Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Third Edition

Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Third Edition provides an up-to-date and comprehensive account of Bayesian disease mapping methods and applications, covering conventional areas such as relative risk estimation, clustering, spatial survival analysis, and longitudinal analysis, as well as more recent developments. It is aimed at public health specialists, epidemiologists, and biostatisticians who need to work with geo-referenced health data.

Format: Paperback / softback
Length: 488 pages
Publication date: 31 March 2021
Publisher: Taylor & Francis Ltd

Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Third Edition is a comprehensive and up-to-date guide to Bayesian disease mapping methods and applications. Since the publication of the second edition, numerous new Bayesian tools and methods have been developed for space-time data analysis, predictive modeling of health outcomes, and other spatial biostatistical areas. This book covers a wide range of topics, including relative risk estimation, clustering, spatial survival analysis, longitudinal analysis, putative hazard modeling, analysis of multiple scales and multiple diseases, spatial survival and longitudinal studies, spatiotemporal methods, and map surveillance. It provides an up-to-date, cohesive account of the full range of Bayesian disease mapping methods and applications.

The book begins with an introduction to Bayesian inference, computation, and model assessment. It then focuses on important themes, such as disease map reconstruction, cluster detection, regression and ecological analysis, putative hazard modeling, analysis of multiple scales and multiple diseases, spatial survival and longitudinal studies, spatiotemporal methods, and map surveillance. The target audience for this text is public health specialists, epidemiologists, and biostatisticians who need to work with geo-referenced health data.

One of the key strengths of Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Third Edition is its emphasis on practical applications. The book provides numerous examples and case studies to illustrate the techniques and their real-world applications. It also includes a comprehensive set of references and resources for further reading.

In addition to its practical applications, Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Third Edition also provides a theoretical foundation for Bayesian disease mapping. The book covers topics such as prior distributions, likelihood functions, and model selection. It also discusses the challenges associated with Bayesian disease mapping, such as model complexity, convergence, and sensitivity analysis.

Overall, Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Third Edition is a valuable resource for anyone who works with geo-referenced health data. It provides a comprehensive and up-to-date guide to Bayesian disease mapping methods and applications, and it is suitable for public health specialists, epidemiologists, and biostatisticians of all levels of experience.

Weight: 903g
Dimension: 234 x 156 (mm)
ISBN-13: 9780367781224
Edition number: 3 New edition