Download or read book Bayesian Analysis of Infectious Diseases written by Lyle D. Broemeling and published by CRC Press. This book was released on 2021-02-07 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 the R and WinBUGS code on at www.routledge.com/9780367633868

Download or read book Bayesian Inference for Infectious Disease Data written by Philip D. O'neill and published by Chapman & Hall/CRC. This book was released on 2009-04-01 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Handbook of Infectious Disease Data Analysis written by Leonhard Held and published by CRC Press. This book was released on 2019-11-07 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Infectious Disease Informatics and Biosurveillance written by Daniel Zeng and published by Springer Science & Business Media. This book was released on 2010-11-16 with total page 531 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book on Infectious Disease Informatics (IDI) and biosurveillance is intended to provide an integrated view of the current state of the art, identify technical and policy challenges and opportunities, and promote cross-disciplinary research that takes advantage of novel methodology and what we have learned from innovative applications. This book also fills a systemic gap in the literature by emphasizing informatics driven perspectives (e.g., information system design, data standards, computational aspects of biosurveillance algorithms, and system evaluation). Finally, this book attempts to reach policy makers and practitioners through the clear and effective communication of recent research findings in the context of case studies in IDI and biosurveillance, providing “hands-on” in-depth opportunities to practitioners to increase their understanding of value, applicability, and limitations of technical solutions. This book collects the state of the art research and modern perspectives of distinguished individuals and research groups on cutting-edge IDI technical and policy research and its application in biosurveillance. The contributed chapters are grouped into three units. Unit I provides an overview of recent biosurveillance research while highlighting the relevant legal and policy structures in the context of IDI and biosurveillance ongoing activities. It also identifies IDI data sources while addressing information collection, sharing, and dissemination issues as well as ethical considerations. Unit II contains survey chapters on the types of surveillance methods used to analyze IDI data in the context of public health and bioterrorism. Specific computational techniques covered include: text mining, time series analysis, multiple data streams methods, ensembles of surveillance methods, spatial analysis and visualization, social network analysis, and agent-based simulation. Unit III examines IT and decision support for public health event response and bio-defense. Practical lessons learned in developing public health and biosurveillance systems, technology adoption, and syndromic surveillance for large events are discussed. The goal of this book is to provide an understandable interdisciplinary IDI and biosurveillance reference either used as a standalone textbook or reference for students, researchers, and practitioners in public health, veterinary medicine, biostatistics, information systems, computer science, and public administration and policy.

Download or read book Bayesian Disease Mapping written by Andrew B. Lawson and published by CRC Press. This book was released on 2008-08-05 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Modeling Infectious Disease Parameters Based on Serological and Social Contact Data written by Niel Hens and published by Springer Science & Business Media. This book was released on 2012-10-24 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Bayesian Analysis of Infectious Disease Time Series Data and Optimal Constrained Bayesian Updating written by and published by . This book was released on 2005 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian analysis of infectious disease time series data and optimal constrained Bayesian updating.

Download or read book Analysis of Infectious Disease Data written by N.G. Becker and published by CRC Press. This book was released on 2017-11-22 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases written by Dongmei Chen and published by John Wiley & Sons. This book was released on 2014-12-08 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Bayesian Inference for Infectious Disease Transmission Models Based on Ordinary Differential Equations written by Felix Weidemann and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Disease Modelling and Public Health Part A written by and published by Elsevier. This book was released on 2017-10-13 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Analysis of Infectious Diseases Data in Ethiopia written by Belay Birlie Yimer (Doctor of Sciences: Statistics) and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Mathematical Tools for Understanding Infectious Disease Dynamics written by Odo Diekmann and published by Princeton University Press. This book was released on 2012-11-18 with total page 517 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical modeling is critical to our understanding of how infectious diseases spread at the individual and population levels. This book gives readers the necessary skills to correctly formulate and analyze mathematical models in infectious disease epidemiology, and is the first treatment of the subject to integrate deterministic and stochastic models and methods. Mathematical Tools for Understanding Infectious Disease Dynamics fully explains how to translate biological assumptions into mathematics to construct useful and consistent models, and how to use the biological interpretation and mathematical reasoning to analyze these models. It shows how to relate models to data through statistical inference, and how to gain important insights into infectious disease dynamics by translating mathematical results back to biology. This comprehensive and accessible book also features numerous detailed exercises throughout; full elaborations to all exercises are provided. Covers the latest research in mathematical modeling of infectious disease epidemiology Integrates deterministic and stochastic approaches Teaches skills in model construction, analysis, inference, and interpretation Features numerous exercises and their detailed elaborations Motivated by real-world applications throughout

Download or read book Stochastic Epidemic Models with Inference written by Tom Britton and published by Springer Nature. This book was released on 2019-11-30 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Bayesian Disease Mapping written by Andrew B. Lawson and published by CRC Press. This book was released on 2018-05-20 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Modeling Infectious Diseases in Humans and Animals written by Matt J. Keeling and published by Princeton University Press. This book was released on 2011-09-19 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: For epidemiologists, evolutionary biologists, and health-care professionals, real-time and predictive modeling of infectious disease is of growing importance. This book provides a timely and comprehensive introduction to the modeling of infectious diseases in humans and animals, focusing on recent developments as well as more traditional approaches. Matt Keeling and Pejman Rohani move from modeling with simple differential equations to more recent, complex models, where spatial structure, seasonal "forcing," or stochasticity influence the dynamics, and where computer simulation needs to be used to generate theory. In each of the eight chapters, they deal with a specific modeling approach or set of techniques designed to capture a particular biological factor. They illustrate the methodology used with examples from recent research literature on human and infectious disease modeling, showing how such techniques can be used in practice. Diseases considered include BSE, foot-and-mouth, HIV, measles, rubella, smallpox, and West Nile virus, among others. Particular attention is given throughout the book to the development of practical models, useful both as predictive tools and as a means to understand fundamental epidemiological processes. To emphasize this approach, the last chapter is dedicated to modeling and understanding the control of diseases through vaccination, quarantine, or culling. Comprehensive, practical introduction to infectious disease modeling Builds from simple to complex predictive models Models and methodology fully supported by examples drawn from research literature Practical models aid students' understanding of fundamental epidemiological processes For many of the models presented, the authors provide accompanying programs written in Java, C, Fortran, and MATLAB In-depth treatment of role of modeling in understanding disease control

Download or read book Infectious Disease Surveillance written by Nkuchia M. M'ikanatha and published by John Wiley & Sons. This book was released on 2013-03-11 with total page 1139 pages. Available in PDF, EPUB and Kindle. Book excerpt: This fully updated edition of Infectious Disease Surveillance is for frontline public health practitioners, epidemiologists, and clinical microbiologists who are engaged in communicable disease control. It is also a foundational text for trainees in public health, applied epidemiology, postgraduate medicine and nursing programs. The second edition portrays both the conceptual framework and practical aspects of infectious disease surveillance. It is a comprehensive resource designed to improve the tracking of infectious diseases and to serve as a starting point in the development of new surveillance systems. Infectious Disease Surveillance includes over 45 chapters from over 100 contributors, and topics organized into six sections based on major themes. Section One highlights the critical role surveillance plays in public health and it provides an overview of the current International Health Regulations (2005) in addition to successes and challenges in infectious disease eradication. Section Two describes surveillance systems based on logical program areas such as foodborne illnesses, vector-borne diseases, sexually transmitted diseases, viral hepatitis healthcare and transplantation associated infections. Attention is devoted to programs for monitoring unexplained deaths, agents of bioterrorism, mass gatherings, and disease associated with international travel. Sections Three and Four explore the uses of the Internet and wireless technologies to advance infectious disease surveillance in various settings with emphasis on best practices based on deployed systems. They also address molecular laboratory methods, and statistical and geospatial analysis, and evaluation of systems for early epidemic detection. Sections Five and Six discuss legal and ethical considerations, communication strategies and applied epidemiology-training programs. The rest of the chapters offer public-private partnerships, as well lessons from the 2009-2010 H1N1 influenza pandemic and future directions for infectious disease surveillance.