Jean-Francois Guégan, UMR 2724 IRD-CNRS-University of Montpellier, and French High School of Public Health, Franck Prugnolle, UMR 2724 IRD-CNRS-University of Montpellier, and Frédéric Thomas, UMR 2724 CNRS-IRD-University of Montpellier, and University of Montréal.
Background/Question/Methods What determines the number of infectious diseases species in a local human community? Do we observe more species of infectious diseases in human communities living in the tropics than those located in more temperate areas? Why are some human infectious diseases extremely rare when others are very common on Earth? These very basic questions, which are identical to those posed by ecologists working on plant and animal communities, have in some way little to do with small-scale processes, but on the contrary need that we explore large-scale phenomena. Because studies have focused too largely in the past on small spatial scales, answers to these questions have only recently received some attention with the development of macroecological studies in human epidemiology. In this presentation, we will review the main large-scale patterns that may help today to understand the geographical distribution of human infectious diseases.
Results/Conclusions Here we draw attention to the now-most popular macroecological patterns in the species richness of infections diseases in humans, e.g. species-area relationship, species-isolation relationship, local-regional richness relationship, species-latitude relationship. A specific attention is given to the importance in characterizing such macro-scale patterns and their linkages with new emerging diseases. We discuss further on the latitudinal gradient in human species richness and its role in both the ecology and biogeography of infectious disease and the evolution of human species. This work highlighting an emerging macroecological approach to human disease is then discussed within the general framework of global change during with which some of these biogeographical patterns could progressively vanish.
