Climate change and vector-borne diseases of public health significance

Many invasive species that have been spread through the globalization of trade and travel are pathogens. A paradigmatic case is the introduction of West Nile virus (WNV) into North America in 1999. A decade of research on the ecology and evolution of WNV includes three findings that provide insight into the outcome of future pathogen introductions. First, WNV transmission in North America is highest in urbanized and agricultural habitats, in part because the hosts and vectors of WNV are abundant in human-modified areas. Second, after its introduction, the virus quickly adapted to infect local mosquito vectors more efficiently than the originally introduced strain. Third, highly focused feeding patterns of the mosquito vectors of WNV result in unexpected host species being important for transmission. This research provides a framework for predicting and preventing the emergence of foreign vector-borne pathogens.

The incidence of malaria in the East African highlands has increased since the end of the 1970s. The role of climate change in the exacerbation of the disease has been controversial, and the specific influence of rising temperature (warming) has been highly debated following a previous study reporting no evidence to support a trend in temperature. We revisit this result using the same temperature data, now updated to the present from 1950 to 2002 for four high-altitude sites in East Africa where malaria has become a serious public health problem. With both nonparametric and parametric statistical analyses, we find evidence for a significant warming trend at all sites. To assess the biological significance of this trend, we drive a dynamical model for the population dynamics of the mosquito vector with the temperature time series and the corresponding detrended versions. This approach suggests that the observed temperature changes would be significantly amplified by the mosquito population dynamics with a difference in the biological response at least 1 order of magnitude larger than that in the environmental variable. Our results emphasize the importance of considering not just the statistical significance of climate trends but also their biological implications with dynamical models.