Hydroclimatic extremes indexed by SPI and malaria case dynamics in Oyo State, Nigeria: evidence for lagged, site-specific effects.

Climate change significantly impacts human health through extreme weather events such as heat waves and meteorological droughts, which increase vulnerability to various malaria diseases. This study examined drought-temperature influences on malaria incidence in Saki and Sepeteri, Oyo State, Southwest Nigeria, using monthly climate and health data from 2013 to 2023. Drought conditions were characterized using standardized precipitation indices (SPI-1, SPI-3, and SPI-12), and associations with malaria were analyzed using regression models accounting for seasonality and temporal lags. Malaria transmission was strongly seasonal, peaking during July-November, with mean monthly cases reaching 1,134 in Saki and 869 in Sepeteri. In Saki, long-term moisture availability significantly increased malaria incidence, with a one-unit increase in SPI-12 associated with a 267% rise in cases (β = 1.299, p = 0.011). This effect was significantly moderated by temperature (β = -0.049, p = 0.011), and 1-2 month lagged climate models substantially improved predictive performance (ΔAIC ≈ 47-59). In Sepeteri, SPI-3 lagged models improved model fit (ΔAIC ≈ 45-50), though interaction effects were not statistically significant. These findings highlight non-linear, location-specific drought-malaria dynamics and support integrating lagged drought and temperature indicators into malaria early-warning systems.