The Public Life of Havana Syndrome: An Infodemiological Analysis of Attention, Publication, and Policy Signals for Anomalous Health Incidents, 2016–2026

Anomalous Health Incidents (AHIs), the unexplained sensory and neurological complaints widely known as Havana syndrome, have drawn nearly a decade of contested commentary without a disciplined account of how the topic has traveled through the public record. The problem is not a shortage of attention but a shortage of measurement: because no verified global incidence registry, validated case definition, or population denominator exists publicly, counting affected people from open data is impossible. This study therefore described and modeled the publication, news-coverage, pageview, search-interest, and administrative footprint of AHIs from 2016 through 2026, never their incidence or prevalence. Sixteen public sources requiring no registration, fee, or login were assembled into monthly and annual panels. Screening reduced 446 scholarly records to 77 unique works; the Global Database of Events, Language, and Tone (GDELT) supplied 13,511 articles across 118 months; and relative search volume peaked at 100 in August 2021. The design paired joinpoint regression, interrupted time-series (ITS) segmented regression at six prespecified events, prewhitened cross-signal analysis, and a sensitivity battery. After an independent post-audit, the scholarly corpus grew at an annual percent change of +44.59%, 95% CI [23.39, 69.43], while attention series climbed faster, the Wikipedia pageview rate reaching an average annual percent change of +56.52%. Attention signals were tightly coupled (search and pageviews at r = .981) yet weakly tied to scholarship, and 63 of 64 Granger tests were null after correction, leaving one fragile lag. The 2024 clinical studies produced the largest attention surge despite null imaging. The public life of Havana syndrome is thus an event-driven information-environment phenomenon on a clock distinct from disease and evidence.