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Mathematical and Statistical Estimation Approaches in Epidemiology / Edition 1

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Overview

This book is intended as a primary resource for graduate students and researchers working in the field of infectious disease epidemiology. This collection of contributions presents deterministic and shastic approaches for epidemic modelling and statistical inference of epidemiological parameters including the real time assessment of the transmission potential of infectious diseases, issues related to the sensitivity of model assumptions, the use of historical archives as valuable sources of epidemiological information, modeling of vaccination programs and relapse, statistical challenges in bio surveillance, approaches for the spatial and temporal analysis of disease time series, quantification of parameter uncertainty and methodologies for sensitivity analysis. Methods and tools are illustrated with simulated and real datasets such as the 1918 influenza pandemic in Winnipeg, Canada, the 1968 influenza pandemic in US cities, Severe Acute Respiratory Syndrome (SARS), the 2005 Marburg fever outbreak in Angola, rubella epidemics in Peru, rotavirus in Mexico and pneumococcal disease in Australia.

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Editorial Reviews

From the Publisher

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)

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Product Details

  • ISBN-13: 9789048123124
  • Publisher: Springer Netherlands
  • Publication date: 8/3/2009
  • Edition description: 2009
  • Edition number: 1
  • Pages: 363
  • Product dimensions: 5.90 (w) x 9.50 (h) x 1.10 (d)

Table of Contents

Chapter 1: The basic reproduction number of infectious diseases: Computation and estimation using compartmental epidemic models
Gerardo Chowell and Fred Brauer
Chapter 2: Shastic Epidemic Modeling
Priscilla E. Greenwood and Luis F. Gordillo
Chapter 3: Two critical issues in quantitative modeling of communicable diseases: Inference of unobservables and dependent happening
Hiroshi Nishiura, Masayuki Kakehashi and Hisashi Inaba
Chapter 4: A note on the definition of contacts, measures of mixing, and model parametrization
Stephen Tennenbaum
Chapter 5: The effective reproduction number as a prelude to statistical estimation of time-dependent epidemic trends
Hiroshi Nishiura and Gerardo Chowell
Chapter 6: Sensitivity of Model-Based Epidemiological Parameter Estimation to Model Assumptions
Alun L. Lloyd
Chapter 7:An ensemble trajectory method for real-time modeling and prediction of unfolding epidemics: analysis of the 2005 Marburg fever outbreak in Angola
Lui's M. A. Bettencourt
Chapter 8: Statistical Challenges in BioSurveillance
Tom Burr, Sarah Michalak and Rick Picard
Chapter 9:Death Records from Historical Archives: A Valuable Source of Epidemiological Information
Rodolfo Acuña-Soto
Chapter 10: Sensitivity Analysis for Uncertainty Quantification in Mathematical Models
Leon Arriola and James M. Hyman
Chapter 11: An Inverse Problem Statistical Methodology Summary
H. T. Banks, Marie Davidian, John R. Samuels, Jr. and Karyn L.Sutton
Chapter 12: The epidemiological impact of rotavirus vaccination programs in the United States and Mexico
Eunha Shim and Carlos Castillo-Chavez
Chapter 13: 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 and Carlos Castillo-Chavez
Chapter 14: TheRole of Nonlinear Relapse on Contagion Amongst Drinking Communities
Ariel Cintrón-Arias, Fabio Sánchez, Xiaohong Wang, Carlos Castillo-Chavez, Dennis M. Gorman and Paul J. Gruenwald

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