Literature DB >> 25843353

Estimating epidemic parameters: Application to H1N1 pandemic data.

Elissa J Schwartz1, Boseung Choi2, Grzegorz A Rempala3.   

Abstract

This paper discusses estimation of the parameters in an SIR epidemic model from the observed longitudinal new infection count data. The potential problems of the standard MLE approaches are revealed and possible remedies suggested. The analysis is based on the epidemic data from the 2009 outbreak of H1N1 influenza on the campus of Washington State University.
Copyright © 2015 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  H1N1 influenza; Monte Carlo approximation; Parameter estimation; Stochastic SIR model

Mesh:

Year:  2015        PMID: 25843353     DOI: 10.1016/j.mbs.2015.03.007

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  4 in total

Review 1.  From within host dynamics to the epidemiology of infectious disease: Scientific overview and challenges.

Authors:  Juan B Gutierrez; Mary R Galinski; Stephen Cantrell; Eberhard O Voit
Journal:  Math Biosci       Date:  2015-10-16       Impact factor: 2.144

2.  Survival dynamical systems: individual-level survival analysis from population-level epidemic models.

Authors:  Wasiur R KhudaBukhsh; Boseung Choi; Eben Kenah; Grzegorz A Rempała
Journal:  Interface Focus       Date:  2019-12-13       Impact factor: 4.661

3.  Estimation of time-varying reproduction numbers underlying epidemiological processes: A new statistical tool for the COVID-19 pandemic.

Authors:  Hyokyoung G Hong; Yi Li
Journal:  PLoS One       Date:  2020-07-21       Impact factor: 3.240

4.  Generalized SIR (GSIR) epidemic model: An improved framework for the predictive monitoring of COVID-19 pandemic.

Authors:  Pushpendra Singh; Anubha Gupta
Journal:  ISA Trans       Date:  2021-02-15       Impact factor: 5.911

  4 in total

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