Between 2015 and 2017, Zika virus spread rapidly through populations in the Americas with no prior exposure to the disease. This provides an opportunity to characterize relationships between the environment, populations, and disease transmission without the confounding effects of pre-existing immunity. Specifically, we tested the hypothesis that climate drives variation in force of infection over time and space for an emerging vector-borne pathogen. To do so, we estimated force of infection for Zika over time and across provinces in Latin America using a time-varying Susceptible Infectious Recovered model. We examined variation in force of infection over time within provinces to understand how strongly climate predicts the probability of local transmission and the intensity of transmission. Then, to understand how climate and population factors shape epidemics geographically, we examined spatial variation in several epidemic metrics, including total human cases and force of infection.
Results/Conclusions
Surprisingly, climate factors explained less than 1% of the variation in force of infection over time, suggesting that week to week transmission within provinces may be too stochastic to predict. By contrast, climate and population factors explained 36-90% of the spatial variation in Zika presence, intensity, and duration among provinces. While humidity and temperature were the most important climate predictors of where Zika transmission occurred, rainfall, temperature range, and mean temperature were the best predictors of Zika intensity and duration, given that Zika was present. Unexpectedly, force of infection was greatest in locations with temperatures near 24°C, much lower than previous estimates from mechanistic models. This result potentially suggests that existing vector control programs and/or prior exposure to other mosquito-borne diseases may have limited transmission in locations most suitable for Aedes aegypti, the main vector of Zika, dengue, and chikungunya viruses in Latin America.