Book Review: Spatial Analysis in Epidemiology

place, however, has always been the most difficult and time consuming to analyze and illustrate [1]. In addition, the majority of data for demographic, socioeconomic, environmental pollution, and health outcomes have a common aspect; all of these data can be located within space as a point, line, or area [2]. Because where people live, work, learn, and play can affect their health and well-being, these location data are gaining momentum as an important part of epidemiology and can be assessed with advanced technology and analytic methods. Spatial analysis in epidemiology is a field dealing with spatial or spatiotemporal data, which can be linked to the phenomenon of disease spread or population at risk [3]. This book, Spatial Analysis in Epidemiology, consists of 8 chapters. Chapter 1 is an introduction to the concepts and framework for spatial analysis, available software, and the basics of spatial data by providing readers with many references, Web sites, and information sources. Chapter 2 dives into more detail about spatial data and spatial effects in conjunction with the geographic information system (GIS), such as data types, collection, and management. Especially for someone who is not familiar with GIS as a powerful tool for dealing with such spatial data, chapter 2 will be an essential read. Chapter 3 focuses on the visualization and representation of spatial data. Examples of geographical data were described as point data (e.g., disease cases, attribute values), aggregated data (e.g., total, mean, and median), and continuous data (e.g., temperature, air pollution). Chapters 4 and 5 introduce spatial clustering for disease at global and local levels, which is very useful for spatial aggregation of disease cases. These 2 chapters provide various methods and statistics dealing with aggregated and point data for spatial clustering that has great potential as an alarm system for disease clustering. Chapter 6 deals with spatial variations in risk, Spatial Analysis in Epidemiology