"Epidemiology and Geography. Principles, Methods and Tools of Spatial Analysis." by Marc Souris, Ph.D.
Department of Microbiology & Immunology
Division of Biomedical Graduate Research Organization
School of Medicine, Georgetown University
|Figure 1. Book cover.|
This book is undoubtedly one of the primary tools necessary for One Health's fundamentally multidisciplinary approaches.
Health phenomena are rarely distributed randomly in space; a health phenomenon very often involves risk factors linked to geographic factors, mesological factors, and spatial relationships between individuals. Using localization is therefore fundamental in the analysis and understanding of health phenomena and their mechanisms. By taking into account the spatial relationships and interactions between the actors of the disease, spatial analysis makes this possible to better identify and understand the mechanisms and the processes underlying emerging or epidemic events. Spatial analysis makes it possible to consolidate "classic" epidemiology to feed research and parameterization of models.
Dr. Marc Souris' book offers an overview of spatial analysis and geographic information systems for health, focusing on the study of health-environment relationships. The book is constructed as a practical introduction to spatial and spatial-temporal analysis for the epidemiology and geography of health. The objectives, concepts, and many methods and techniques available in the domain is detailed with an educational approach which is illustrated by concrete examples.
This book establishes a rich state-of-the-art of the methods and tools of spatial analysis used today in epidemiology and in health geography, whether for scientific research or policy development studies. Such presentation includes among others: cartographic analysis, highlighting the geometrical and spatial-temporal characteristics of epidemics, the analysis of the spatial variability of the epidemiological patterns, the search for case aggregates, the search for environmental correlations, the search for statistical models including the spatial relationships between individuals, the search for scales of analysis and spatial structures, the analysis of spatial health disparities, etc.
This educational presentation balances the theoretical aspects, the methodological aspects, and the practical elements relating to the software being used. The methods are presented with a lot of pedagogy through simply formulated questions which they allow to be answered, and which are illustrated by concrete examples from the numerous works of the author. The work includes easy and accessible summaries at the end of the chapter, numerous illustrations, a glossary, bibliography and detailed practical cases which make working the book easy and enjoyable.
The introductory chapter sets the principles and concepts of a systems approach to health, the concept of risk in this context, then the different disciplines using the presented methods and tools. Chapter 2 presents in detail the principles of spatial analysis for epidemiology and the knowledge necessary to understand the methods stated, particularly in epidemiology and statistics. Chapter 3 recalls the principles of spatialization of data in epidemiology and presents the different sources of localized data used in epidemiology and health geography. Chapter 4 presents the data visualization methods and tools used in the health field. Chapter 4 also shows how to use mapping and errors to avoid when representing data. Chapter 5 details the main methods used to analyze the spatial distribution of health events: position, extent, centrality, autocorrelation, spatial relationships between two phenomena, cluster search, analysis around a source point, etc. Chapter 6 describes the methods used for spatial risk analysis including "classic" statistical methods used in epidemiology with aggregated data and rates, and environmental data obtained through Geographic Information Systems. Chapter 7 presents spatial temporal analyzes and spatialized modeling like cluster determination, autocorrelation, modeling, and simulation of epidemic processes.
Dr. Souris’ writing is ideal for everyone in the public or veterinary health who wish to find a summary of the broad subject of spatial analysis without being overburdened by excessive mathematics or statistics. This book is a valuable resource for anyone wishing to familiarize themselves with spatial analysis methods, whatever the field of application and in particular the use/understanding of Geographical information System applied to the One Health approach.
Below are two examples of the use of spatial and temporal analysis (kindly provided by Dr. Souris).
Figure 2: Spatial analysis of diabetes in France (1997). Spatial association between districts (Blue circles are “cold spots” (weak values surrounded by weak values), Red circles are “hot spots” (strong values surrounded by strong values). The not statistically significant associations are represented by a rhomboid point.
Figure 3: Spatial-temporal analysis of forest workers mobility and the risk of malaria exposure in Cambodia. Using GPS tracking of movements of forest workers (Mondolkiri district, Cambodia) allows the calculation of the time spent for each individual in a place and its exposure to various environments, and the calculation of correlation between exposure and malaria incidence among these workers. It also allows the characterization of the most crowded (Dark blue) passage places.