tetano
Editor, Senior Moderator
Math Biosci. 2013 Sep 3. pii: S0025-5564(13)00211-3. doi: 10.1016/j.mbs.2013.08.009. [Epub ahead of print]
Extension and verification of the SEIR model on the 2009 influenza A(H1N1) pandemic in Japan.
Saito MM, Imoto S, Yamaguchi R, Sato H, Nakada H, Kami M, Miyano S, Higuchi T.
Source
The Institute of Statistical Mathematics, 10-3 Midoricho, Tachikawa, Tokyo 190-8562, Japan. Electronic address: saitohm@ism.ac.jp.
Abstract
In order to understand the evolution of the 2009 influenza A(H1N1) pandemic within local regions of Japan, we studied the significance of regional migration between these regions. For this purpose, we have employed an extended SEIR model to describe the immigration of infected people and the stochastic variation of the infectious efficiency. We then applied a data assimilation technique in order to study how the agreement of the simulation results with the observed data depends on the presence/absence of immigration and the degree of variation of the infectious efficiency. Reproducibility is evaluated by log-likelihood values. The log-likelihood does not indicate the significance of immigration. Although there are multiple waves in the time course of the number of reported infected individuals, these waves could be explained by the stochastic nature of infectious events.
Copyright ? 2013. Published by Elsevier Inc.
KEYWORDS:
Data assimilation, Influenza pandemic simulation, SEIR model
PMID:
24012502
[PubMed - as supplied by publisher]
http://www.ncbi.nlm.nih.gov/pubmed/24012502
Extension and verification of the SEIR model on the 2009 influenza A(H1N1) pandemic in Japan.
Saito MM, Imoto S, Yamaguchi R, Sato H, Nakada H, Kami M, Miyano S, Higuchi T.
Source
The Institute of Statistical Mathematics, 10-3 Midoricho, Tachikawa, Tokyo 190-8562, Japan. Electronic address: saitohm@ism.ac.jp.
Abstract
In order to understand the evolution of the 2009 influenza A(H1N1) pandemic within local regions of Japan, we studied the significance of regional migration between these regions. For this purpose, we have employed an extended SEIR model to describe the immigration of infected people and the stochastic variation of the infectious efficiency. We then applied a data assimilation technique in order to study how the agreement of the simulation results with the observed data depends on the presence/absence of immigration and the degree of variation of the infectious efficiency. Reproducibility is evaluated by log-likelihood values. The log-likelihood does not indicate the significance of immigration. Although there are multiple waves in the time course of the number of reported infected individuals, these waves could be explained by the stochastic nature of infectious events.
Copyright ? 2013. Published by Elsevier Inc.
KEYWORDS:
Data assimilation, Influenza pandemic simulation, SEIR model
PMID:
24012502
[PubMed - as supplied by publisher]
http://www.ncbi.nlm.nih.gov/pubmed/24012502