When a formerly rare pathogen emerges to cause a pandemic, it is critical to understand the ecology of the disease dynamics and its potential effects on disease control. Here, we take advantage of newly available experimental data to parameterize a temperature-dependent dynamical model of Zika virus (ZIKV) transmission, and analyze the effects of temperature variability and the parameters related to control strategies on ZIKV R  and the total disease burden (i.e., total number of human cases). Sensitivity analyses identified that R  and disease burden were largely driven by different parameters, with the exception of temperature, which is the dominant driver of epidemic dynamics in the models. Our estimate of R  had a single optimum temperature (≈ 30° C, comparable to recently published results (≈ 29°) [[1][1]]. However, the total number of human cases (“disease burden”) is maximized across a wider temperature range, from 24 to 36°C. The models indicate that the disease is highly sensitive to seasonal temperature variation. For example, although the model predicts that Zika transmission cannot occur at a constant temperature of 22°C, with seasonal variation of 5°C around a mean of 22°C, the model predicts a larger epidemic than what would occur at a constant 30°C, the temperature predicted to maximize R . This suggests that the potential geographic range of Zika is wider than indicated from static R  models, underscoring the importance of climate dynamics and variation on emerging infectious diseases. [1]: #ref-1

Effects of Temperature on Zika Dynamics and Control