Disease Modelling and Public Health, Part A

Nonfiction, Science & Nature, Mathematics, Statistics
Cover of the book Disease Modelling and Public Health, Part A by C.R. Rao, Saumyadipta Pyne, Arni S. R. Srinivasa Rao, Elsevier Science
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Author: C.R. Rao, Saumyadipta Pyne, Arni S. R. Srinivasa Rao ISBN: 9780444639691
Publisher: Elsevier Science Publication: October 13, 2017
Imprint: North Holland Language: English
Author: C.R. Rao, Saumyadipta Pyne, Arni S. R. Srinivasa Rao
ISBN: 9780444639691
Publisher: Elsevier Science
Publication: October 13, 2017
Imprint: North Holland
Language: English

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
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

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