702 Pages
    by Chapman & Hall

    702 Pages 129 B/W Illustrations
    by Chapman & Hall

    Handbook of Spatial Epidemiology explains how to model epidemiological problems and improve inference about disease etiology from a geographical perspective. Top epidemiologists, geographers, and statisticians share interdisciplinary viewpoints on analyzing spatial data and space–time variations in disease incidences. These analyses can provide important information that leads to better decision making in public health.

    The first part of the book addresses general issues related to epidemiology, GIS, environmental studies, clustering, and ecological analysis. The second part presents basic statistical methods used in spatial epidemiology, including fundamental likelihood principles, Bayesian methods, and testing and nonparametric approaches. With a focus on special methods, the third part describes geostatistical models, splines, quantile regression, focused clustering, mixtures, multivariate methods, and much more. The final part examines special problems and application areas, such as residential history analysis, segregation, health services research, health surveys, infectious disease, veterinary topics, and health surveillance and clustering.

    Spatial epidemiology, also known as disease mapping, studies the geographical or spatial distribution of health outcomes. This handbook offers a wide-ranging overview of state-of-the-art approaches to determine the relationships between health and various risk factors, empowering researchers and policy makers to tackle public health problems.

    Part I: Introduction
    Chapter 1: Integration of Different Epidemiologic Perspectives and Applications to Spatial Epidemiology
    Sara Wagner Robb, Sarah E. Bauer, John E. Vena
    Chapter 2: Environmental Studies
    Mark J. Nieuwenhuijsen
    Chapter 3: Interpreting Clusters of Health Events
    Geoffrey Jacquez, Jared Aldstadt
    Chapter 4: Geographic Information Systems in Spatial Epidemiology and Public Health
    Robert Haining, Ravi Maheswaran
    Chapter 5: Ecological Modeling: General Issues
    Jon C. Wakefield, Theresa R. Smith

    Part II: Basic Methods
    Chapter 6: Case Event and Count Data Modeling
    Andrew B. Lawson
    Chapter 7: Bayesian Modeling and Inference
    Georgiana Onicescu, Andrew B. Lawson
    Chapter 8: Statistical Tests for Clustering and Surveillance
    Peter A. Rogerson, Geoffrey Jacquez
    Chapter 9: Scan Tests
    Inkyung Jung
    Chapter 10: Kernel Smoothing Methods
    Martin L. Hazelton

    Part III: Special Methods
    Chapter 11: Geostatistics in Small-Area Health Applications
    Patrick E. Brown
    Chapter 12: Splines in Disease Mapping
    Tomás Goicoa, Jaione Etxeberria, and María Dolores Ugarte
    Chapter 13: Quantile Regression for Epidemiological Applications
    Brian J. Reich
    Chapter 14: Focused Clustering: Statistical Analysis of Spatial Patterns of Disease around Putative Sources of Increased Risk
    Lance A. Waller, David C. Wheeler, Jeffrey M. Switchenko
    Chapter 15: Estimating the Health Impact of Air Pollution Fields
    Duncan Lee, Sujit K. Sahu
    Chapter 16: Data Assimilation for Environmental Pollution Fields
    Howard H. Chang
    Chapter 17: Spatial Survival Models
    Sudipto Banerjee
    Chapter 18: Spatial Longitudinal Analysis
    Andrew B. Lawson
    Chapter 19: Spatiotemporal Disease Mapping
    Andrew B. Lawson, Jungsoon Choi
    Chapter 20: Mixtures and Latent Structure in Spatial Epidemiology
    Md. Monir Hossain and Andrew B. Lawson
    Chapter 21: Bayesian Nonparametric Modeling for Disease Incidence Data
    Athanasios Kottas
    Chapter 22: Multivariate Spatial Models
    Sudipto Banerjee

    Part IV: Special Problems and Applications
    Chapter 23: Bayesian Variable Selection in Semiparametric and Nonstationary Geostatistical Models: An Application to Mapping Malaria Risk in Mali
    Federica Giardina, Nafomon Sogoba, Penelope Vounatsou
    Chapter 24: Computational Issues and R Packages for Spatial Data Analysis
    Marta Blangiardo, Michela Cameletti
    Chapter 25: The Role of Spatial Analysis in Risk-Based Animal Disease Management
    Kim B. Stevens, Dirk U. Pfeiffer
    Chapter 26: Infectious Disease Modelling
    Michael Höhle
    Chapter 27: Spatial Health Surveillance
    Ana Corberán-Vallet and Andrew B. Lawson
    Chapter 28: Cluster Modeling and Detection
    Andrew B. Lawson
    Chapter 29: Spatial Data Analysis for Health Services Research
    Brian Neelon
    Chapter 30: Spatial Health Survey Data
    Christel Faes, Yannick Vandendijck, Andrew B. Lawson
    Chapter 31: Graphical Modeling of Spatial Health Data
    Adrian Dobra
    Chapter 32: Smoothed ANOVA Modeling
    Miguel A. Martinez-Beneito, James S. Hodges, and Marc Marí-Dell’Olmo
    Chapter 33: Sociospatial Epidemiology: Segregation
    Sue C. Grady
    Chapter 34: Sociospatial Epidemiology: Residential History Analysis
    David C. Wheeler, Catherine A. Calder
    Chapter 35: Spatiotemporal Modeling of Preterm Birth
    Joshua L. Warren, Montserrat Fuentes, Amy H. Herring, Peter H. Langlois


    Andrew B. Lawson is a professor of biostatistics in the Division of Biostatistics, Department of Public Health Sciences, College of Medicine at the Medical University of South Carolina (MUSC). He is an MUSC eminent scholar and American Statistical Association (ASA) fellow. He is also an advisor in disease mapping and risk assessment for the World Health Organization, the founding editor of the journal Spatial and Spatio-Temporal Epidemiology, and the author of eight books, including the highly regarded Chapman & Hall/CRC book Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Second Edition. He has published more than 150 journal articles on spatial epidemiology, spatial statistics, and related areas. He earned a PhD in spatial statistics from the University of St. Andrews.

    Sudipto Banerjee is a professor and chair in the Department of Biostatistics at the University of California, Los Angeles. He is an elected fellow of the ASA, the Institute of Mathematical Statistics, and the International Statistical Institute. He is also a recipient of the Mortimer Spiegelman Award from the American Public Health Association. He is the author/coauthor of more than 100 peer-reviewed publications and two highly regarded Chapman & Hall/CRC books: Hierarchical Modeling and Analysis for Spatial Data, Second Edition and Linear Algebra and Matrix Analysis for Statistics. His research interests include hierarchical modeling and Bayesian inference for spatially referenced data.

    Robert Haining retired as a professor of human geography from the University of Cambridge in September 2015. He is the author/coauthor of more than 150 articles and two books. His research focuses on the quantitative analysis of geographical data, including the geography of health, spatial representation, spatial sampling, exploratory data analysis, small-area estimation and hypothesis testing, spatial data analysis, and spatial econometrics. His past work has involved the evaluation of the impact of air pollution on health status using small-area statistics as well as the development of new methods for evaluating the effectiveness of small-area targeted police interventions.

    María Dolores Ugarte is a professor of statistics at the Public University of Navarre. She is the author/coauthor of many papers on statistics and epidemiology and several books, including the recent Chapman & Hall/CRC book Probability and Statistics with R, Second Edition. She is also an associate editor for Statistical Modelling, TEST, and Computational Statistics and Data Analysis as well as an editorial panel member of Spatial and Spatio-Temporal Epidemiology. Her research focuses on spatiotemporal disease mapping and small-area estimation with applications in several fields. She earned a PhD in statistics from the Public University of Navarre.

    "In 2008, CRC Press started publishing the Handbooks of Modern Statistical Methods. Apparently the series is popular as it is growing rapidly, with 13 volumes printed now and 7 announced. It is easy to understand why: the books are attractive in content, presentation and price. The present volume is no exception. The book has been edited by first-class experts, who also contributed a number of chapters. The book’s website gives a table of the contents of the 35 chapters. It documents the rich variety of subjects. … I can only recommend this book."
    —Paul Eilers, ISCB News, May 2017