Spatial analysis for epidemiology and health geography

Faced with the evidence of multiple transmissions of diseases from animals to humans, an integrated, systemic approach has gradually become essential to better understand, assess and prepare for health risks: it is necessary to study diseases in their global context, taking into account not only potential patients, but also all the players involved in the emergence and spread of diseases. There are many such players: pathogens, human and animal populations, vectors, with biological, geographical, environmental, behavioral, social, economic and other risk factors.

Heterogeneity is the key to epidemiology, in the sense that uniform risk in observed data does not allow epidemiological differences to be associated with factors that might have etiological significance. Heterogeneity also concerns the spatial distribution of diseases: health phenomena are rarely randomly distributed in space, and their spatial distribution often reflects risk factors linked to geographical factors and proximity relationships between individuals, which make it possible to decipher them. Many processes depend on proximity, either through contamination or contagion processes, or through geographical causal relationships with environmental characteristics. The study of heterogeneity in the spatial distribution of health phenomena therefore proves to be important in the analysis and understanding of these phenomena and the identification of their risk factors: when risk varies from one place to another, geographical location is an important explanatory variable, either because it reflects an element of risk determined by the environment (be it an element of the natural or sociocultural environment associated with a place), or because people with similar risk characteristics live together, or because risk is linked to a process of contagion by proximity.

This article introduces the conceptual and methodological foundations underpinning spatial analysis in epidemiology, whose various methods and tools will be described in detail in the associated article [MED 4 002] . The two-dimensional nature of geographical location means that standard representation methods and statistical techniques for dealing with essentially univariate sets of variables need to be supplemented by more sophisticated methods. The term "spatial analysis" is thus used to describe analysis techniques, essentially statistical, that make use of geographical location. Spatial analysis of a health phenomenon mainly consists in...