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

Elissa J. Schwartz
, Boseung Choi
, Grzegorz A. Rempala^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

17 Citations (Scopus)

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.

Original language	English
Pages (from-to)	198-203
Number of pages	6
Journal	Mathematical Biosciences
Volume	270
DOIs	https://doi.org/10.1016/j.mbs.2015.03.007
Publication status	Published - 2015 Dec 1
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2015 Elsevier Inc..

Keywords

62M-05
92-08
92D30
H1N1 influenza
Monte Carlo approximation
Parameter estimation
Stochastic SIR model

ASJC Scopus subject areas

Statistics and Probability
Modelling and Simulation
General Biochemistry,Genetics and Molecular Biology
General Immunology and Microbiology
General Agricultural and Biological Sciences
Applied Mathematics

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10.1016/j.mbs.2015.03.007

Cite this

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title = "Estimating epidemic parameters: Application to H1N1 pandemic data",

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 = "62M-05, 92-08, 92D30, H1N1 influenza, Monte Carlo approximation, Parameter estimation, Stochastic SIR model",

author = "Schwartz, \{Elissa J.\} and Boseung Choi and Rempala, \{Grzegorz A.\}",

note = "Publisher Copyright: {\textcopyright} 2015 Elsevier Inc..",

year = "2015",

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doi = "10.1016/j.mbs.2015.03.007",

language = "English",

volume = "270",

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T2 - Application to H1N1 pandemic data

AU - Schwartz, Elissa J.

AU - Choi, Boseung

AU - Rempala, Grzegorz A.

PY - 2015/12/1

Y1 - 2015/12/1

N2 - 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.

AB - 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.

KW - 62M-05

KW - 92-08

KW - 92D30

KW - H1N1 influenza

KW - Monte Carlo approximation

KW - Parameter estimation

KW - Stochastic SIR model

UR - https://www.scopus.com/pages/publications/84949532708

U2 - 10.1016/j.mbs.2015.03.007

DO - 10.1016/j.mbs.2015.03.007

M3 - Article

C2 - 25843353

AN - SCOPUS:84949532708

SN - 0025-5564

VL - 270

SP - 198

EP - 203

JO - Mathematical Biosciences

JF - Mathematical Biosciences

ER -

Estimating epidemic parameters: Application to H1N1 pandemic data

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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