Rethinking Malaria Seasonality: Humidity-Driven Transmission Shifts and Emerging Hotspots in Zambia (2009-2023)

BackgroundClimate variability is increasingly altering the distribution and seasonality of malaria in Africa, yet evidence to guide climate-resilient 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. MethodsAn ecological time-series analysis was conducted using 15 years (2009-2023) of district-level malaria surveillance data from the National Malaria Elimination Centre, climate data from the Zambia Meteorological Department, and satellite products. Monthly incidence was correlated with rainfall, temperature, and relative humidity using a structured additive semiparametric Poisson model accounting for spatial and temporal autocorrelation. Hotspots were detected with SATScan, and changes in seasonal transmission were analysed across three five-year periods. Forecast error variance decomposition and Granger-causality tests assessed the direction and strength of climatic variables influence on malaria trends. ResultsNational 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 traditional January-April peak to December-June, reflecting more extended periods of conducive climatic conditions. Relative humidity was the strongest and most consistent predictor of malaria incidence (p < 0.001), surpassing rainfall and temperature in explanatory power. Predictive models suggest that without enhanced interventions, rising temperatures and humidity will continue to drive increases in incidence through 2030. ConclusionsMalaria transmission in Zambia is becoming more prolonged, spatially dynamic, and increasingly climate sensitive. Integrating real-time climate surveillance, adaptive vector control and synchronised vaccine deployment into malaria programming could strengthen elimination efforts and build resilience in climate-vulnerable settings. Author SummaryUsing 15 years of national surveillance and climate data, this study provides new evidence that relative humidity, not rainfall or temperature, is the most consistent and powerful climatic predictor of malaria incidence in Zambia. We show that malaria transmission seasons are lengthening, spatial hotspots are shifting, and climate-sensitive drivers are amplifying risk in previously lower-burden areas. These findings challenge long-standing assumptions guiding malaria control strategies, including the timing of vector control and the rollout of new malaria vaccines. By identifying humidity as a key determinant of malaria risk, this analysis provides actionable insights for climate-resilient programming. It supports integrating real-time climate intelligence into elimination efforts across climate-vulnerable regions.