Statistical Methods for Disease Clustering PDF Download

Author: Toshiro Tango
Publisher: Springer Science & Business Media
ISBN: 1441915729
Category : Mathematics
Languages : en
Pages : 240

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Book Description
This book is intended to provide a text on statistical methods for detecting clus ters and/or clustering of health events that is of interest to ?nal year undergraduate and graduate level statistics, biostatistics, epidemiology, and geography students but will also be of relevance to public health practitioners, statisticians, biostatisticians, epidemiologists, medical geographers, human geographers, environmental scien tists, and ecologists. Prerequisites are introductory biostatistics and epidemiology courses. With increasing public health concerns about environmental risks, the need for sophisticated methods for analyzing spatial health events is immediate. Further more, the research area of statistical tests for disease clustering now attracts a wide audience due to the perceived need to implement wide ranging monitoring systems to detect possible health related bioterrorism activity. With this background and the development of the geographical information system (GIS), the analysis of disease clustering of health events has seen considerable development over the last decade. Therefore, several excellent books on spatial epidemiology and statistics have re cently been published. However, it seems to me that there is no other book solely focusing on statistical methods for disease clustering. I hope that readers will ?nd this book useful and interesting as an introduction to the subject.

Author: Peter Rogerson
Publisher: CRC Press
ISBN: 9781584889366
Category : Mathematics
Languages : en
Pages : 324

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Book Description
The widespread popularity of geographic information systems (GIS) has led to new insights in countless areas of application. It has facilitated not only the collection and storage of geographic data, but also the display of such data. Building on this progress by using an integrated approach, Statistical Detection and Monitoring of Geographic Clusters provides the statistical tools to identify whether data on a given map deviates significantly from expectations and to determine quickly whether new point patterns are emerging over time. The book begins with a review of statistical methods for cluster detection, organized according to the different types of hypotheses and questions about clustering that can be investigated. It then delineates methods that allow for the quick detection of emergent geographic clusters. The book delivers a cohesive presentation unlike that of most edited volumes. Drawing on the authors' extensive work in the field, the book delineates methods in such a way that they can be applied, almost instantly, to an array of disciplines. The readily applicable methods the book describes are useful for a multitude of problems in a variety of fields, particularly disease surveillance in the public health industry. Statistical Detection and Monitoring of Geographic Clusters is an essential volume for your reference shelf.

Author: Andrew B. Lawson
Publisher: John Wiley & Sons
ISBN: 1118723171
Category : Medical
Languages : en
Pages : 302

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Book Description
Spatial epidemiology is the description and analysis of the geographical distribution of disease. It is more important now than ever, with modern threats such as bio-terrorism making such analysis even more complex. This second edition of Statistical Methods in Spatial Epidemiology is updated and expanded to offer a complete coverage of the analysis and application of spatial statistical methods. The book is divided into two main sections: Part 1 introduces basic definitions and terminology, along with map construction and some basic models. This is expanded upon in Part II by applying this knowledge to the fundamental problems within spatial epidemiology, such as disease mapping, ecological analysis, disease clustering, bio-terrorism, space-time analysis, surveillance and infectious disease modelling. Provides a comprehensive overview of the main statistical methods used in spatial epidemiology. Updated to include a new emphasis on bio-terrorism and disease surveillance. Emphasizes the importance of space-time modelling and outlines the practical application of the method. Discusses the wide range of software available for analyzing spatial data, including WinBUGS, SaTScan and R, and features an accompanying website hosting related software. Contains numerous data sets, each representing a different approach to the analysis, and provides an insight into various modelling techniques. This text is primarily aimed at medical statisticians, researchers and practitioners from public health and epidemiology. It is also suitable for postgraduate students of statistics and epidemiology, as well professionals working in government agencies.

Author: Joseph Glaz
Publisher: Springer Science & Business Media
ISBN: 1475734603
Category : Mathematics
Languages : en
Pages : 380

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Book Description
In many statistical applications, scientists have to analyze the occurrence of observed clusters of events in time or space. Scientists are especially interested in determining whether an observed cluster of events has occurred by chance if it is assumed that the events are distributed independently and uniformly over time or space. Scan statistics have relevant applications in many areas of science and technology including geology, geography, medicine, minefield detection, molecular biology, photography, quality control and reliability theory and radio-optics.

Author: Timothy C. Urdan
Publisher: Psychology Press
ISBN: 0805852417
Category : Electronic books
Languages : en
Pages : 199

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Book Description
This book is meant to be a supplement to a more detailed statistics textbook, such as that recommended for a statistics course in the social sciences. Also, as a reference book to refresh your memory about statistical concepts.

Author: Mohamed M. Shoukri
Publisher: CRC Press
ISBN: 9780849310959
Category : Mathematics
Languages : en
Pages : 400

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Book Description
Building upon material presented in the first edition, Statistical Methods for Health Sciences, Second Edition continues to address the analytical issues related to the modeling and analysis of cluster data, both physical clustering-sampling of communities, families, or herds-and overtime clustering-longitudinal, repeated measures, or time series data. All examples in this new edition are solved using the SAS package, and all SAS programs are provided for understanding material presented. Numerous medical examples make this text especially suitable for applied health scientists and epidemiologists.

Author: F. E. Alexander
Publisher: Oxford University Press, USA
ISBN:
Category : Medical
Languages : en
Pages : 282

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Book Description
Methods for investigating generalized spatial clustering of disease in human populations have only recently become available. This volume presents the outcome of a unique practical test of these methods, in which authors of several newly-developed approaches conducted their own blind analyses of over 50 artificial datasets, some random, some generated by clustering processes. Results were then compared with the known spatial structure. An historical view of leukaemia clustering is also included. This book will be of particular interest to epidemiologists and public health specialists with responsibility for analysing childhood leukaemia and other rare diseases for which the phenomenon of clustering may offer important clues to aetiology. It will also be useful for statisticians with an interest in analysis of spatial distributions of rare disease.

Author: Paula Moraga
Publisher: CRC Press
ISBN: 1000732150
Category : Medical
Languages : en
Pages : 217

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Book Description
Geospatial health data are essential to inform public health and policy. These data can be used to quantify disease burden, understand geographic and temporal patterns, identify risk factors, and measure inequalities. Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny describes spatial and spatio-temporal statistical methods and visualization techniques to analyze georeferenced health data in R. The book covers the following topics: Manipulate and transform point, areal, and raster data, Bayesian hierarchical models for disease mapping using areal and geostatistical data, Fit and interpret spatial and spatio-temporal models with the Integrated Nested Laplace Approximations (INLA) and the Stochastic Partial Differential Equation (SPDE) approaches, Create interactive and static visualizations such as disease maps and time plots, Reproducible R Markdown reports, interactive dashboards, and Shiny web applications that facilitate the communication of insights to collaborators and policy makers. The book features fully reproducible examples of several disease and environmental applications using real-world data such as malaria in The Gambia, cancer in Scotland and USA, and air pollution in Spain. Examples in the book focus on health applications, but the approaches covered are also applicable to other fields that use georeferenced data including epidemiology, ecology, demography or criminology. The book provides clear descriptions of the R code for data importing, manipulation, modeling and visualization, as well as the interpretation of the results. This ensures contents are fully reproducible and accessible for students, researchers and practitioners.

Author: Ron Brookmeyer
Publisher: Oxford University Press
ISBN: 0195146492
Category : Medical
Languages : en
Pages : 389

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Book Description
This text explores the critical issues in the statistical analysis and interpretation of public health surveillance data. It covers statistical methods for detecting disease outbreaks and clusters, the use of survey methods and interpreting time trends and geographic patterns, among other topics.

Author: Yichuan Zhao
Publisher: Springer
ISBN: 9783030724399
Category : Medical
Languages : en
Pages : 0

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Book Description
This book brings together the voices of leading experts in the frontiers of biostatistics, biomedicine, and the health sciences to discuss the statistical procedures, useful methods, and novel applications in biostatistics research. It also includes discussions of potential future directions of biomedicine and new statistical developments for health research, with the intent of stimulating research and fostering the interactions of scholars across health research related disciplines. Topics covered include: Health data analysis and applications to EHR data Clinical trials, FDR, and applications in health science Big network analytics and its applications in GWAS Survival analysis and functional data analysis Graphical modelling in genomic studies The book will be valuable to data scientists and statisticians who are working in biomedicine and health, other practitioners in the health sciences, and graduate students and researchers in biostatistics and health.