Rethinking malaria seasonality: humidity-driven transmission shifts and emerging hotspots in Zambia (2009–2023)

Abstract

Climate variability is increasingly altering the distribution and seasonality of malaria in Africa, yet evidence to guide climate-informed control strategies remains limited. Despite having previously been on course for elimination, Zambia has experienced a resurgence of malaria cases alongside intensifying weather events, underscoring the urgency of adapting interventions to shifting transmission dynamics. An ecological time-series analysis was conducted using 15 years (2009–2023) of district-level malaria surveillance data from the National Malaria Elimination Centre, together with meteorological and satellite derived climate data from the Zambia Meteorological Department. Spatial hotspot analysis, Spearman correlation, vector autoregressive modeling, Granger-causality tests, forecast error variance decomposition and seasonal autoregressive integrated moving average (SARIMA) models were used to examine climate-malaria relationships and forecast malaria incidence through 2030. Malaria incidence increased despite intensified control interventions, with a marked geographic shift from historically high-burden provinces (Luapula, Northern, Eastern) toward emerging hotspots in Northwestern, Copperbelt, and Western provinces. The transmission season extended from the previous traditional January-April peak to December–June, reflecting more extended periods of conducive climatic conditions. Forecasting analyses suggest that, if historical climate–malaria relationships persist, malaria incidence will continue increasing through 2030, with relative humidity remaining the strongest climatic predictor (p<0.001). Malaria transmission in Zambia persists, becoming more prolonged, spatially dynamic, and increasingly climate-sensitive. Integrating real-time climate surveillance, adaptive geographical targeting of malaria interventions and climate informed deployment of malaria vaccines into malaria programming could strengthen elimination efforts and build resilience in climate-vulnerable settings.