Climate predicts geographic and temporal variation in mosquito-borne disease dynamics on two continents
Jamie M. Caldwell, A. Desirée LaBeaud, Éric F. Lambin, Anna M. Stewart‐Ibarra, Bryson Ndenga, Francis Mutuku, Amy Krystosik, Efraín Beltrán Ayala, Assaf Anyamba, Mercy J. Borbor‐Cordova, R. Damoah, Elysse N. Grossi-Soyster, Froilán Heras, Harun N. Ngugi, Sadie J. Ryan, Melisa M. Shah, Rachel Sippy, Erin A. Mordecai
Abstract
Climate drives population dynamics through multiple mechanisms, which can lead to seemingly context-dependent effects of climate on natural populations. For climate-sensitive diseases, such as dengue, chikungunya, and Zika, climate appears to have opposing effects in different contexts. Here we show that a model, parameterized with laboratory measured climate-driven mosquito physiology, captures three key epidemic characteristics across ecologically and culturally distinct settings in Ecuador and Kenya: the number, timing, and duration of outbreaks. The model generates a range of disease dynamics consistent with observed Aedes aegypti abundances and laboratory-confirmed arboviral incidence with variable accuracy (28-85% for vectors, 44-88% for incidence). The model predicted vector dynamics better in sites with a smaller proportion of young children in the population, lower mean temperature, and homes with piped water and made of cement. Models with limited calibration that robustly capture climate-virus relationships can help guide intervention efforts and climate change disease projections.