the validation image can unzip the 2026 archive, and Fragile States Index is retired from public artifacts because fresh bulk data is no longer available. Results are stored in `resilience:benchmark:external:v1` and committed as validation artifacts.
- **T2.5** (#2986): Outcome backtest framework covering 7 event families (FX stress, sovereign stress, power outages, food-crisis escalation, refugee surges, sanctions shocks, conflict spillover). Each family has a binary event definition, a 2024-2025 hold-out window, an AUC target of 0.75, and a 0.03 gate width for release decisions. Four families currently use frozen independently sourced 2024-2025 reference sets (FX stress, sovereign stress, power outages, sanctions shocks); three read live Redis seed outputs (food-crisis escalation, refugee surges, conflict spillover). The committed artifact exposes `dataSource` and `labelSources` per family so this split is auditable.
- **T2.6/T2.8** (#2991): Sensitivity suite v2 with 4-pass perturbation (weight, goalpost, imputation, alpha), alpha-curve analysis, and ceiling-effect detection. Release gate: no single-axis perturbation moves a top-50 country by more than 5 rank positions; overall dimension failure rate must be 20% or lower.
- **T2.7** (#2988): Railway cron service wired for weekly benchmark, backtest, and sensitivity runs. Results published to Redis with health monitoring integration. Weekly cron leaves the previous artifact in place on cold-start skips; release regeneration runs the scripts with `--strict` or `RESILIENCE_VALIDATION_STRICT=1` so skipped or failing artifacts block publication.
- **T2.9** (#2992): Language and source-density normalization for the informationCognitive dimension. The English-source-sensitive `socialVelocity` and `newsThreatScore` sub-indicator weights are attenuated by the language coverage of the source set so lower-coverage countries lean more heavily on the static RSF press-freedom indicator, which is not language-adjusted. The dimension is promoted back to Core tier after normalization.
**What changed from v1.1**: The five-domain flat structure was extended into a six-domain structure by adding the Recovery domain with six new dimensions, and a three-pillar outer layer groups the six domains into structural readiness (0.40), live shock exposure (0.35), and recovery capacity (0.25). Every response now carries real pillar scores at `pillars[]`. The `schemaVersion` field is `"2.0"` by default (env var `RESILIENCE_SCHEMA_V2_ENABLED=false` provides a rollback path). **The top-level `overall_score` is now the pillar-combined penalized formula**, which reduces compensatory washout by applying the min-pillar penalty to the weighted pillar mean. The cache key is bumped to the current version.
### Pillar-combined score activation (active)
The plan's non-compensatory pillar combine is the methodologically stronger form: it prevents a strong institutional score from fully washing out a severe live-shock exposure. Before activation we measured the actual impact on the live ranking.
**Sensitivity and comparison artifact** (2026-04-21, commit `048bb8b`, 52-country sample, regenerated after the comparison script was corrected to use the production `buildPillarList` aggregation): [`docs/snapshots/resilience-pillar-sensitivity-2026-04-21.json`](../snapshots/resilience-pillar-sensitivity-2026-04-21.json).
| Metric | Value |
|---|---|
| Spearman rank correlation (current vs proposed) | **0.9863** |
| Mean absolute score delta | **−11.30 points** (every country drops) |
| Max top-50 rank swing | **9 positions** (Syria) |
| Ceiling / floor effects under ±20% weight perturbation | **None detected** |
| Release gate result (≤20% dimensions exceeding 3-rank swing) | **PASS** (0/19 failures) |
**Top 5 movers by absolute rank change:**
| Country | Current rank | Proposed rank | Rank Δ | Current score | Proposed score | Score Δ |
|---|---:|---:|---:|---:|---:|---:|
| Syria | 40 | 49 | ↓9 | 49.64 | 30.55 | −19.09 |
| Central African Republic | 46 | 39 | ↑7 | 46.46 | 34.55 | −11.91 |
| Venezuela | 42 | 48 | ↓6 | 47.70 | 31.18 | −16.52 |
| Afghanistan | 33 | 37 | ↓4 | 54.55 | 37.97 | −16.58 |
| Russia | 23 | 27 | ↓4 | 61.08 | 46.28 | −14.80 |
**Interpretation**: Rank order is strongly preserved on the 52-country sample (Spearman 0.9863 clears the ≥0.90 bar typically required for a rank-stable methodology change). The ranking *shape* — who is top-10, who is bottom-10, Lebanon below South Africa, Norway above the US — does not materially change. However, every country's absolute score drops on average ~11 points because the penalty factor is always ≤ 1, and imbalanced countries with one very weak pillar (Syria, Afghanistan, Venezuela, Russia) drop the most (15-19 points). Balanced top-tier countries (Switzerland, Sweden, Denmark, Iceland, Norway) drop the least (5-7 points). This is the intended behavior: the penalty punishes pillar imbalance, and pillar imbalance is strongly correlated with state fragility.
**Activation status**: `RESILIENCE_PILLAR_COMBINE_ENABLED=true` is live in production and in the Railway validation cron. The rank-stability evidence supports the activated default — there is no statistical reason to keep the legacy compensatory form. The visible score drop is a methodology change, not a deterioration in country conditions. The activation wiring keeps rollback a single env-var change:
1. **Feature flag**: `RESILIENCE_PILLAR_COMBINE_ENABLED`, read dynamically from `process.env` per call. The published pillar-combined methodology is the runtime default: production Vercel and Railway validation environments set this to `true`, and an unset value also resolves to `true`. Set the flag explicitly to `false` only for the legacy six-domain rollback. Formula-tag checks (`pc` versus `d6`) reject cached scores from the other methodology, so a default or operator change cannot silently reuse cross-formula cache entries.
2. **Cache invalidation**: per-country score cache bumped from `resilience:score:v9:` to `resilience:score:v10:`, ranking cache bumped from `resilience:ranking:v9` to `resilience:ranking:v10`, and score-history bumped from `resilience:history:v4:` to `resilience:history:v5:` (subsequently bumped to `resilience:score:v11:`, `resilience:ranking:v11`, and `resilience:history:v6:` in the recovery-domain weight rebalance — see the Redis keys table above for current values). The version bumps are a clean-slate guard; the actual cross-formula isolation is the `_formula` tag written into every cached score / ranking payload and the `:d6` / `:pc` suffix on every history sorted-set member, checked at read time so a flag flip forces a rebuild without waiting for TTLs.
3. **Methodology-aware level thresholds**: `classifyResilienceLevel` reads `isPillarCombineEnabled()` and switches the high/medium cutoffs from 70/40 (6-domain) to 60/30 (pillar-combined). Without this, scale compression alone would demote FI (75.64 → 68.60) and NZ (76.26 → 67.93) from "high" to "medium" purely because the formula changed, not because anything about the country changed. The re-anchored cutoffs preserve the qualitative label for every country whose old label was correct.
4. **Re-anchored release-gate bands**: `tests/resilience-pillar-combine-activation.test.mts` pins high-band anchors (NO, CH, DK) at ≥ 55 (vs the 6-domain formula's ≥ 70 floor) and low-band anchors (YE, SO) at ≤ 40 (vs ≤ 45). The snapshot test reads `methodologyFormula` from each snapshot and applies the matching bands. The reference-edition recompute confirms the bands hold with margin after domain-weighted pillar aggregation: NO = 74.85 (≥ 55 by 19.85 points), YE = 29.20 (≤ 40 by 10.80 points).
5. **Projected and authoritative snapshots**: `docs/snapshots/resilience-ranking-pillar-combined-projected-2026-04-21.json` carries the 52-country preview tables used before activation. `docs/snapshots/resilience-ranking-2026-05-28.json` remains a labelled pre-P1-1 historical capture. `docs/snapshots/resilience-ranking-2026-08-29.json` is the current full-universe capture and applies domain design weights inside pillar aggregation.
Rollback: set `RESILIENCE_PILLAR_COMBINE_ENABLED=false`, flush the current `resilience:score:v28:*`, `resilience:ranking:v28`, `resilience:history:v22:*`, and `resilience:intervals:v11:*` keys (or wait for TTLs to expire). The 6-domain formula lives alongside the pillar combine in `_shared.ts` and needs no code change to come back.
### Scorecard (v2.0 self-assessment)
Self-assessed against the standard composite-indicator review axes on a 0-10 scale. This is the Phase 2 acceptance gate defined in the upgrade plan (`Validation >= 8.0`, `Data >= 9.0`, `Architecture >= 9.0`). An external expert review (Phase 3 T3.8b) will supersede these self-ratings once it completes.
| Axis | Score | Rationale |
|---|---|---|
| **Validation** | 8.0 | Cross-index benchmark against INFORM, UNDP HDI, and the WorldRiskIndex vulnerability component with explicit directional hypotheses. Outcome backtest across 7 event families with AUC release gates. Sensitivity suite with 4-pass perturbation and ceiling detection. Gap: external expert review (Phase 3 T3.8b) not yet complete. |
| **Data** | 9.0 | The current registry contains 72 indicators across 21 active dimensions and 6 domains (plus 2 structurally-retired dimensions kept for schema continuity). Recovery capacity uses real import-HHI data where Comtrade quota/backfill limits permit; `fuelStockDays` is retired from the core score and retained only as an experimental registry surface. Signal tiering registry tags every indicator Core/Enrichment/Experimental with coverage + license audit. Gap: reserve-margin integration, external expert review, formal refresh SLAs, and attribution/explanation surfaces. |
| **Architecture** | 9.0 | Three-pillar schema with schemaVersion feature flag for backward compat. Penalized weighted mean aggregation with documented alpha. Domain-weighted pillar scores. Cache-key versioning (bumped per schema change). Language normalization corrects English-press bias. Gap: alpha tuning is initial (0.5), needs backtest-driven refinement after live data accumulates. |
| **Methodology** | 8.5 | Every dimension has a named source, direction, goalpost, weight, cadence, imputation class, AND tier. Four-class imputation taxonomy live end-to-end. Freshness classifier surfaces staleness at the dimension level. Methodology doc linter enforces parity. Gap: three-pillar weight rationale is defensible but not yet empirically optimized. |
| **Explainability** | 8.0 | Per-dimension confidence grid with imputation icon + freshness badge. Pillar structure makes the index decomposable (structural vs live-shock vs recovery). Gap: no waterfall chart yet (Phase 3 T3.3), no change attribution (Phase 3 T3.5). |
| **Timeliness** | 7.0 | Stress-side indicators include realtime/daily inputs, with UCDP conflict pressure updated on annual GED releases and monitored separately for seeder liveness. Language normalization corrects for source-density bias. Recovery capacity adds monthly reserve + debt signals. Gap: structural sources still annual (WGI/GPI/RSF/WHO). Phase 3 reference-edition split formalizes annual vs rolling cadences per pillar. |
**Phase 2 acceptance gate status: met.** All three required thresholds (Validation >= 8.0, Data >= 9.0, Architecture >= 9.0) are satisfied. The gaps flagged in each axis are tracked against Phase 3 tasks in the upgrade plan.
### v2.1 (April 2026) — PR 1 energy construct repair (active)
**Status: active in production.** The energy construct repair originally landed behind `RESILIENCE_ENERGY_V2_ENABLED`; production now runs with the flag on, the runtime manifest reports `constructVersions.energy="v2"`, and the legacy scorer is retained as the flag-off rollback path.
- **Framing decision: Option B (power-system security).** The `energy` dimension under v2 measures power-system security, not total-energy security. See Energy Domain section above for rationale and future-reversal cost.
- **Indicators retired:** `electricityConsumption` (wealth proxy), `gasShare` / `coalShare` / `dependency` (replaced by `importedFossilDependence`), `renewShare` (absorbed into `lowCarbonGenerationShare`).
- **Indicators added (live in PR 1):** `importedFossilDependence` (composite: `EG.ELC.FOSL.ZS × max(EG.IMP.CONS.ZS, 0) / 100`, reusing the existing `resilience:static.iea.energyImportDependency.value` for net-imports), `lowCarbonGenerationShare` (OWID Grapher `share-electricity-low-carbon`: renewables plus nuclear share of electricity generation), `powerLossesPct` (`EG.ELC.LOSS.ZS`, weight absorbs the deferred `reserveMarginPct`'s 0.10 share). `accessToElectricityPct` moves to the `infrastructure` domain where it acts as a grid-collapse threshold.
- **Indicator deferred in PR 1:** `reserveMarginPct` — IEA electricity-balance seeder is out of scope per plan §3.1 open-question. Redis key name + scorer-plumbing slot reserved for the commit that ships the seeder.
- **New seeders (weekly):** `seed-low-carbon-generation.mjs` (OWID Grapher `share-electricity-low-carbon`), `seed-fossil-electricity-share.mjs` (EG.ELC.FOSL.ZS), `seed-power-reliability.mjs` (EG.ELC.LOSS.ZS). Bundled by `seed-bundle-resilience-energy-v2.mjs` for a single Railway cron service. Net-energy-imports (`EG.IMP.CONS.ZS`) is NOT a new seeder — it reuses the existing `seed-resilience-static.mjs` path. All three seed-meta keys are registered as STRICT `SEED_META` entries in `api/health.js` (NOT `ON_DEMAND_KEYS`) per plan `2026-04-24-001`: `/api/health` reports CRIT on absence/staleness and the scorer fails closed (`ResilienceConfigurationError` → source-failure) if v2 is active before seeds populate. The 2026-06-02 live audit reported `OK` for `lowCarbonGeneration`, `fossilElectricityShare`, and `powerLosses`.
- **Acceptance gates (plan §6):** Spearman vs baseline >= 0.85; no country moves >15 points; matched-pair gap signs verified; cohort median shifts capped at 10 points; per-indicator effective influence measured via the PR 0 apparatus. The post-flip ranking and acceptance artifacts still need a credentialed operator capture as `docs/snapshots/resilience-ranking-live-post-pr1-{date}.json` and `docs/snapshots/resilience-energy-v2-acceptance-{date}.json`; see `docs/methodology/energy-v2-flag-flip-runbook.md` for the exact commands and required credentials.
### v2.2 (April 2026) — PR 3 dead-signal cleanup
**Status: landing.** The dead-signal cleanup and coverage-based nominal-weight cap apply immediately because the retired constructs were never producing global signal.
- **§3.5 point 1 — `fuelStockDays` permanently retired from the core score.** IEA/EIA fuel-stock disclosure covers ~45 OECD-member countries; every other country was imputed `unmonitored`. `scoreFuelStockDays` now pins at `score=50, coverage=0, imputationClass=null` for every country. Coverage-weighted domain aggregation excludes it (coverage=0 contributes zero weight), and user-facing confidence / coverage averages exclude it via the `RESILIENCE_RETIRED_DIMENSIONS` registry filter (distinct from non-retired runtime coverage=0 entries, which must keep dragging confidence down — that is the sparse-data signal). `imputationClass=null` (not `source-failure`) because retirement is structural, not a runtime outage; `source-failure` would render a false "Source down" label in the widget on every country. The `recoveryFuelStockDays` registry entry remains (tier=`experimental`) so the data surfaces on IEA-member drill-downs. Re-retention requires a globally-comparable strategic-reserve disclosure concept (>180 countries) to emerge.
- **§3.5 point 2 — `currencyExternal` rebuilt on IMF inflation + WB reserves.** BIS REER covered only the BIS-reporting economy set, so the old composite fell through to curated_list_absent (coverage 0.3) or a thin IMF proxy (coverage 0.45) for roughly two-thirds of the 196-country public rankable universe. New dimension: `inflationStability` (IMF WEO headline inflation, weight 0.60) + `fxReservesAdequacy` (WB reserves in months, weight 0.40). Coverage ladder: both=0.85, inflation-only=0.55, reserves-only=0.40, neither=0.30. Legacy `fxVolatility` + `fxDeviation` kept as `tier='experimental'` on country drill-downs for BIS-tracked economies; BIS household debt-service ratio remains active under `macroFiscal`, not `currencyExternal`.
- **§3.5 point 3 — `externalDebtCoverage` re-goalposted from (0..5) to (0..2).** The old goalpost made ratios under 0.5 all score above 90, saturating at 100 across the full 9-country probe (including stressed states). New goalpost is anchored on Greenspan-Guidotti: ratio=1.0 (short-term debt matches reserves = reserve inadequacy threshold) → score 50; ratio=2.0 (double the threshold = acute rollover-shock exposure) → score 0. Ratios above 2.0 clamp to 0.
- **§3.6 — Coverage-and-influence gate on indicator weight.** `tests/resilience-coverage-influence-gate.test.mts` fails the build if any core indicator below the committed 70% coverage floor for the rankable universe carries more than 5% nominal weight in the overall score. The effective-influence half (variance-explained, Pearson-derivative) runs through `scripts/validate-resilience-sensitivity.mjs` and is committed as an artifact per plan §5 acceptance-criterion 9.
- **Acceptance gates (plan §6):** Spearman vs prior-state >= 0.85, no country swings >5 points from PR 1 state (plan §3.5 deliverable row 4), all release-gate anchors hold, matched-pair directions verified. Sensitivity rerun and post-PR-3 snapshot committed as `docs/snapshots/resilience-ranking-live-post-pr3-{date}.json` at flag-flip/ranking-refresh time.
- **Construct-audit updates:** `docs/methodology/indicator-sources.yaml` updates `recoveryDebtToReserves.constructStatus` from `dead-signal` to `observed-mechanism` citing the Greenspan-Guidotti anchor.
### v2.3 (August 2026) — education dimension activated (#6460)
**Status: active.** The `education` dimension shipped flag-dark on 2026-08-10 (#6450) and was activated on 2026-08-11. `RESILIENCE_EDUCATION_ENABLED` now defaults to `true`; setting it to `false` in the production environment is the rollback.
- **Construct.** One indicator, `femaleUpperSecondaryAttainment` (World Bank `SE.SEC.CUAT.UP.FE.ZS` — at least completed upper secondary, population 25+, female), promoted from `tier='experimental'` to `tier='core'`. Coverage re-measured immediately before promotion: **181 of 196**, one country above the `CORE_MIN_COVERAGE = 180` floor. The female variant is used because the causal literature the construct rests on (Striessnig, Lutz & Patt 2013; Lutz, Muttarak & Striessnig 2014) reports the income-independent effect on female secondary attainment specifically, and coverage is identical across the female, male, and total series.
- **Domain effect.** Adds a fifth core-bearing dimension to social-governance, moving every other dimension in that domain from a 1/4 to a 1/5 gate share. The six WGI governance indicators are the largest single loser.
- **Measured acceptance (196 countries, production seeds, flag-off vs flag-on, pillar-combined penalized):** Spearman 1.00, max country drift 3.45 (VU), worst cohort median shift −1.08 (fragile-states), 47/51 Core indicators measurable (92.16%). Harness: `scripts/dry-run-resilience-education-flip.mjs`.
- **Directional gates.** Spearman and max-drift are magnitude gates — they bound how far a ranking moves, never which way, and a fully inverted low-weight dimension passes both (the `financialSystemExposure` finding in #6459). Three whole-index matched pairs were added specifically to bound this construct's known cohort-lag property: `pt-vs-uz` and `es-vs-by` at minGap 3, `ch-vs-tm` at minGap 5. All hold post-flip at 5.84, 9.01 and 28.28. They are whole-index rather than dimension-scoped because education is a single monotone component whose direction cannot invert; the risk it carries is a correct dimension with a wide spread moving the overall ranking, which only the overall score can see.
- **Weight.** Held at 0.5. The runbook's pre-agreed fallback (halve to 0.25 if a gate fails) was measured and found not to apply: the only failing matched pair, `in-vs-za`, was already below its minGap with the flag off (2.54 vs 3) and remained so at 0.25 (2.13), so it is a pre-existing condition this activation did not cause. Tracked in #6466.
- **Cache generations rotated** — score `v26`→`v27`, ranking `v26`→`v27`, history `v20`→`v21`, intervals `v9`→`v10`. History and intervals rotate because the flip changes scores: mixing pre- and post-flip history points would manufacture false trends and stale sensitivity bands would produce stale `rankStable` verdicts.
- **Dark-dimension reconciliation.** `financialSystemExposure` remains outside `RESILIENCE_FLAG_DARK_WHEN_ZERO_COVERAGE`, but its owner-controlled production flag is now on. Keeping it outside the exclusion set means active observations and source failures remain visible in coverage and `headlineEligible`; the code default remains false for CI and rollback.
### v2.4 (August 2026) — financial-system exposure activated (#6511)
**Status: active in production.** `RESILIENCE_FIN_SYS_EXPOSURE_ENABLED=true` was already set in Vercel production when this protocol was backfilled. The code default remains `false`, so CI keeps the flag-off rollback posture and an operator can disable the production flag without a code change.
- **Cache generations rotated** — score/ranking `v27`→`v28`, history `v21`→`v22`, and intervals `v10`→`v11`. The rotation keeps education-only and finance-on scores, history, rankings, and stability bands separate.
- **Acceptance harness.** `scripts/dry-run-resilience-financial-system-exposure-flip.mjs` reads one production Upstash snapshot without writing Redis, then compares flag-off and flag-on full-universe scores. It fails closed on unresolved reads and records source and harness provenance in the committed acceptance artifact.
- **Measured acceptance (196 countries, 2026-08-13).** Spearman **0.9983**; **196/196 (100%)** moved by less than 3 overall points; maximum absolute movement **2.23**; no non-sanctions country moved by more than 12; headline eligibility changed for **0** countries. The capture resolved **650** Redis keys and used score/ranking `v28`, history `v22`, and intervals `v11`. The run emitted the known static WGI source-failure diagnostics, so this is a paired finance activation measurement, not an all-source health claim.
- **Acceptance gates.** Spearman must be at least 0.85, at least 60% of countries must move by less than 3 overall points, and no non-sanctions country may move by more than 12 points. Headline-eligibility changes and finance source-failure rows remain explicit in the artifact.
- **Issue state.** #6461 is already closed by #6515, which landed the residual absence-as-strength fix. No issue reprioritization mutation is required.
See [`financial-system-exposure-flag-flip-runbook.md`](https://github.com/koala73/worldmonitor/blob/main/docs/methodology/financial-system-exposure-flag-flip-runbook.md) and the committed [`resilience-financial-system-exposure-acceptance-2026-08-13.json`](../snapshots/resilience-financial-system-exposure-acceptance-2026-08-13.json) snapshot for the operator procedure and measured result.
### Editorial notes
- This document is maintained at parity with OECD/JRC composite-indicator standards: every dimension has a named source, direction, goalpost range, weight rationale, cadence, and imputation class. A methodology doc linter (Phase 1 T1.8) validates that the list of dimensions in the indicator registry matches the list documented here and fails CI if they drift.
- For questions about an individual country's score, the widget footer shows the `dataVersion`, the confidence label, and the 30-day delta; the deep-dive panel exposes per-dimension breakdowns so an analyst can see which component moved. The full proto schema lives in `docs/api/ResilienceService.openapi.yaml`.
## Revision and corrections log
This public log records material revisions to WorldMonitor datasets and
methods. The automated Energy Atlas asset-change writer remains planned.
What ships today on the Energy Atlas includes the evidence bundles inside each
RPC response (`ListPipelines`, `ListStorageFacilities`,
`ListFuelShortages`, `ListEnergyDisruptions`), and the methodology pages
that describe how public badges are derived from those bundles. Until the
asset-change writer ships:
`GetPipelineDetail.revisions` and `GetStorageFacilityDetail.revisions`
return empty arrays, and there is no automated correction-intake path.
## Published revisions
| Effective date | Product | Revision | Published effect |
| --- | --- | --- | --- |
| 2026-09-08 | Country pages / country brief | **Unsupported brief citations withheld.** The September 7 audit reported 20 of 50 sampled "What this means" bullets naming assets absent from their grounding headlines, including Cerrejón, Caño Limón-Coveñas, Tamar, Leviathan and El Guri. A citation index alone did not prove that its source named the entities in the claim. The freeze and page build now check each paragraph or bullet against every source it cites and withhold the whole brief when the check fails. Uncited lines must also ground their names in the retained source set. | A local replay of the 2026-09-04 snapshot with this rule withholds all 22 briefs that survived the earlier publisher floor, leaving 0 published briefs from that capture. These are precautionary withdrawals, not a claim that all their statements are false. Dated headlines and timelines remain. The same rule applies to the downloadable datasets and future freezes; the historical snapshot is preserved. Only source titles are retained, so the check cannot rely on article bodies and can reject legitimate paraphrases or mixed-source paragraphs. This checks named-entity presence, not factual entailment. See [issue #7865](https://github.com/koala73/worldmonitor/issues/7865). |
| 2026-09-05 | Country pages / country brief | **Single-publisher briefs withheld; brief text and grounding corrected.** A generated country brief is now published only when its grounding headlines come from at least two distinct publishers; a 24/48/72h outlook synthesised from one outlet is withheld and the page keeps its dated headlines. The country matcher that selected grounding headlines matched bare ISO codes as words, so a few briefs were grounded on another country's news (an "African Union (AU)" story on the Australia page); one shared matcher now grounds the pages, the dashboard and the MCP tool. Briefs also rendered raw markdown markers and, for countries outside the tier-1 table, the ISO code in place of the country name in the "What this means for" heading. | Applies to every indexed country page, its dataset download and the weekly frozen snapshot. On the 2026-09-04 snapshot 18 of 40 published briefs are withdrawn (including the wrong-country ones and one grounded on three articles from a single newsroom) and the remaining 22 render as structured text with the country name in the heading. New briefs are grounded and named correctly from the first refresh after this change. See [PR #7762](https://github.com/koala73/worldmonitor/pull/7762) for [issue #7748](https://github.com/koala73/worldmonitor/issues/7748) and [issue #7738](https://github.com/koala73/worldmonitor/issues/7738). |
| 2026-09-02 | Chokepoint status | **Source availability separated.** NGA navigational warnings, the AIS snapshot, relay transit counts and PortWatch movement are now four independent availability domains, so one missing source no longer hides another's valid values and an unavailable reading is never shown as a measured zero or a calm level. The combined warnings row was split into navigational warnings and AIS disruptions, and congestion is labelled AIS congestion. | Applies to all 13 chokepoint pages, dashboard panels, frozen snapshots, OpenAPI clients and the public agent skill. Cached payloads and frozen snapshots predating the new source flags fail closed, so warnings, AIS disruptions and AIS congestion stay withheld until a fresh capture replaces them. See [PR #7535](https://github.com/koala73/worldmonitor/pull/7535) for [issue #7529](https://github.com/koala73/worldmonitor/issues/7529). |
| 2026-09-01 | Chokepoint status | **Derived metrics withheld without a transit count.** Week-over-week movement, navigational-warning counts and AIS-derived congestion were published even when the day's transit count was unavailable, contradicting the page's own transit disclaimer. A shared coverage rule now withholds every metric that depends on a missing transit count. | Applies to all 13 chokepoint pages and the live browser refresh path. Withheld values render as an em dash or are hidden; complete transit coverage is unchanged. See [PR #7515](https://github.com/koala73/worldmonitor/pull/7515) for [issue #7503](https://github.com/koala73/worldmonitor/issues/7503). |
| 2026-06-01 | Country Resilience Index | **P1-1 pillar aggregation correction.** Pillar scores now apply each domain's design weight inside pillar aggregation. The 2026-05-28 snapshot used the earlier coverage-only member aggregation and remains a labelled historical capture. | Live score, ranking, history, and interval cache generations changed together. The 2026-08-29 full-universe capture is the first published country snapshot after this correction. See [PR #4021](https://github.com/koala73/worldmonitor/pull/4021). |
The crawlable CRI snapshot workflow is scheduled for the first day of each month (`17 5 1 * *` UTC). It captures the credentialed full-universe ranking, rebuilds the crawlable corpus and sitemap, and opens a pull request for review. Off-cycle captures also ship when a methodology correction needs a new full-universe artifact. The current published snapshot is `resilience-ranking-2026-08-29.json` (captured 2026-08-29, after the P1-1 pillar-aggregation correction), not a first-of-month run.
## Energy Atlas automated revision log (planned)
WorldMonitor's Energy Atlas publishes evidence bundles — not opinions —
for pipelines, storage facilities, [fuel shortages](/docs/api-reference/supplychainservice/listfuelshortages), and disruption
events. A deterministic, versioned classifier turns those bundles into
public badges (`flowing` / `reduced` / `offline` / `disputed` for
assets; `confirmed` / `watch` for shortages).
When the classifier goes live, every time it changes a public field —
because evidence updated, because staleness decayed a badge, because a
new classifier version re-derived an old asset, or because an
operator/regulator-submitted correction was applied — it will write an
append-only entry here.
This is the designed asset-level audit record. The evidence registries
are forward-looking snapshots. The automated log will record how each
status changed.
## Planned data shape
Each entry is planned as a row with the following fields:
```ts
{
date: string, // ISO8601 — when the change was written
assetOrEventId: string, // matches an id in the pipeline / storage / shortage / disruption registry
fieldChanged: string, // e.g. 'publicBadge', 'physicalState', 'severity', 'evidence.sanctionRefs'
previousValue: unknown, // value before the change
newValue: unknown, // value after the change
trigger: 'classifier' | 'source' | 'decay' | 'override',
sourcesUsed: string[], // URLs cited by the classifier for this change
classifierVersion: string, // version that produced newValue (e.g. 'badge-deriver-v1')
}
```
The matching proto surface lives at
`GetPipelineDetail.revisions` and `GetStorageFacilityDetail.revisions`.
Both currently return empty arrays by design — the handlers document
"Revision log arrives in a post-launch release" in their code comments
rather than pretending the surface is live.
### Planned trigger vocabulary
- **`classifier`** — a routine classifier pass re-derives the field
from the current evidence bundle. Expected to be the most common
trigger once live.
- **`source`** — a new evidence source arrives (regulator filing,
operator press release, sanction list update) and the classifier
re-derives accordingly.
- **`decay`** — the evidence is older than the staleness window
(14 days for registry fields, 30 days for shortage evidence) and the
classifier demotes a non-positive badge to `disputed` or `watch`.
- **`override`** — a break-glass manual override is applied. Reserved
for demonstrably-wrong classifier outputs flagged by readers.
Overrides will carry the same `sourcesUsed` discipline as classifier
entries.
## What is live today
- **Published methodology revisions.** The table on this page records
changes that affect public datasets and their interpretation.
- **Evidence bundles on every asset.** Click any pipeline, storage
facility, or shortage pin on the [Energy Atlas](https://energy.worldmonitor.app/dashboard)
and you see its full evidence bundle: physical state, commercial
state, operator statements (with URL and date), sanction references
(with authority + list ID + URL), classifier version and confidence,
and the timestamp of the most recent evidence update. This is the
primary audit surface today.
- **Public methodology pages.** The derivation rules, staleness
windows, and evidence-threshold specs are all publicly documented:
- [Pipeline Registry](/docs/methodology/pipelines)
- [Storage Facilities](/docs/methodology/storage)
- [Fuel Shortages](/docs/methodology/shortages)
- [Disruption Event Log](/docs/methodology/disruptions)
- [Chokepoints](/docs/methodology/chokepoints)
- **Versioned classifier output.** Every RPC response carries a
`classifier_version` field. A reader can pin expectations to a
version today even though the revision-log history-of-versions
surface isn't yet published.
## What is not live today
- Automated Energy Atlas asset-level entries. This page will list those
rows after the classifier ships.
- An automated correction-intake pipeline. If you spot something
wrong, use the feedback channels at
[worldmonitor.app](https://www.worldmonitor.app) or open a GitHub issue
at the [public repository](https://github.com/koala73/worldmonitor/issues).
Corrections are not yet on the classifier's path — they're handled
manually today.
- The `override`-trigger entry writer. Same dependency: ships with the
classifier.
## Verifying a badge today (pre-classifier)
Until the revision log is live, the audit path for any status on the
Energy Atlas is:
1. Open the asset drawer (click the pipeline / storage dot / shortage
pin).
2. Read the evidence bundle — every source is linked with publication
date and authority (`regulator` / `operator` / `press` /
`satellite`).
3. Check the methodology page for the asset class — the derivation
rules are deterministic and versioned.
4. If all evidence is current and the public badge still looks wrong
after walking the rules, open an issue on the public repository
with the asset id, the current evidence bundle, and your reasoning.
The manual review path will seed `override` entries once the
revision log ships.
## Why document this surface before it ships
Two reasons to publish the spec before the writer lands:
1. **Contract stability.** The shape of `revisions` in
`GetPipelineDetail.revisions` / `GetStorageFacilityDetail.revisions`
is part of the RPC contract that agents and MCP clients consume.
Documenting it now means downstream consumers can code against the
stable shape before live data arrives.
2. **Policy signalling.** Evidence-first classification only works if
the audit trail is committed-to in public, not treated as an
internal implementation detail. Publishing the planned shape and
submission policy ahead of the writer is the commitment.
Neither reason justifies overstating the current state. When automated
asset-level entries start appearing, this page will replace the status
callout with the last update time.
## Published country resilience ranking
Snapshot `docs/snapshots/resilience-ranking-2026-08-29.json` captured 2026-08-29. This 2026-08-29 snapshot applies domain design weights inside pillar aggregation. Earlier published CRI numbers used coverage-only member aggregation and are not directly comparable.
| Rank | Country | Code | Score | Coverage |
| ---: | --- | --- | ---: | ---: |
| 1 | Switzerland | CH | 76.8 | 76% |
| 2 | Norway | NO | 75.4 | 76% |
| 3 | Iceland | IS | 74.6 | 76% |
| 4 | Denmark | DK | 72.5 | 77% |
| 5 | Japan | JP | 71.3 | 75% |
| 6 | New Zealand | NZ | 68.8 | 75% |
| 7 | Czechia | CZ | 68.8 | 77% |
| 8 | Samoa | WS | 67.4 | 76% |
| 9 | Luxembourg | LU | 67.1 | 76% |
| 10 | Sweden | SE | 66.9 | 77% |
| 11 | United Arab Emirates | AE | 66.5 | 74% |
| 12 | Finland | FI | 65.6 | 77% |
| 13 | Uruguay | UY | 65.3 | 75% |
| 14 | Italy | IT | 64.9 | 77% |
| 15 | Kuwait | KW | 64.6 | 74% |
| 16 | Bulgaria | BG | 64.3 | 81% |
| 17 | Albania | AL | 64.3 | 81% |
| 18 | Spain | ES | 64.2 | 77% |
| 19 | Slovenia | SI | 64.1 | 76% |
| 20 | Austria | AT | 64.0 | 76% |
| 21 | Portugal | PT | 63.9 | 77% |
| 22 | Ireland | IE | 63.5 | 76% |
| 23 | Netherlands | NL | 63.4 | 77% |
| 24 | Germany | DE | 63.2 | 77% |
| 25 | Latvia | LV | 62.8 | 76% |
| 26 | Lithuania | LT | 62.6 | 76% |
| 27 | France | FR | 62.5 | 77% |
| 28 | Montenegro | ME | 62.3 | 77% |
| 29 | Cyprus | CY | 61.9 | 76% |
| 30 | Qatar | QA | 61.7 | 75% |
| 31 | Serbia | RS | 61.7 | 79% |
| 32 | Saudi Arabia | SA | 61.6 | 76% |
| 33 | United Kingdom | GB | 61.6 | 76% |
| 34 | Slovakia | SK | 61.6 | 76% |
| 35 | Barbados | BB | 61.2 | 66% |
| 36 | Poland | PL | 61.2 | 76% |
| 37 | Hungary | HU | 61.2 | 77% |
| 38 | Croatia | HR | 60.6 | 76% |
| 39 | Uzbekistan | UZ | 60.6 | 81% |
| 40 | Greece | GR | 60.5 | 77% |
| 41 | Estonia | EE | 60.4 | 76% |
| 42 | Peru | PE | 60.4 | 81% |
| 43 | Australia | AU | 60.3 | 77% |
| 44 | United States | US | 60.0 | 76% |
| 45 | Belgium | BE | 59.6 | 77% |
| 46 | Brunei | BN | 59.5 | 75% |
| 47 | Canada | CA | 59.4 | 77% |
| 48 | Tajikistan | TJ | 59.2 | 79% |
| 49 | Romania | RO | 58.9 | 76% |
| 50 | Azerbaijan | AZ | 58.8 | 79% |
| 51 | Chile | CL | 58.7 | 75% |
| 52 | Solomon Islands | SB | 58.3 | 71% |
| 53 | Israel | IL | 57.7 | 76% |
| 54 | Kazakhstan | KZ | 57.5 | 78% |
| 55 | Mongolia | MN | 57.4 | 81% |
| 56 | Brazil | BR | 57.4 | 81% |
| 57 | Singapore | SG | 57.4 | 73% |
| 58 | South Korea | KR | 57.3 | 77% |
| 59 | Georgia | GE | 56.8 | 81% |
| 60 | Paraguay | PY | 56.7 | 81% |
| 61 | Malaysia | MY | 56.6 | 76% |
| 62 | Belize | BZ | 56.6 | 77% |
| 63 | Oman | OM | 56.5 | 76% |
| 64 | Malta | MT | 56.4 | 76% |
| 65 | Bosnia & Herzegovina | BA | 56.2 | 81% |
| 66 | Fiji | FJ | 55.9 | 77% |
| 67 | Mauritius | MU | 55.9 | 85% |
| 68 | Nicaragua | NI | 55.8 | 79% |
| 69 | Suriname | SR | 55.6 | 79% |
| 70 | China | CN | 55.3 | 81% |
| 71 | Moldova | MD | 55.3 | 81% |
| 72 | Belarus | BY | 55.2 | 77% |
| 73 | Timor-Leste | TL | 55.2 | 81% |
| 74 | Jamaica | JM | 55.2 | 81% |
| 75 | Philippines | PH | 54.6 | 81% |
| 76 | Panama | PA | 54.5 | 75% |
| 77 | Bhutan | BT | 54.5 | 74% |
| 78 | Hong Kong | HK | 54.2 | 70% |
| 79 | Armenia | AM | 54.1 | 81% |
| 80 | Trinidad & Tobago | TT | 54.1 | 75% |
| 81 | Vanuatu | VU | 54.1 | 73% |
| 82 | El Salvador | SV | 54.0 | 81% |
| 83 | Cape Verde | CV | 54.0 | 84% |
| 84 | North Macedonia | MK | 53.9 | 79% |
| 85 | São Tomé & Príncipe | ST | 53.7 | 76% |
| 86 | Guyana | GY | 53.5 | 77% |
| 87 | Kyrgyzstan | KG | 53.5 | 75% |
| 88 | Jordan | JO | 52.9 | 81% |
| 89 | Ecuador | EC | 52.6 | 81% |
| 90 | Vietnam | VN | 52.6 | 81% |
| 91 | Thailand | TH | 52.3 | 81% |
| 92 | Costa Rica | CR | 52.0 | 75% |
| 93 | Colombia | CO | 51.9 | 81% |
| 94 | Algeria | DZ | 51.9 | 83% |
| 95 | Dominican Republic | DO | 51.9 | 81% |
| 96 | Indonesia | ID | 51.7 | 81% |
| 97 | Maldives | MV | 51.7 | 73% |
| 98 | Papua New Guinea | PG | 51.6 | 79% |
| 99 | Russia | RU | 51.5 | 78% |
| 100 | Laos | LA | 50.8 | 80% |
| 101 | Lesotho | LS | 50.8 | 84% |
| 102 | Morocco | MA | 50.7 | 84% |
| 103 | Argentina | AR | 50.7 | 79% |
| 104 | Guatemala | GT | 50.6 | 81% |
| 105 | Cambodia | KH | 50.5 | 80% |
| 106 | India | IN | 50.0 | 81% |
| 107 | Nepal | NP | 49.9 | 80% |
| 108 | Honduras | HN | 49.7 | 81% |
| 109 | Turkmenistan | TM | 49.6 | 66% |
| 110 | Ghana | GH | 48.9 | 85% |
| 111 | Sri Lanka | LK | 48.8 | 81% |
| 112 | Egypt | EG | 48.7 | 83% |
| 113 | Namibia | NA | 48.4 | 79% |
| 114 | South Africa | ZA | 48.2 | 85% |
| 115 | Bahamas | BS | 48.2 | 73% |
| 116 | Comoros | KM | 47.7 | 73% |
| 117 | Zambia | ZM | 47.5 | 83% |
| 118 | Gambia | GM | 47.1 | 83% |
| 119 | Gabon | GA | 46.8 | 77% |
| 120 | Mexico | MX | 46.6 | 81% |
| 121 | Liberia | LR | 46.5 | 79% |
| 122 | Bahrain | BH | 46.3 | 77% |
| 123 | Mauritania | MR | 46.2 | 82% |
| 124 | Bolivia | BO | 46.0 | 79% |
| 125 | Turkey | TR | 45.1 | 79% |
| 126 | Libya | LY | 45.0 | 68% |
| 127 | Lebanon | LB | 45.0 | 77% |
| 128 | Ukraine | UA | 44.9 | 81% |
| 129 | Botswana | BW | 44.6 | 84% |
| 130 | Rwanda | RW | 44.4 | 84% |
| 131 | Sierra Leone | SL | 44.2 | 79% |
| 132 | Djibouti | DJ | 43.6 | 83% |
| 133 | Tunisia | TN | 43.5 | 85% |
| 134 | Côte d’Ivoire | CI | 43.5 | 78% |
| 135 | Congo - Brazzaville | CG | 43.3 | 82% |
| 136 | Madagascar | MG | 43.0 | 85% |
| 137 | Angola | AO | 42.9 | 83% |
| 138 | Togo | TG | 42.6 | 78% |
| 139 | Senegal | SN | 42.5 | 78% |
| 140 | Myanmar | MM | 42.2 | 74% |
| 141 | Tanzania | TZ | 42.1 | 78% |
| 142 | Malawi | MW | 42.0 | 73% |
| 143 | Uganda | UG | 41.9 | 85% |
| 144 | Kenya | KE | 41.2 | 85% |
| 145 | Guinea | GN | 41.1 | 79% |
| 146 | Eswatini | SZ | 41.0 | 85% |
| 147 | Pakistan | PK | 40.8 | 81% |
| 148 | Bangladesh | BD | 40.8 | 77% |
| 149 | Burundi | BI | 40.7 | 81% |
| 150 | Haiti | HT | 40.5 | 72% |
| 151 | Guinea-Bissau | GW | 40.1 | 73% |
| 152 | Nigeria | NG | 39.9 | 83% |
| 153 | Benin | BJ | 39.5 | 78% |
| 154 | Mozambique | MZ | 39.2 | 85% |
| 155 | Cameroon | CM | 39.0 | 84% |
| 156 | Zimbabwe | ZW | 38.3 | 83% |
| 157 | Congo - Kinshasa | CD | 38.2 | 83% |
| 158 | Central African Republic | CF | 37.8 | 78% |
| 159 | Ethiopia | ET | 37.2 | 82% |
| 160 | Burkina Faso | BF | 36.5 | 78% |
| 161 | Chad | TD | 35.7 | 75% |
| 162 | Iran | IR | 34.5 | 71% |
| 163 | Afghanistan | AF | 34.0 | 69% |
| 164 | Niger | NE | 33.8 | 76% |
| 165 | Venezuela | VE | 33.7 | 65% |
| 166 | Mali | ML | 32.0 | 75% |
| 167 | Yemen | YE | 29.6 | 69% |
| 168 | South Sudan | SS | 28.5 | 71% |
| 169 | Somalia | SO | 21.1 | 69% |
| 170 | Sudan | SD | 19.7 | 71% |
Unranked (greyed-out) countries in the same capture:
- Andorra (AD)
- Antigua & Barbuda (AG)
- Cuba (CU)
- Dominica (DM)
- Eritrea (ER)
- Micronesia (FM)
- Grenada (GD)
- Equatorial Guinea (GQ)
- Iraq (IQ)
- Kiribati (KI)
- St. Kitts & Nevis (KN)
- North Korea (KP)
- Saint Lucia (LC)
- Liechtenstein (LI)
- Monaco (MC)
- Marshall Islands (MH)
- Macau (MO)
- Nauru (NR)
- Palau (PW)
- Seychelles (SC)
- San Marino (SM)
- Syria (SY)
- Tonga (TO)
- Tuvalu (TV)
- Taiwan (TW)
- St. Vincent & Grenadines (VC)