Susceptible host availability modulates climate effects on dengue dynamics

Experiments and models suggest that climate affects mosquito-borne disease transmission. However, disease transmission involves complex nonlinear interactions between climate and population dynamics, which makes detecting climate drivers at the population level challenging. By analysing incidence data, estimated susceptible population size, and climate data with methods based on nonlinear time series analysis (collectively referred to as empirical dynamic modelling), we identified drivers and their interactive effects on dengue dynamics in San Juan, Puerto Rico. Climatic forcing arose only when susceptible availability was high: temperature and rainfall had net positive and negative effects respectively. By capturing mechanistic, nonlinear and context-dependent effects of population susceptibility, temperature and rainfall on dengue transmission empirically, our model improves forecast skill over recent, state-of-the-art models for dengue incidence. Together, these results provide empirical evidence that the interdependence of host population susceptibility and climate drives dengue dynamics in a nonlinear and complex, yet predictable way.R35GM133439 - NIH HHS; DBI-1667584 - National Science Foundation; DEB-1655203 - National Science Foundation; 00028335 - Lenfest Foundation; Stanford University: Bing Fellowship in Honor of Paul Ehrlich, Stanford Data Science Scholars program, Lindsay Family E-IPER Fellowship, Illich-Sadowsky Interdisciplinary Graduate Fellowship, Terman Fellowship, King Center for Global Development seed grant; SERDP 15 RC-2509 - U.S. Department of Defense; University of California San Diego: McQuown Chair in Natural Sciences; DBI-1611767 - National Science Foundation; RAPID DEB-1640780 - National Science Foundation; R35GM133439 - NIH HHS; Hellman Foundation: Hellman Faculty Fellowship; Stanford Woods Institute for the Environment: Environmental Ventures Program; DEB-1518681 - National Science Foundation; R35 GM133439 - NIGMS NIH HHS; DEB-2011147 - National Science Foundationhttps://www.biorxiv.org/content/biorxiv/early/2020/10/19/2019.12.20.883363.full.pdfAccepted manuscrip