On epidemic modeling in real time: An application to the 2009 Novel A (H1N1) influenza outbreak in Canada

<p>Abstract</p> <p>Background</p> <p>Management of emerging infectious diseases such as the 2009 influenza pandemic A (H1N1) poses great challenges for real-time mathematical modeling of disease transmission due to limited information on disease natural history and epid...

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Main Authors: Fisman David N, Hsieh Ying-Hen, Wu Jianhong
Format: Article
Language:English
Published: BMC 2010-11-01
Series:BMC Research Notes
Online Access:http://www.biomedcentral.com/1756-0500/3/283
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author Fisman David N
Hsieh Ying-Hen
Wu Jianhong
author_facet Fisman David N
Hsieh Ying-Hen
Wu Jianhong
author_sort Fisman David N
collection DOAJ
description <p>Abstract</p> <p>Background</p> <p>Management of emerging infectious diseases such as the 2009 influenza pandemic A (H1N1) poses great challenges for real-time mathematical modeling of disease transmission due to limited information on disease natural history and epidemiology, stochastic variation in the course of epidemics, and changing case definitions and surveillance practices.</p> <p>Findings</p> <p>The Richards model and its variants are used to fit the cumulative epidemic curve for laboratory-confirmed pandemic H1N1 (pH1N1) infections in Canada, made available by the Public Health Agency of Canada (PHAC). The model is used to obtain estimates for turning points in the initial outbreak, the basic reproductive number (R<sub>0</sub>), and for expected final outbreak size in the absence of interventions. Confirmed case data were used to construct a best-fit 2-phase model with three turning points. R<sub>0 </sub>was estimated to be 1.30 (95% CI 1.12-1.47) for the first phase (April 1 to May 4) and 1.35 (95% CI 1.16-1.54) for the second phase (May 4 to June 19). Hospitalization data were also used to fit a 1-phase model with R<sub>0 </sub>= 1.35 (1.20-1.49) and a single turning point of June 11.</p> <p>Conclusions</p> <p>Application of the Richards model to Canadian pH1N1 data shows that detection of turning points is affected by the quality of data available at the time of data usage. Using a Richards model, robust estimates of R<sub>0 </sub>were obtained approximately one month after the initial outbreak in the case of 2009 A (H1N1) in Canada.</p>
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spelling doaj.art-5e0ba1b96ed7442ba098d5465f775cce2022-12-21T19:10:16ZengBMCBMC Research Notes1756-05002010-11-013128310.1186/1756-0500-3-283On epidemic modeling in real time: An application to the 2009 Novel A (H1N1) influenza outbreak in CanadaFisman David NHsieh Ying-HenWu Jianhong<p>Abstract</p> <p>Background</p> <p>Management of emerging infectious diseases such as the 2009 influenza pandemic A (H1N1) poses great challenges for real-time mathematical modeling of disease transmission due to limited information on disease natural history and epidemiology, stochastic variation in the course of epidemics, and changing case definitions and surveillance practices.</p> <p>Findings</p> <p>The Richards model and its variants are used to fit the cumulative epidemic curve for laboratory-confirmed pandemic H1N1 (pH1N1) infections in Canada, made available by the Public Health Agency of Canada (PHAC). The model is used to obtain estimates for turning points in the initial outbreak, the basic reproductive number (R<sub>0</sub>), and for expected final outbreak size in the absence of interventions. Confirmed case data were used to construct a best-fit 2-phase model with three turning points. R<sub>0 </sub>was estimated to be 1.30 (95% CI 1.12-1.47) for the first phase (April 1 to May 4) and 1.35 (95% CI 1.16-1.54) for the second phase (May 4 to June 19). Hospitalization data were also used to fit a 1-phase model with R<sub>0 </sub>= 1.35 (1.20-1.49) and a single turning point of June 11.</p> <p>Conclusions</p> <p>Application of the Richards model to Canadian pH1N1 data shows that detection of turning points is affected by the quality of data available at the time of data usage. Using a Richards model, robust estimates of R<sub>0 </sub>were obtained approximately one month after the initial outbreak in the case of 2009 A (H1N1) in Canada.</p>http://www.biomedcentral.com/1756-0500/3/283
spellingShingle Fisman David N
Hsieh Ying-Hen
Wu Jianhong
On epidemic modeling in real time: An application to the 2009 Novel A (H1N1) influenza outbreak in Canada
BMC Research Notes
title On epidemic modeling in real time: An application to the 2009 Novel A (H1N1) influenza outbreak in Canada
title_full On epidemic modeling in real time: An application to the 2009 Novel A (H1N1) influenza outbreak in Canada
title_fullStr On epidemic modeling in real time: An application to the 2009 Novel A (H1N1) influenza outbreak in Canada
title_full_unstemmed On epidemic modeling in real time: An application to the 2009 Novel A (H1N1) influenza outbreak in Canada
title_short On epidemic modeling in real time: An application to the 2009 Novel A (H1N1) influenza outbreak in Canada
title_sort on epidemic modeling in real time an application to the 2009 novel a h1n1 influenza outbreak in canada
url http://www.biomedcentral.com/1756-0500/3/283
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