Detecting the impact of temperature on transmission of Zika, dengue, and chikungunya using mechanistic models

Abstract

Recent epidemics of Zika, dengue, and chikungunya have heightened the need to understand the seasonal and geographic range of transmission by Aedes aegypti and Ae. albopictus mosquitoes. We use mechanistic transmission models to derive predictions for how the probability and magnitude of transmission for Zika, chikungunya, and dengue change with mean temperature, and we show that these predictions are well matched by human case data. Across all three viruses, models and human case data both show that transmission occurs between 18-34°C with maximal transmission occurring in a range from 26-29°C. Controlling for population size and two socioeconomic factors, temperature-dependent transmission based on our mechanistic model is an important predictor of human transmission occurrence and incidence. Risk maps indicate that tropical and subtropical regions are suitable for extended seasonal or year-round transmission, but transmission in temperate areas is limited to at most three months per year even if vectors are present. Such brief transmission windows limit the likelihood of major epidemics following disease introduction in temperate zones.

Fig 1. Thermal responses of Ae. aegypti and DENV traits that drive transmission (data sources listed in Table B in S2 Text).

Informative priors based on data from additional Aedes spp. and flavivirus studies helped to constrain uncertainty in the model fits (see Materials and Methods; Table C in S2 Text). Points and error bars indicate the data means and standard errors (for display only; models were fit from the raw data). Black solid lines are the mean model fits; red dashed lines are the 95% credible intervals. Thermal responses for Ae. albopictus are shown in Fig A in S1 Text.

Fig 2. Relative R₀ across constant temperatures (°C; top) for Ae. albopictus (light blue) and Ae. aegypti (dark blue), and histograms of the posterior distributions of the critical thermal minimum (bottom left), temperature at peak transmission (bottom middle), and critical thermal maximum (bottom right; all in °C).

Solid lines: mean posterior estimates; dashed lines: 95% credible intervals. R₀ curves normalized to a 0–1 scale for ease of comparison and visualization.

Fig 3. Ae. aegypti R₀(T) and population size predict the probability and magnitude of transmission of DENV, CHIKV, and ZIKV across the Americas.

A, log(p)*GR₀ (the posterior probability that R₀(T) > 0 times the log of population size) versus the probability of local transmission in the data. B, log(p*R₀(T)) (log of R₀(T) times the population size) versus the log of incidence, given that it exceeds the threshold for local transmission. Tick-marks and points: human transmission occurrence and incidence data, respectively, by country-week in the Americas and Caribbean. Lines and shaded areas: mean and 95% CI from GLM fits for DENV (blue) and CHIKV and ZIKV (red). For simplicity, we show the models that only include the covariates log(p)*GR₀ or log(p*R₀(T)), respectively, and do not include the socioeconomic covariates (models PA6 and IM4 in Table D in S2 Text). For each case report data point, log(p)*GR₀ and log(p*R₀(T)) were calculated at the mean temperature 10 weeks prior to the reporting week [40].

Fig 4. Map of predicted temperature suitability for virus transmission by Ae. albopictus and Ae. aegypti.

Color indicates the consecutive months in which temperature is permissive for transmission (predicted R₀ > 0) for Aedes spp. transmission based on the minimum likely range (> 97.5% posterior probability that R₀ > 0). Black lines indicate the CDC estimated range for the two Aedes spp. in the United States. Model suitability predictions combine temperature mean and 8°C daily variation and are informed by laboratory data (Fig 1, Fig A in S1 Text) and validated against field data (Fig 3).