• Complain

Lyle D. Broemeling - Bayesian Analysis of Infectious Diseases

Here you can read online Lyle D. Broemeling - Bayesian Analysis of Infectious Diseases full text of the book (entire story) in english for free. Download pdf and epub, get meaning, cover and reviews about this ebook. City: Boca Raton, year: 2021, publisher: CRC Press/Chapman & Hall, genre: Science. Description of the work, (preface) as well as reviews are available. Best literature library LitArk.com created for fans of good reading and offers a wide selection of genres:

Romance novel Science fiction Adventure Detective Science History Home and family Prose Art Politics Computer Non-fiction Religion Business Children Humor

Choose a favorite category and find really read worthwhile books. Enjoy immersion in the world of imagination, feel the emotions of the characters or learn something new for yourself, make an fascinating discovery.

No cover
  • Book:
    Bayesian Analysis of Infectious Diseases
  • Author:
  • Publisher:
    CRC Press/Chapman & Hall
  • Genre:
  • Year:
    2021
  • City:
    Boca Raton
  • Rating:
    3 / 5
  • Favourites:
    Add to favourites
  • Your mark:
    • 60
    • 1
    • 2
    • 3
    • 4
    • 5

Bayesian Analysis of Infectious Diseases: summary, description and annotation

We offer to read an annotation, description, summary or preface (depends on what the author of the book "Bayesian Analysis of Infectious Diseases" wrote himself). If you haven't found the necessary information about the book — write in the comments, we will try to find it.

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

Lyle D. Broemeling: author's other books


Who wrote Bayesian Analysis of Infectious Diseases? Find out the surname, the name of the author of the book and a list of all author's works by series.

Bayesian Analysis of Infectious Diseases — read online for free the complete book (whole text) full work

Below is the text of the book, divided by pages. System saving the place of the last page read, allows you to conveniently read the book "Bayesian Analysis of Infectious Diseases" online for free, without having to search again every time where you left off. Put a bookmark, and you can go to the page where you finished reading at any time.

Light

Font size:

Reset

Interval:

Bookmark:

Make
Table of Contents Guide Pages Bayesian Analysis of Infectious Diseases Chapman - photo 1
Table of Contents
Guide
Pages
Bayesian Analysis of Infectious Diseases
Chapman & Hall/CRC Biostatistics Series

Series Editors

Shein-Chung Chow, Duke University School of Medicine, USA

Byron Jones, Novartis Pharma AG, Switzerland

Jen-pei Liu, National Taiwan University, Taiwan

Karl E. Peace, Georgia Southern University, USA

Bruce W. Turnbull, Cornell University, USA

Recently Published Titles

Biomarker Analysis in Clinical Trials with R

Nusrat Rabbee

Interface between Regulation and Statistics in Drug Development

Demissie Alemayehu, Birol Emir, Michael Gaffney

Innovative Methods for Rare Disease Drug Development

Shein-Chung Chow

Medical Risk Prediction Models: With Ties to Machine Learning

Thomas A Gerds, Michael W. Kattan

Real-World Evidence in Drug Development and Evaluation

Harry Yang, Binbing Yu

Cure Models: Methods, Applications, and Implementation

Yingwei Peng, Binbing Yu

Bayesian Analysis of Infectious Diseases

COVID-19 and Beyond

Lyle D. Broemeling

Statistical Meta-Analysis using R and Stata, Second Edition

Ding-Geng (Din) Chen and Karl E. Peace

Advanced Survival Models

Catherine Legrand

Structural Equation Modeling for Health and Medicine

Douglas Gunzler, Adam Perzynski and Adam C. Carle

For more information about this series, please visit: https://www.routledge.com/Chapman--Hall-CRC-Biostatistics-Series/book-series/CHBIOSTATIS

First edition published 2021
by CRC Press
6000 Broken Sound Parkway NW, Suite 300, Boca Raton, FL 33487-2742

and by CRC Press
2 Park Square, Milton Park, Abingdon, Oxon, OX14 4RN

2021 Lyle D. Broemeling

CRC Press is an imprint of Taylor & Francis Group, LLC

The right of Lyle D. Broemeling to be identified as author of this work has been asserted by him in accordance with sections 77 and 78 of the Copyright, Designs and Patents Act 1988.

Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use. The authors and publishers have attempted to trace the copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been obtained. If any copyright material has not been acknowledged, please write and let us know so we may rectify in any future reprint.

Except as permitted under U.S. Copyright Law, no part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers.
For permission to photocopy or use material electronically from this work, access

Trademark notice: Product or corporate names may be trademarks or registered trademarks and are used only for identification and explanation without intent to infringe.

Library of Congress Cataloging-in-Publication Data

ISBN: 9780367633868 (hbk)
ISBN: 9781003125983 (ebk)

Typeset in Palatino
by SPi Global, India

Lyle D. Broemeling, Ph.D., is Director of Broemeling and Associates Inc., and is a consulting biostatistician. He has been involved with academic health science centers for about 20 years and has taught and been a consultant at the University of Texas Medical Branch in Galveston, The University of Texas MD Anderson Cancer Center and the University of Texas School of Public Health. His main interest is in developing Bayesian methods for use in medical and biological problems and in authoring textbooks in statistics. His previous books are Bayesian Biostatistics and Diagnostic Medicine, and Bayesian Methods for Agreement.

This book will introduce the reader to the latest Bayesian techniques that analyze the behavior of infectious diseases. A preview of the book is presented, followed by a list of references, and ending with online resources that provide information about emerging infectious diseases and allied subjects.

describes the foundation of Bayesian statistics. First, Bayesian theorem is given for both discrete and continuous measurements. This necessitates an explanation of the components of Bayes theorem, namely prior information, the posterior distribution of the unknown parameters, and the predictive distribution of future observations. Also provided in this chapter are many examples that illustrate Bayes theorem, among then the standard populations, such as the binomial, the normal, the Poisson, the multivariate normal, and the multinomial, and the Dirichlet.

explicates the biology and evolutionary behavior of infectious diseases, including viral and bacterial manifestations of the contagion. Next to be explained is that of the immune response via antibodies that attack the invading pathogens. The immune response involves various blood cells (white, red, and platelets) that defend against the disease. Next to be described are drugs that attempt to destroy the components of the disease. A good example of this is quinine and related drugs that control the malaria virus, and drugs that can nearly eradicate the HIV virus of AIDS patients. Although drugs have been very successful in controlling diseases, drug resistance can become a serious issue. This was the case for streptomycin, the breakthrough drug that controlled tuberculosis, but later developed a resistance. Of course, vaccines were a giant advance in medical theory, and one first thinks of the smallpox vaccine against polio. Of course, there are many examples of vaccines, such as those against measles, mumps, and diphtheria. It should be noted that for some viruses, a vaccine is yet to be developed. AIDS and Ebola do not have vaccines, but a very successful treatment for AIDS is successful, but not for Ebola. Of course, transmission of the disease from animals to humans plays an important role in the biology of emerging diseases. It is thought that the coronavirus first appeared in animals (birds, pigs, etc.) in China and was later transmitted to humans in the latter months in 2019. Ebola is believed to have been transmitted by nonhuman African primates to human.

lays the foundation for Bayesian inference of discrete time Markov chain. The concepts of limiting distributions, transient and recurrent states, ergodic chains, and the period of a chain are defined and explained.

presents biological examples of discrete time Markov chains including (1) birth and death processes, (2) logistic growth processes, (3) epidemic processes, (4) deterministic version of epidemics, (5) the stochastic version of epidemics, (6) chain binomial epidemic models, (7) the Greenwood Model, (8) The Reed-Frost Model, and (9) the duration and size of an epidemic. Lastly, the chapter consists of the explanation of statistical concepts necessary to understand epidemics.

is about the Bayesian analysis of continuous time Markov chains, such as the Poisson process. Of primary importance is the estimation of the parameter of the Poisson process via its posterior distribution. Associated subjects of the Poisson process are thinning and superposition, the spatial Poisson process, and concomitant Poisson processes. Also discussed are non-homogeneous Poisson processes and its intensity function. The chapter ends with an explanation of the important question about the coronavirus: Why are more tests needed than was originally thought to be necessary?

Next page
Light

Font size:

Reset

Interval:

Bookmark:

Make

Similar books «Bayesian Analysis of Infectious Diseases»

Look at similar books to Bayesian Analysis of Infectious Diseases. We have selected literature similar in name and meaning in the hope of providing readers with more options to find new, interesting, not yet read works.


Reviews about «Bayesian Analysis of Infectious Diseases»

Discussion, reviews of the book Bayesian Analysis of Infectious Diseases and just readers' own opinions. Leave your comments, write what you think about the work, its meaning or the main characters. Specify what exactly you liked and what you didn't like, and why you think so.