Estimating epidemic parameters: Application to H1N1 pandemic data

Elissa J Schwartz; Boseung Choi; Grzegorz A Rempala

doi:10.1016/j.mbs.2015.03.007

Estimating epidemic parameters: Application to H1N1 pandemic data

Math Biosci. 2015 Dec;270(Pt B):198-203. doi: 10.1016/j.mbs.2015.03.007. Epub 2015 Apr 2.

Authors

Elissa J Schwartz¹, Boseung Choi², Grzegorz A Rempala³

Affiliations

¹ School of Biological Sciences and Department of Mathematics, Washington State University, Pullman, WA 99164, USA. Electronic address: ejs@wsu.edu.
² Department of Computer Science and Statistics, Daegu University, Gyeongbuk 712-714, Republic of Korea. Electronic address: bchoi@daegu.ac.kr.
³ Division of Biostatistics and Mathematical Biosciences Institute, The Ohio State University, Columbus, OH 43210, USA. Electronic address: rempala.3@osu.edu.

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

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.

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

Publication types

Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Humans
Influenza A Virus, H1N1 Subtype / pathogenicity*
Influenza, Human / epidemiology*
Models, Theoretical*
Pandemics / statistics & numerical data*