tetano
Editor, Senior Moderator
Math Biosci. 2015 Apr 2. pii: S0025-5564(15)00066-8. doi: 10.1016/j.mbs.2015.03.007. [Epub ahead of print]
[h=1]Estimating Epidemic Parameters: Application to H1N1 Pandemic Data.[/h] Schwartz EJ[SUP]1[/SUP], Choi B[SUP]2[/SUP], Rempala GA[SUP]3[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] 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.
[h=4]KEYWORDS:[/h] H1N1 influenza; Monte Carlo approximation; parameter estimation; stochastic SIR model
PMID: 25843353 [PubMed - as supplied by publisher]
[h=1]Estimating Epidemic Parameters: Application to H1N1 Pandemic Data.[/h] Schwartz EJ[SUP]1[/SUP], Choi B[SUP]2[/SUP], Rempala GA[SUP]3[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] 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.
[h=4]KEYWORDS:[/h] H1N1 influenza; Monte Carlo approximation; parameter estimation; stochastic SIR model
PMID: 25843353 [PubMed - as supplied by publisher]