Susceptible host availability modulates climate effects on dengue dynamics. (10th December 2020)

• Record Type: Journal Article
• Authors: Nova, Nicole; Deyle, Ethan R.; Shocket, Marta S.; MacDonald, Andrew J.; Childs, Marissa L.; Rypdal, Martin; Sugihara, George; Mordecai, Erin A.
• Editors: Coulson, Tim
• Is Part Of: Ecology letters. Volume 24:Number 3(2021)
• Page Start: 415
• Page End: 425
• Publication Date: 2020-12-10
• Subjects: Arbovirus -- climate -- dengue -- empirical dynamic modelling -- forecasting -- rainfall -- susceptible population size -- temperature -- vector‐borne disease; Ecology -- Periodicals; 577
• DOI: 10.1111/ele.13652
• Languages: English
• ISSNs: 1461-023X

Abstract

Abstract: 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. Abstract : Detecting climate drivers and describing their effects on dengue incidence at the population level is challenging due to nonlinear and state‐dependent functional responses. We used long time series data, an inferred proxy for the susceptible population size, and empirical dynamic modelling to capture temperature and rainfall effects on dengue incidence in San Juan, Puerto Rico, which arose only when susceptible availability was above a certain threshold.