Rough AI truth score
92/100
The zoonotic majority, reservoir-host logic, and ecological drivers of emergence are strongly supported. Predicting that a particular next pandemic will be zoonotic is probabilistic, not a prophecy.
Based on three central claims · high confidence
A global event analysis estimated that about sixty percent of emerging-disease events were zoonotic and nearly seventy-two percent of those had wildlife origins. Definitions and surveillance bias affect the exact fractions, not the broad pattern.
Pathogen presence in wildlife is only one step: contact rates, host density, environmental disruption, intermediate hosts, adaptation, and human networks determine whether infection crosses species and spreads. The book accurately resists a single-cause account.
Zoonotic RNA viruses are a well-grounded high-risk class, and SARS-CoV-2 made the forecast look prescient. Pandemic probability spans many agents, however, and a correct class-level warning does not identify a specific virus, timing, or pathway.
What this number means. It is an AI-generated first-pass judgment of three central factual or causal claims—not a rating, exhaustive fact-check, or human peer review. Claim credits are 100% for supported, 75% for mostly supported, 50% for mixed, and 25% for weak, then averaged and rounded. Lower confidence means the score should move more as better evidence arrives.
Method three-central-claims/0.1.0 · checked 2026-09-01 · 3/3 selected claims assessed · method and source audit