Handbook of Spatial Epidemiology
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Handbook of Spatial Epidemiology

Handbook of Spatial Epidemiology

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About the Book

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.

Table of Contents:
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


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Product Details
  • ISBN-13: 9780367570385
  • Publisher: Taylor & Francis Ltd
  • Publisher Imprint: Chapman & Hall/CRC
  • Height: 254 mm
  • No of Pages: 702
  • Width: 178 mm
  • ISBN-10: 0367570386
  • Publisher Date: 30 Jun 2020
  • Binding: Paperback
  • Language: English
  • Weight: 1250 gr


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