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In the seventeenth century, a map of the plague suggested a radical idea—that the disease was carried and spread by humans. In the nineteenth century, maps of cholera cases were used to prove its waterborne nature. More recently, maps charting the swine flu pandemic caused worldwide panic and sent shockwaves through the medical community. In Disease Maps, Tom Koch contends that to understand epidemics and their history we need to think about maps of varying scale, from the individual body to shared symptoms evidenced across cities, nations, and the world. Disease Maps begins with a brief review of epidemic mapping today and a detailed example of its power. Koch then traces the early history of medical cartography, including pandemics such as European plague and yellow fever, and the advancements in anatomy, printing, and world atlases that paved the way for their mapping. Moving on to the scourge of the nineteenth century—cholera—Koch considers the many choleras argued into existence by the maps of the day, including a new perspective on John Snow’s science and legacy. Finally, Koch addresses contemporary outbreaks such as AIDS, cancer, and H1N1, and reaches into the future, toward the coming epidemics. Ultimately, Disease Maps redefines conventional medical history with new surgical precision, revealing that only in maps do patterns emerge that allow disease theories to be proposed, hypotheses tested, and treatments advanced.
Cartographies of Disease: Maps, Mapping, and Medicine, new expanded edition, is a comprehensive survey of the technology of mapping and its relationship to the battle against disease. This look at medical mapping advances the argument that maps are not merely representations of spatial realities but a way of thinking about relationships between viral and bacterial communities, human hosts, and the environments in which diseases flourish. Cartographies of Disease traces the history of medical mapping from its growth in the 19th century during an era of trade and immigration to its renaissance in the 1990s during a new era of globalization. Referencing maps older than John Snow's famous cholera maps of London in the mid-19th century, this survey pulls from the plague maps of the 1600s, while addressing current issues concerning the ability of GIS technology to track diseases worldwide. The original chapters have some minor updating, and two new chapters have been added. Chapter 13 attempts to understand how the hundreds of maps of Ebola revealed not simply disease incidence but the way in which the epidemic itself was perceived. Chapter 14 is about the spatiality of the disease and the means by which different cartographic approaches may affect how infectious outbreaks like ebola can be confronted and contained.
In the seventeenth century, a map of the plague suggested a radical idea—that the disease was carried and spread by humans. In the nineteenth century, maps of cholera cases were used to prove its waterborne nature. More recently, maps charting the swine flu pandemic caused worldwide panic and sent shockwaves through the medical community. In Disease Maps, Tom Koch contends that to understand epidemics and their history we need to think about maps of varying scale, from the individual body to shared symptoms evidenced across cities, nations, and the world. Disease Maps begins with a brief review of epidemic mapping today and a detailed example of its power. Koch then traces the early history of medical cartography, including pandemics such as European plague and yellow fever, and the advancements in anatomy, printing, and world atlases that paved the way for their mapping. Moving on to the scourge of the nineteenth century—cholera—Koch considers the many choleras argued into existence by the maps of the day, including a new perspective on John Snow’s science and legacy. Finally, Koch addresses contemporary outbreaks such as AIDS, cancer, and H1N1, and reaches into the future, toward the coming epidemics. Ultimately, Disease Maps redefines conventional medical history with new surgical precision, revealing that only in maps do patterns emerge that allow disease theories to be proposed, hypotheses tested, and treatments advanced.
Cartographies of Disease: Maps, Mapping, and Medicine, new expanded edition, is a comprehensive survey of the technology of mapping and its relationship to the battle against disease. This look at medical mapping advances the argument that maps are not merely representations of spatial realities but a way of thinking about relationships between viral and bacterial communities, human hosts, and the environments in which diseases flourish. Cartographies of Disease traces the history of medical mapping from its growth in the 19th century during an era of trade and immigration to its renaissance in the 1990s during a new era of globalization. Referencing maps older than John Snow's famous cholera maps of London in the mid-19th century, this survey pulls from the plague maps of the 1600s, while addressing current issues concerning the ability of GIS technology to track diseases worldwide. The original chapters have some minor updating, and two new chapters have been added. Chapter 13 attempts to understand how the hundreds of maps of Ebola revealed not simply disease incidence but the way in which the epidemic itself was perceived. Chapter 14 is about the spatiality of the disease and the means by which different cartographic approaches may affect how infectious outbreaks like ebola can be confronted and contained.
Disease mapping involves the analysis of geo-referenced disease incidence data and has many applications, for example within resource allocation, cluster alarm analysis, and ecological studies. There is a real need amongst public health workers for simpler and more efficient tools for the analysis of geo-referenced disease incidence data. Bayesian and multilevel methods provide the required efficiency, and with the emergence of software packages – such as WinBUGS and MLwiN – are now easy to implement in practice. Provides an introduction to Bayesian and multilevel modelling in disease mapping. Adopts a practical approach, with many detailed worked examples. Includes introductory material on WinBUGS and MLwiN. Discusses three applications in detail – relative risk estimation, focused clustering, and ecological analysis. Suitable for public health workers and epidemiologists with a sound statistical knowledge. Supported by a Website featuring data sets and WinBUGS and MLwiN programs. Disease Mapping with WinBUGS and MLwiN provides a practical introduction to the use of software for disease mapping for researchers, practitioners and graduate students from statistics, public health and epidemiology who analyse disease incidence data.
“A pleasingly written lay person’s primer to disease epidemiology, as well as a gentle introduction to the social and cultural history of medicine.” —The Biologist Includes extensive illustrations Behind every disease is a story, a narrative woven of multiple threads—from the natural history of the disease to the tale of its discovery and its place in world events. The Atlas of Disease is the first book to tell these stories in a new and innovative way, interweaving new maps with contemporary illustrations to chart some of the world’s deadliest pandemics and epidemics. Sandra Hempel reveals how maps have uncovered insightful information about the history of disease, from the seventeenth-century plague maps that revealed the radical idea that diseases might be carried and spread by humans, to cholera maps in the 1800s showing the disease was carried by water, right up to the AIDs epidemic in the 1980s, and the more recent devastating Ebola outbreak. Crucially, The Atlas of Disease also explores how cartographic techniques have been used to combat epidemics by revealing previously hidden patterns. These are the stories of discoveries that have changed the course of history, affected human evolution, stimulated advances in medicine, and saved countless lives. “Ample and well-chosen pictures . . . In fact, it is the sort of book that one can leaf through, looking only at illustrations and maps, and so is suitable for the informed and curious lay reader . . . Healthcare professionals and historians should also find it of interest.” —British Society for the History of Medicine Acclaim for Sandra Hempel’s previous works of medical history “A real-life scientific thriller.” —Kirkus Reviews “Riveting.” —Daily Telegraph “Fascinating . . . [A] masterful combination of telling details, engrossing prose, and drama.” —Publishers Weekly (starred review)
Disease Mapping: From Foundations to Multidimensional Modeling guides the reader from the basics of disease mapping to the most advanced topics in this field. A multidimensional framework is offered that makes possible the joint modeling of several risks patterns corresponding to combinations of several factors, including age group, time period, disease, etc. Although theory will be covered, the applied component will be equally as important with lots of practical examples offered. Features: Discusses the very latest developments on multivariate and multidimensional mapping. Gives a single state-of-the-art framework that unifies most of the previously proposed disease mapping approaches. Balances epidemiological and statistical points-of-view. Requires no previous knowledge of disease mapping. Includes practical sessions at the end of each chapter with WinBUGs/INLA and real world datasets. Supplies R code for the examples in the book so that they can be reproduced by the reader. About the Authors: Miguel A. Martinez Beneito has spent his whole career working as a statistician for public health services, first at the epidemiology unit of the Valencia (Spain) regional health administration and later as a researcher at the public health division of FISABIO, a regional bio-sanitary research center. He has been also the Bayesian Hierarchical Models professor for several seasons at the University of Valencia Biostatics Master. Paloma Botella Rocamora has spent most of her professional career in academia although she now works as a statistician for the epidemiology unit of the Valencia regional health administration. Most of her research has been devoted to developing and applying disease mapping models to real data, although her work as a statistician in an epidemiology unit makes her develop and apply statistical methods to health data, in general.
Containing method descriptions and step-by-step procedures, the Spatial Epidemiological Approaches in Disease Mapping and Analysis equips readers with skills to prepare health-related data in the proper format, process these data using relevant functions and software, and display the results as mapped or statistical summaries. Describing the wide r
Since the publication of the second edition, many new Bayesian tools and methods have been developed for space-time data analysis, the predictive modeling of health outcomes, and other spatial biostatistical areas. Exploring these new developments, Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Third Edition provides an up-to-date, cohesive account of the full range of Bayesian disease mapping methods and applications. In addition to the new material, the book also covers more conventional areas such as relative risk estimation, clustering, spatial survival analysis, and longitudinal analysis. After an introduction to Bayesian inference, computation, and model assessment, the text focuses on important themes, including 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. It shows how Bayesian disease mapping can yield significant insights into georeferenced health data. The target audience for this text is public health specialists, epidemiologists, and biostatisticians who need to work with geo-referenced health data.
Disease mapping involves the analysis of geo-referenced disease incidence data and has many applications, for example within resource allocation, cluster alarm analysis, and ecological studies. There is a real need amongst public health workers for simpler and more efficient tools for the analysis of geo-referenced disease incidence data. Bayesian and multilevel methods provide the required efficiency, and with the emergence of software packages – such as WinBUGS and MLwiN – are now easy to implement in practice. Provides an introduction to Bayesian and multilevel modelling in disease mapping. Adopts a practical approach, with many detailed worked examples. Includes introductory material on WinBUGS and MLwiN. Discusses three applications in detail – relative risk estimation, focused clustering, and ecological analysis. Suitable for public health workers and epidemiologists with a sound statistical knowledge. Supported by a Website featuring data sets and WinBUGS and MLwiN programs. Disease Mapping with WinBUGS and MLwiN provides a practical introduction to the use of software for disease mapping for researchers, practitioners and graduate students from statistics, public health and epidemiology who analyse disease incidence data.