Severe Droughts and the Tuberculosis and HIV Care Cascade in the Brazilian Amazon (2001–2024): Code and Derived Data for Bayesian Interrupted Time-Series Analyses

Analysis code and derived (aggregated) datasets supporting the manuscript: “Severe Droughts and the Tuberculosis and HIV Care Cascade in the Brazilian Amazon: A Bayesian Structural Interrupted Time Series Analysis of 24 Years of Surveillance Data.”We quantified drought-associated disruptions in primary-care consultations and the tuberculosis (TB) and HIV care cascades across Amazonas state (Brazil), using interrupted time-series models with basin-level partial pooling. Severe drought episodes were defined by hydrometeorological criteria (relative maximum cumulative water deficit [rMCWD] < −2·0 or monthly river discharge ≤ 5th historical percentile), with a two-month immediate post-drought window to capture lagged operational impacts.