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

Climate drives population dynamics, but when the underlying mechanisms are unresolved, studies can lead to seemingly contradictory effects of climate on natural populations. Climate-sensitive vector-borne diseases such as dengue, chikungunya, and Zika are one example where climate appears to have opposing effects in different contexts. In this study, we use a mathematical model to directly connect climate-driven mosquito physiology measured in laboratory studies to observed vector and disease dynamics in the field across ecologically and culturally distinct settings in Ecuador and Kenya. We show that temperature, rainfall, and humidity predict Aedes aepgyti abundances and laboratory-confirmed arboviral incidence across ecologically distinct settings. Further, this trait-based approach resolves seemingly contradictory results from prior field studies and highlights climate conditions where mechanisms remain unresolved. Using this mechanistic model, we tested several intervention strategies and found that reducing immature mosquito habitat or contact rate between mosquitoes and humans are more effective interventions than killing adult mosquitoes. These results can help guide intervention efforts and improve climate change predictions for vector-borne diseases.