Climate Predicts Geographic and Temporal Variation in Mosquito-Borne Disease Dynamics on Two Continents

• Published in: Nature communications Vol. 12; no. 1; pp. 1233 - 13
• Main Authors: Caldwell, Jamie M, LaBeaud, A Desiree, Lambin, Eric F, Stewart-Ibarra, Anna M, Ndenga, Bryson A, Mutuku, Francis M, Krystosik, Amy R, Ayala, Efraín Beltrán, Anyamba, Assaf, Borbor-Cordova, Mercy J, Damoah, Richard, Grossi-Soyster, Elysse N, Heras, Froilán Heras, Ngugi, Harun N, Ryan, Sadie J, Shah, Melisa M, Sippy, Rachel, Mordecai, Erin A
• Format: Journal Article
• Language: English
• Published: Goddard Space Flight Center Nature Research 23.02.2021; Nature Publishing Group UK; Nature Publishing Group; Nature Portfolio
• Subjects: 631/158; 631/158/1144; 631/158/1469; 631/158/2165; 692/699/255; Aedes aegypti; Animals; Basic Reproduction Number; Calibration; Children; Climate Change; Climate effects; Climate models; Climate prediction; Context; Culicidae - physiology; Dengue fever; Disease; Disease Outbreaks; Dynamics; Ecuador - epidemiology; Epidemics; Geography; Humanities and Social Sciences; Humans; Infectious diseases; Kenya - epidemiology; Laboratories; Life Sciences (General); Meteorology and Climatology; Models, Biological; Mosquitoes; multidisciplinary; Natural populations; Nonlinear Dynamics; Outbreaks; Population dynamics; Science; Science (multidisciplinary); Socioeconomic Factors; Spatio-Temporal Analysis; Temporal variations; Time Factors; Vector Borne Diseases - epidemiology; Vector Borne Diseases - transmission; Vector-borne diseases; Vectors; Viruses; Kenya; Ecuador; Infectious Diseases; Ecological Modelling; Ecology; Climate-Change Ecology; Ecological Epidemiology
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-021-21496-7

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.