Influence of climate variability and seasonal trends on malaria incidence in Dar es Salaam, Tanzania using generalized additive models.

While malaria transmission in coastal East Africa is strongly shaped by climatic variability, few studies examine long-term interactions in rapidly urbanizing settings. This study evaluated the impact of climate and seasonal trends on malaria incidence in Dar es Salaam, Tanzania (2014-2024). Monthly cases and meteorological data were analyzed using seasonal-trend decomposition (STL) and generalized additive models (GAMs) to quantify nonlinear and lagged climatic associations. Over the decade, malaria incidence declined sharply from >130 cases per 10,000 in 2014 to <30 by 2023. However, strong seasonal peaks persisted, with STL revealing consistent annual surges during April-June following the rainy season. GAM analysis identified rainfall as the dominant climatic driver, demonstrating significant 1- and 2-month lagged effects (p < 0.001). Daytime (1-month lag) and night-time (2-month lag) temperatures showed non-linear associations, peaking in incidence at optimal mosquito-development temperatures (~30-31°C). Despite substantial incidence declines, transmission remains highly climate-sensitive. Driven primarily by lagged rainfall and temperature effects rather than current-month conditions, these dynamics underscore the urgent need for climate-informed early warning systems and targeted seasonal interventions in coastal urban environments.