Spatio-temporal modelling of the risk of disease under climate change scenarios Seminar

Human health, and the security of our food, are widely perceived to be threatened by climate change's effects on infectious diseases of humans, animals and plants. While the risk appears to be real, predicting what might actually happen in the future is extremely difficult. A useful tool for investigating the future of certain climate-sensitive diseases is to link climate-driven disease models to the outputs of climate models. A suitable, generic model for many infectious diseases is known as the Basic Reproduction Ratio (R0), defined as the number of secondary infections arising from one newly infected individual introduced into a fully susceptible population; R0 then defines the risk of spread of the disease, the scale of the subsequent outbreak (if uncontrolled) and the effort required to control it. R0 can be defined mathematically, and some of the terms within its mathematical definition are determined by climatic variables. These climate-sensitive variables provide a link between the R0 disease model and models of climate change, thereby allowing the impact of future climates on disease-risk to be quantified, albeit with significant uncertainty. This framework is demonstrated for a recently-emerged disease of ruminant livestock called bluetongue. The results show that the recent emergence of the disease in Europe can be at least partly attributed to concurrent changes in temperature and rainfall; that the mechanisms by which climate has affected the disease differ between northern and southern Europe; and that there is consistency between climate models in projecting further increase in risk of the disease in Europe until at least 2050.