Risk Mapping and Mathematical Modelling:Assessment Tools for the Impact of Climate Change on Infectious Diseases

Abstract

There is now near undisputed scientific consensus that the rise in atmospheric concentration of greenhouse gases causes warming at the Earth¿s surface. Global warming will also have impacts on human health. We focus here on vector-borne infectious diseases because climatic variables are major determinants of the geographical distribution of the cold-blooded insect and tick species that can transmit viruses, bacteria and other microparasites to humans. The distribution of vectors is thus one important component of infection risk. We review the methods that have been developed in the past few years to determine and to model the distribution of species under actual and hypothetical environmental conditions and show how mathematical models have been used in this context. Remote sensing technology offers progressively better environmental and climatic data which can be employed in conjunction with Geographic Information Systems (GIS) and spatial statistical techniques to determine the distribution of vector species under different scenarios. Mathematical models can help to elucidate many aspects of infectious disease dynamics. The available studies lead to the expectation that climate change affects the transmission dynamics of vector-borne infectious diseases. However, the details and the degree of these effects are very uncertain. In order to predict more reliably the effects of extreme climate variability or climate change on infectious disease dynamics more data on the interaction between ecological, epidemiological, economical and social processes are needed.