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Author: Philip D. O'neill
Publisher: Chapman & Hall/CRC
ISBN: 9781584885481
Category : Mathematics
Languages : en
Pages : 288
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Book Description
Bayesian methods play an increasingly important role in the analysis of infectious disease data, driven by recent increases in computing power. However, few books focus on Bayesian methods for such analyses. Emphasizing the practical value of methods and how they can be used to address scientific questions of interest, Bayesian Inference for Infectious Disease Data features a wide variety of real examples to illustrate the methods described. The book uses Monte Carlo Markov chain (MCMC) methods for simulating the analyses. Assuming limited mathematical knowledge, it provides an accessible introduction to Bayesian methods that is suitable for graduate students as well as researchers in the field.
Author: Philip D. O'neill
Publisher: Chapman & Hall/CRC
ISBN: 9781584885481
Category : Mathematics
Languages : en
Pages : 288
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Book Description
Bayesian methods play an increasingly important role in the analysis of infectious disease data, driven by recent increases in computing power. However, few books focus on Bayesian methods for such analyses. Emphasizing the practical value of methods and how they can be used to address scientific questions of interest, Bayesian Inference for Infectious Disease Data features a wide variety of real examples to illustrate the methods described. The book uses Monte Carlo Markov chain (MCMC) methods for simulating the analyses. Assuming limited mathematical knowledge, it provides an accessible introduction to Bayesian methods that is suitable for graduate students as well as researchers in the field.
Author: Lyle D. Broemeling
Publisher: CRC Press
ISBN: 1000336476
Category : Mathematics
Languages : en
Pages : 216
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Book Description
Bayesian Analysis of Infectious Diseases -COVID-19 and Beyond shows how the Bayesian approach can be used to analyze the evolutionary behavior of infectious diseases, including the coronavirus pandemic. The book describes the foundation of Bayesian statistics while explicating the biology and evolutionary behavior of infectious diseases, including viral and bacterial manifestations of the contagion. The book discusses the application of Markov Chains to contagious diseases, previews data analysis models, the epidemic threshold theorem, and basic properties of the infection process. Also described are the chain binomial model for the evolution of epidemics. Features: Represents the first book on infectious disease from a Bayesian perspective. Employs WinBUGS and R to generate observations that follow the course of contagious maladies. Includes discussion of the coronavirus pandemic as well as many examples from the past, including the flu epidemic of 1918-1919. Compares standard non-Bayesian and Bayesian inferences. Offers a companion website with the R and WinBUGS code.
Author: Leonhard Held
Publisher: CRC Press
ISBN: 1351839314
Category : Medical
Languages : en
Pages : 472
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Book Description
Recent years have seen an explosion in new kinds of data on infectious diseases, including data on social contacts, whole genome sequences of pathogens, biomarkers for susceptibility to infection, serological panel data, and surveillance data. The Handbook of Infectious Disease Data Analysis provides an overview of many key statistical methods that have been developed in response to such new data streams and the associated ability to address key scientific and epidemiological questions. A unique feature of the Handbook is the wide range of topics covered. Key features Contributors include many leading researchers in the field Divided into four main sections: Basic concepts, Analysis of Outbreak Data, Analysis of Seroprevalence Data, Analysis of Surveillance Data Numerous case studies and examples throughout Provides both introductory material and key reference material
Author: N.G. Becker
Publisher: CRC Press
ISBN: 1351466704
Category : Mathematics
Languages : en
Pages : 234
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Book Description
The book gives an up-to-date account of various approaches availablefor the analysis of infectious disease data. Most of the methods havebeen developed only recently, and for those based on particularlymodern mathematics, details of the computation are carefullyillustrated. Interpretation is discussed at some length and the emphasisthroughout is on making statistical inferences about epidemiologicallyimportant parameters.Niels G. Becker is Reader in Statistics at La Trobe University,Australia.
Author: Niel Hens
Publisher: Springer Science & Business Media
ISBN: 1461440726
Category : Medical
Languages : en
Pages : 300
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Book Description
Mathematical epidemiology of infectious diseases usually involves describing the flow of individuals between mutually exclusive infection states. One of the key parameters describing the transition from the susceptible to the infected class is the hazard of infection, often referred to as the force of infection. The force of infection reflects the degree of contact with potential for transmission between infected and susceptible individuals. The mathematical relation between the force of infection and effective contact patterns is generally assumed to be subjected to the mass action principle, which yields the necessary information to estimate the basic reproduction number, another key parameter in infectious disease epidemiology. It is within this context that the Center for Statistics (CenStat, I-Biostat, Hasselt University) and the Centre for the Evaluation of Vaccination and the Centre for Health Economic Research and Modelling Infectious Diseases (CEV, CHERMID, Vaccine and Infectious Disease Institute, University of Antwerp) have collaborated over the past 15 years. This book demonstrates the past and current research activities of these institutes and can be considered to be a milestone in this collaboration. This book is focused on the application of modern statistical methods and models to estimate infectious disease parameters. We want to provide the readers with software guidance, such as R packages, and with data, as far as they can be made publicly available.
Author: Andrew B. Lawson
Publisher: CRC Press
ISBN: 1584888415
Category : Mathematics
Languages : en
Pages : 364
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Book Description
Focusing on data commonly found in public health databases and clinical settings, Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology provides an overview of the main areas of Bayesian hierarchical modeling and its application to the geographical analysis of disease. The book explores a range of topics in Bayesian inference and
Author: Tom Britton
Publisher: Springer Nature
ISBN: 3030309002
Category : Mathematics
Languages : en
Pages : 474
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Book Description
Focussing on stochastic models for the spread of infectious diseases in a human population, this book is the outcome of a two-week ICPAM/CIMPA school on "Stochastic models of epidemics" which took place in Ziguinchor, Senegal, December 5–16, 2015. The text is divided into four parts, each based on one of the courses given at the school: homogeneous models (Tom Britton and Etienne Pardoux), two-level mixing models (David Sirl and Frank Ball), epidemics on graphs (Viet Chi Tran), and statistics for epidemic models (Catherine Larédo). The CIMPA school was aimed at PhD students and Post Docs in the mathematical sciences. Parts (or all) of this book can be used as the basis for traditional or individual reading courses on the topic. For this reason, examples and exercises (some with solutions) are provided throughout.
Author: Dongmei Chen
Publisher: John Wiley & Sons
ISBN: 1118629914
Category : Medical
Languages : en
Pages : 496
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Book Description
Features modern research and methodology on the spread of infectious diseases and showcases a broad range of multi-disciplinary and state-of-the-art techniques on geo-simulation, geo-visualization, remote sensing, metapopulation modeling, cloud computing, and pattern analysis Given the ongoing risk of infectious diseases worldwide, it is crucial to develop appropriate analysis methods, models, and tools to assess and predict the spread of disease and evaluate the risk. Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases features mathematical and spatial modeling approaches that integrate applications from various fields such as geo-computation and simulation, spatial analytics, mathematics, statistics, epidemiology, and health policy. In addition, the book captures the latest advances in the use of geographic information system (GIS), global positioning system (GPS), and other location-based technologies in the spatial and temporal study of infectious diseases. Highlighting the current practices and methodology via various infectious disease studies, Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases features: Approaches to better use infectious disease data collected from various sources for analysis and modeling purposes Examples of disease spreading dynamics, including West Nile virus, bird flu, Lyme disease, pandemic influenza (H1N1), and schistosomiasis Modern techniques such as Smartphone use in spatio-temporal usage data, cloud computing-enabled cluster detection, and communicable disease geo-simulation based on human mobility An overview of different mathematical, statistical, spatial modeling, and geo-simulation techniques Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases is an excellent resource for researchers and scientists who use, manage, or analyze infectious disease data, need to learn various traditional and advanced analytical methods and modeling techniques, and become aware of different issues and challenges related to infectious disease modeling and simulation. The book is also a useful textbook and/or supplement for upper-undergraduate and graduate-level courses in bioinformatics, biostatistics, public health and policy, and epidemiology.
Author:
Publisher: Elsevier
ISBN: 0444639691
Category : Mathematics
Languages : en
Pages : 500
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Book Description
Disease Modelling and Public Health, Part A, Volume 36 addresses new challenges in existing and emerging diseases with a variety of comprehensive chapters that cover Infectious Disease Modeling, Bayesian Disease Mapping for Public Health, Real time estimation of the case fatality ratio and risk factor of death, Alternative Sampling Designs for Time-To-Event Data with Applications to Biomarker Discovery in Alzheimer's Disease, Dynamic risk prediction for cardiovascular disease: An illustration using the ARIC Study, Theoretical advances in type 2 diabetes, Finite Mixture Models in Biostatistics, and Models of Individual and Collective Behavior for Public Health Epidemiology. As a two part volume, the series covers an extensive range of techniques in the field. It present a vital resource for statisticians who need to access a number of different methods for assessing epidemic spread in population, or in formulating public health policy. Presents a comprehensive, two-part volume written by leading subject experts Provides a unique breadth and depth of content coverage Addresses the most cutting-edge developments in the field Includes chapters on Ebola and the Zika virus; topics which have grown in prominence and scholarly output
Author: Bradley P. Carlin
Publisher: Chapman and Hall/CRC
ISBN: 9781584886976
Category : Mathematics
Languages : en
Pages : 0
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Book Description
Broadening its scope to nonstatisticians, Bayesian Methods for Data Analysis, Third Edition provides an accessible introduction to the foundations and applications of Bayesian analysis. Along with a complete reorganization of the material, this edition concentrates more on hierarchical Bayesian modeling as implemented via Markov chain Monte Carlo (MCMC) methods and related data analytic techniques. New to the Third Edition New data examples, corresponding R and WinBUGS code, and homework problems Explicit descriptions and illustrations of hierarchical modeling—now commonplace in Bayesian data analysis A new chapter on Bayesian design that emphasizes Bayesian clinical trials A completely revised and expanded section on ranking and histogram estimation A new case study on infectious disease modeling and the 1918 flu epidemic A solutions manual for qualifying instructors that contains solutions, computer code, and associated output for every homework problem—available both electronically and in print Ideal for Anyone Performing Statistical Analyses Focusing on applications from biostatistics, epidemiology, and medicine, this text builds on the popularity of its predecessors by making it suitable for even more practitioners and students.
