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Mathematical and Statistical Estimation Approaches in Epidemiology

  • Book
  • © 2009

Overview

Editors:
  1. Gerardo Chowell

    1. Arizona State University School of Human Evolution & Social Change, Tempe, USA

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    You can also search for this editor in PubMed   Google Scholar

  2. James M. Hyman

    1. Los Alamos National Laboratory, Los Alamos, USA

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  3. Luís M. A. Bettencourt

    1. Los Alamos National Laboratory, Los Alamos, USA

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  4. Carlos Castillo-Chavez

    1. Dept. Mathematics & Statistics, Arizona State University, Tempe, USA

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  • Essential resource for graduate students interested in the analysis of infectious disease outbreaks and epidemic modeling
  • Approaches for the estimation of the transmission potential of infectious diseases and other epidemiological parameters
  • Methods and applications for sensitivity and uncertainty quantification in epidemic modelling
  • Theory and methods are illustrated using real applications

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Table of contents (14 chapters)

  1. Front Matter

    Pages I-XIII
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  2. The Basic Reproduction Number of Infectious Diseases: Computation and Estimation Using Compartmental Epidemic Models

    • Gerardo Chowell, Fred Brauer
    Pages 1-30

  3. Stochastic Epidemic Modeling

    • Priscilla E. Greenwood, Luis F. Gordillo
    Pages 31-52

  4. Two Critical Issues in Quantitative Modeling of Communicable Diseases: Inference of Unobservables and Dependent Happening

    • Hiroshi Nishiura, Masayuki Kakehashi, Hisashi Inaba
    Pages 53-87

  5. The Chain of Infection, Contacts, and Model Parametrization

    • Stephen Tennenbaum
    Pages 89-102

  6. The Effective Reproduction Number as a Prelude to Statistical Estimation of Time-Dependent Epidemic Trends

    • Hiroshi Nishiura, Gerardo Chowell
    Pages 103-121

  7. Sensitivity of Model-Based Epidemiological Parameter Estimation to Model Assumptions

    • A.L. Lloyd
    Pages 123-141

  8. An Ensemble Trajectory Method for Real-Time Modeling and Prediction of Unfolding Epidemics: Analysis of the 2005 Marburg Fever Outbreak in Angola

    • Luís M. A. Bettencourt
    Pages 143-161

  9. Statistical Challenges in BioSurveillance

    • Tom Burr, Sarah Michalak, Rick Picard
    Pages 163-187

  10. Death Records from Historical Archives: A Valuable Source of Epidemiological Information

    • Rodolfo Acuna-Soto
    Pages 189-194

  11. Sensitivity Analysis for Uncertainty Quantification in Mathematical Models

    • Leon Arriola, James M. Hyman
    Pages 195-247

  12. An Inverse Problem Statistical Methodology Summary

    • H. Thomas Banks, Marie Davidian, John R. Samuels Jr., Karyn L. Sutton
    Pages 249-302

  13. The Epidemiological Impact of Rotavirus Vaccination Programs in the United States and Mexico

    • Eunha Shim, Carlos Castillo-Chavez
    Pages 303-323

  14. Spatial and Temporal Dynamics of Rubella in Peru, 1997–2006: Geographic Patterns, Age at Infection and Estimation of Transmissibility

    • Daniel Rios-Doria, Gerardo Chowell, Cesar Munayco-Escate, Alvaro Witthembury, Carlos Castillo-Chavez
    Pages 325-341

  15. The Role of Nonlinear Relapse on Contagion Amongst Drinking Communities

    • Ariel Cintrón-Arias, Fabio Sánchez, Xiaohong Wang, Carlos Castillo-Chavez, Dennis M. Gorman, Paul J. Gruenewald
    Pages 343-360

  16. Back Matter

    Pages 361-363
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Keywords

About this book

Mathematical and Statistical Estimation Approaches in Epidemiology compiles t- oretical and practical contributions of experts in the analysis of infectious disease epidemics in a single volume. Recent collections have focused in the analyses and simulation of deterministic and stochastic models whose aim is to identify and rank epidemiological and social mechanisms responsible for disease transmission. The contributions in this volume focus on the connections between models and disease data with emphasis on the application of mathematical and statistical approaches that quantify model and data uncertainty. The book is aimed at public health experts, applied mathematicians and sci- tists in the life and social sciences, particularly graduate or advanced undergraduate students, who are interested not only in building and connecting models to data but also in applying and developing methods that quantify uncertainty in the context of infectious diseases. Chowell and Brauer open this volume with an overview of the classical disease transmission models of Kermack-McKendrick including extensions that account for increased levels of epidemiological heterogeneity. Their theoretical tour is followed by the introduction of a simple methodology for the estimation of, the basic reproduction number,R . The use of this methodology 0 is illustrated, using regional data for 1918–1919 and 1968 in uenza pandemics.

Reviews

From the reviews:

“Mathematical and Statistical Estimation Approaches in Epidemiology is a well written book … . The book is aimed at public health experts, applied mathematicians and scientists in the life and social sciences particularly graduate or advanced undergraduate students. This is an excellent text for those with some knowledge of statistics mathematics … . it suits the expectations for that category of readers that is written for and will be a useful reference on many bookshelves.” (Peter Wludyka and Carmen Masnita Iusan, Technometrics, Vol. 53 (1), February, 2011)

Editors and Affiliations

  • Arizona State University School of Human Evolution & Social Change, Tempe, USA

    Gerardo Chowell

  • Los Alamos National Laboratory, Los Alamos, USA

    James M. Hyman, Luís M. A. Bettencourt

  • Dept. Mathematics & Statistics, Arizona State University, Tempe, USA

    Carlos Castillo-Chavez

About the editors

Gerardo Chowell is an associate professor and a Second Century Initiative Scholar (2CI) in the School of Public Health at Georgia State University in Atlanta. His research program includes the development and application of quantitative approaches for understanding the transmission dynamics and control of infectious diseases including influenza, Ebola, and dengue fever. His work has appeared in high-impact journals including The New England Journal of Medicine, PLOS Medicine, and BMC Medicine, and has been cited by major media outlets including the Washington Post and TIME magazine.

James (Mac) Hyman has developed and analyzed mathematical models for the transmission of HIV/AIDs, influenza, malaria, dengue fever, chikungunya, and infections.  His current focus is to identify approaches where these models can help public health workers be more effective in mitigating the impact of emerging diseases.  He was a research scientist at Los Alamos National Laboratory for over thirty years, is a past president of the Society for Industrial and Applied Mathematics (SIAM),  and now holds the Phillips Distinguished Chair in Mathematics at Tulane University.

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