Susceptible host availability modulates climate effects on dengue dynamics
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.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Dec 10, 2020
- Source ID
- 10.1111/ele.13652
Entities
People
- Andrew MacDonald
- Erin A. Mordecai
- Ethan R Deyle
- George Sugihara
- Marissa L. Childs
- Marta S Shocket
- Martin Rypdal
- Nicole Nova
Organizations
- Boston University
- Hellman Foundation
- National Institutes of Health
- National Science Foundation
- Stanford University
- United States Department of Defense
- University of California
- University of California, San Diego
- University of California, Santa Barbara
- University of Tromsø – The Arctic University of Norway