Climate predicts geographic and temporal variation in mosquito-borne disease dynamics on two continents

Climate influences population dynamics via multiple mechanisms that can yield context-dependent effects in natural systems. For climate-sensitive arboviral diseases (dengue, chikungunya, Zika), climate has been observed to have opposing effects across settings. The authors show that a mechanistic SEI-SEIR model parameterized with laboratory-derived climate effects on Aedes aegypti physiology reproduces three key epidemic characteristics across distinct settings in Ecuador and Kenya: number, timing, and duration of outbreaks. The model yields dynamics consistent with observed Aedes aegypti abundances and laboratory-confirmed incidence with variable accuracy (28–85% for vectors, 44–88% for incidence). Predictive skill for vectors was higher in sites with fewer young children, lower mean temperatures, and greater prevalence of piped water and cement housing. Models with limited calibration that robustly represent climate–virus relationships can inform interventions and projections under climate change.