How We Calculate Safety Scores

Overview

We aggregate data from 40+ trusted public sources to compute a composite safety score (1-10) for every country. Higher scores indicate safer destinations. Our hybrid scoring engine uses a weighted geometric mean across five categories — Conflict (30%), Crime (25%), Health (20%), Governance (15%), and Environment (10%) — so that a single critical weakness (e.g. active war) cannot be masked by strong scores elsewhere. Additional safety nets include a hard cap when a majority of government advisories issue "Do Not Travel" warnings, a critical floor when any category falls below a danger threshold, and advisory-based blending for countries with limited data coverage.

Data Sources

Government Travel Advisories

We collect travel advisory levels from 37 governments across all continents. Each advisory is normalized to a unified 1-4 scale (1=safe, 4=do not travel) and weighted by tier in the Conflict pillar.

Scoring Formula

Raw indicator values are normalized to a 0-1 scale (higher = safer). Within each pillar, indicators have explicit sub-weights and are blended via baseline (~70%) and signal (~30%) tiers with exponential freshness decay. The composite score uses a weighted geometric mean of the five pillar scores — unlike an arithmetic mean, a geometric mean ensures that a single dangerously low pillar drags the overall score down significantly. Three additional safety mechanisms apply: (1) if a majority of government advisories reach Level 4 "Do Not Travel", the score is capped proportionally to the worst pillar; (2) if any pillar with data falls below a critical threshold, the score is capped to the weakest pillar; (3) for countries with limited data coverage, the score blends toward an advisory-derived estimate.

Baseline + Signal Architecture

Baseline sources (World Bank, INFORM, GPI) are updated annually and provide a stable foundation for scoring. Signal sources (ReliefWeb, GDACS, and 37 government travel advisories from countries spanning all continents) update daily or weekly and capture emerging crises such as armed conflicts, natural disasters, and disease outbreaks. Signal source influence is capped at 30% within each pillar, ensuring that volatile short-term data cannot dominate long-term structural indicators.

Data Freshness Decay

Each data source has a configured half-life for freshness decay. If a source's data is one half-life old, it contributes 50% of its full weight; at two half-lives, 25%; and so on. Beyond the configured maximum age, stale data is dropped entirely. This ensures scores always reflect the most current available information while gracefully degrading when sources are temporarily unavailable.

How INFORM Enriches the Scoring

The INFORM Risk Index, published by the European Commission Joint Research Centre and UN OCHA, provides granular sub-indices for natural hazards, epidemic risk, health conditions, governance fragility, and climate/flood exposure. These indicators complement World Bank governance data by adding hazard-specific dimensions that are especially relevant to travelers.

Global Peace Index

The Global Peace Index (GPI) from the Institute for Economics and Peace is integrated into the Conflict pillar. GPI indicators (overall score, safety & security, militarisation) provide a comprehensive picture of peacefulness based on 23 qualitative and quantitative indicators across 163 countries.

Category Weights

Categories are weighted to reflect their relative importance to traveler safety. Conflict carries the highest weight (30%) because active conflicts pose the most immediate and severe risk. Crime contributes 25%, as it directly affects personal safety day-to-day. Health (20%) remains important but is often manageable with precautions. Governance (15%) captures institutional stability as an indirect factor. Environment (10%) reflects natural and climate hazards that, while relevant, tend to be more localized or seasonal.

Understanding Each Category

Click on each category below to learn what it measures and how to interpret scores.