How we score travel safety

Every IsMyTripSafe report answers one question — is this place safe to visit? — with a 0–100 score (100 = safest) built the same way for every destination. Nothing on a report page is hand-written per city; everything is computed from the sources below, so scores are comparable across destinations.

The score

20+ indicators are grouped into six hazard families: crime, conflict & terrorism, official guidance, institutions & rule of law, everyday hazards, and health & environment. Within a family, indicators are averaged — they are several noisy readings of one underlying thing, so averaging cancels noise. Across families they are not averaged: a good score in one family cannot buy off a bad one elsewhere. High risk in any single family dominates the result, which is the only honest way to combine hazards a traveller would meet all at once.

A few facts are categorical, not quantitative. A "Do Not Travel" advisory or active-conflict conditions set a ceiling on the score that no other indicator can argue away; when a ceiling binds, the report says so and names the reason.

Where institutions are weak, flattering recorded-crime figures are read with appropriate caution, and a missing hazard family is never silently assumed safe — each report carries a confidence figure that says how much of the score is backed by measured data rather than estimates.

AI-assisted field research

Databases lag reality, so each report also includes AI-assisted field research: an agent searches current news and traveller reporting for recent incidents, unrest, district-level safety, scams and traveller sentiment, with the database profile and official advisories supplied as fixed ground truth it must not contradict. That research contributes to the published score — its share is disclosed on every report — and its street-crime and sentiment findings are shown on the page with their sources.

Advisory levels are never AI-generated — they are shown verbatim from the issuing governments' own feeds. The scoring, the data and the published numbers are fully transparent; only the prose research summary is written by a model, over real, cited evidence.

Personalised scores

Safety is not one number. Per-traveller scores — solo, family, a women-only party, nightlife, 65+ — are deterministic re-weightings of the same category scores: more weight on health for families and older travellers, more on street-crime where it matters most. Same inputs, same answers, same number, every time — nothing about personalisation is AI-generated.

Update cadence

Live feeds (advisories, air quality, disaster alerts, weather) are fetched at report build time, and a report's "last updated" date is the moment its data was actually rebuilt — we never bump dates without rebuilding the data behind them. Reports are rebuilt on demand once they're older than seven days.

Limitations

• Most statistical indicators are national; city-level nuance comes from FBI and Numbeo (where cities have enough contributors), OpenStreetMap, live environmental feeds and the field research.
• Survey-based indicators (victimisation, feeling safe at night) can be years old — every value shows its year on the report.
• Crowdsourced indices reflect perception, which can diverge from recorded crime.
• A score is a summary, not a guarantee. Conditions change fast; check your government's advisory before you travel.

Every source we use