Bridging surveillance gaps in dengue: a hierarchical model integrating mixed data sources for transmission estimation and vaccine targeting
This study presents a Bayesian hierarchical model that integrates mixed surveillance data and seroprevalence surveys to accurately estimate dengue transmission dynamics and identify high-priority districts for vaccination in Indonesia, revealing that reliance on reported incidence alone often underestimates risk in areas with weak surveillance.