Spatio-Temporal Methods in Environmental Epidemiology

Gavin Shaddick, James V. Zidek

June 24, 2015 by Chapman and Hall/CRC
Textbook - 395 Pages - 52 Color Illustrations
ISBN 9781482237030 - CAT# K23149
Series: Chapman & Hall/CRC Texts in Statistical Science


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  • Explores the interface between environmental epidemiology and spatio-temporal modeling
  • Incorporates many examples that illustrate how spatio-temporal methodology can be used to inform real societal concerns related to the effects of environmental hazards on health
  • Uses the Bayesian approach as an important unifying framework for the integration of spatio-temporal modeling into environmental epidemiology
  • Discusses current research topics, including visualization and mapping, high-dimensional data analysis, the design of monitoring networks, and the effects of preferential sampling
  • Provides details on using specific R packages; other software, including WinBUGS/OpenBUGS; and modern computational methods, such as INLA
  • Includes a summary and exercises at the end of each chapter
  • Offers code, data, examples, course information, and more on a supplementary website

Figure slides are available upon qualifying course adoption.


Teaches Students How to Perform Spatio-Temporal Analyses within Epidemiological Studies

Spatio-Temporal Methods in Environmental Epidemiology is the first book of its kind to specifically address the interface between environmental epidemiology and spatio-temporal modeling. In response to the growing need for collaboration between statisticians and environmental epidemiologists, the book links recent developments in spatio-temporal methodology with epidemiological applications. Drawing on real-life problems, it provides the necessary tools to exploit advances in methodology when assessing the health risks associated with environmental hazards. The book’s clear guidelines enable the implementation of the methodology and estimation of risks in practice.

Designed for graduate students in both epidemiology and statistics, the text covers a wide range of topics, from an introduction to epidemiological principles and the foundations of spatio-temporal modeling to new research directions. It describes traditional and Bayesian approaches and presents the theory of spatial, temporal, and spatio-temporal modeling in the context of its application to environmental epidemiology. The text includes practical examples together with embedded R code, details of specific R packages, and the use of other software, such as WinBUGS/OpenBUGS and integrated nested Laplace approximations (INLA). A supplementary website provides additional code, data, examples, exercises, lab projects, and more.

Representing a major new direction in environmental epidemiology, this book—in full color throughout—underscores the increasing need to consider dependencies in both space and time when modeling epidemiological data. Students will learn how to identify and model patterns in spatio-temporal data as well as exploit dependencies over space and time to reduce bias and inefficiency.


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