Nonlinear effects of noise on outbreaks of mosquito-borne diseases

Mosquito-borne diseases are a significant and growing public health burden globally. Predictions about the future spread and impact of mosquito-borne disease outbreaks can help inform direct control and prevention measures. However, climate change is expected to increase weather variability, which may shape the future of mosquito-borne disease outbreaks globally. In this study, we sought to determine the effects of demographic and environmental noise (stochasticity) on the duration and size of outbreaks predicted by models of mosquito-borne disease. We developed a demographically and environmentally stochastic Ross-Macdonald model to assess how noise affects the probability of an outbreak, the peak number of cases, and the duration of outbreaks at increasing levels of the basic reproduction number (R0) and environmental noise strength. Increasing environmental noise lowers the risk of endemic disease from 100% down to almost 0%, but the largest outbreaks occur at intermediate environmental noise levels. In this case, if an outbreak dies out, it ends quickly. With noise present, R0 alone is insufficient to predict definitively whether an outbreak occurs. Surprisingly, our model suggests that increasing environmental noise may reduce the risk of endemic disease and epidemics due to more frequent extreme conditions dramatically affecting mosquito populations. Author SummaryClimate change is expected to cause drastic changes in the spread of mosquito-borne disease outbreaks, both in where they occur and in their size. A key aspect of climate change is an increase in the variability of weather factors, such as rainfall and temperature, factors that also play a crucial role in mosquito survival and reproduction. We created a mathematical model to help us understand how increases in variability might affect mosquito-borne disease outbreaks in the future. Results from our modeling suggest that, depending on current levels, future increases in environmental variability could either increase or decrease the size of future outbreaks. Our work highlights the need to better understand the connections between environmental changes and mosquito biology to inform efforts to forecast and suppress mosquito outbreaks.