Epidemiologic Modeling with FluSurge for Pandemic (H1N1) 2009 Outbreak, Queensland, Australia

At the beginning of the pandemic (H1N1) 2009 outbreak, we estimated the potential surge in demand for hospital-based services in 4 Health Service Districts of Queensland, Australia, using the FluSurge model. Modifications to the model were made on the basis of emergent evidence and results provided...

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Main Authors: Philip R.A. Baker, Jiandong Sun, James Morris, Amanda Dines
Format: Article
Language:English
Published: Centers for Disease Control and Prevention 2011-09-01
Series:Emerging Infectious Diseases
Subjects:
Online Access:https://wwwnc.cdc.gov/eid/article/17/9/10-2012_article
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spelling doaj-788d0464508f47aeb6265e6fb50bc87a2020-11-24T21:45:54ZengCenters for Disease Control and PreventionEmerging Infectious Diseases1080-60401080-60592011-09-011791608161410.3201/eid1709.102012Epidemiologic Modeling with FluSurge for Pandemic (H1N1) 2009 Outbreak, Queensland, AustraliaPhilip R.A. BakerJiandong SunJames MorrisAmanda DinesAt the beginning of the pandemic (H1N1) 2009 outbreak, we estimated the potential surge in demand for hospital-based services in 4 Health Service Districts of Queensland, Australia, using the FluSurge model. Modifications to the model were made on the basis of emergent evidence and results provided to local hospitals to inform resource planning for the forthcoming pandemic. To evaluate the fit of the model, a comparison between the model’s predictions and actual hospitalizations was made. In early 2010, a Web-based survey was undertaken to evaluate the model’s usefulness. Predictions based on modified assumptions arising from the new pandemic gained better fit than results from the default model. The survey identified that the modeling support was helpful and useful to service planning for local hospitals. Our research illustrates an integrated framework involving post hoc comparison and evaluation for implementing epidemiologic modeling in response to a public health emergency.https://wwwnc.cdc.gov/eid/article/17/9/10-2012_articlevirusesinfluenzahuman influenzainfluenza A viruspandemic (H1N1) 2009pandemic
collection DOAJ
language English
format Article
sources DOAJ
author Philip R.A. Baker
Jiandong Sun
James Morris
Amanda Dines
spellingShingle Philip R.A. Baker
Jiandong Sun
James Morris
Amanda Dines
Epidemiologic Modeling with FluSurge for Pandemic (H1N1) 2009 Outbreak, Queensland, Australia
Emerging Infectious Diseases
viruses
influenza
human influenza
influenza A virus
pandemic (H1N1) 2009
pandemic
author_facet Philip R.A. Baker
Jiandong Sun
James Morris
Amanda Dines
author_sort Philip R.A. Baker
title Epidemiologic Modeling with FluSurge for Pandemic (H1N1) 2009 Outbreak, Queensland, Australia
title_short Epidemiologic Modeling with FluSurge for Pandemic (H1N1) 2009 Outbreak, Queensland, Australia
title_full Epidemiologic Modeling with FluSurge for Pandemic (H1N1) 2009 Outbreak, Queensland, Australia
title_fullStr Epidemiologic Modeling with FluSurge for Pandemic (H1N1) 2009 Outbreak, Queensland, Australia
title_full_unstemmed Epidemiologic Modeling with FluSurge for Pandemic (H1N1) 2009 Outbreak, Queensland, Australia
title_sort epidemiologic modeling with flusurge for pandemic (h1n1) 2009 outbreak, queensland, australia
publisher Centers for Disease Control and Prevention
series Emerging Infectious Diseases
issn 1080-6040
1080-6059
publishDate 2011-09-01
description At the beginning of the pandemic (H1N1) 2009 outbreak, we estimated the potential surge in demand for hospital-based services in 4 Health Service Districts of Queensland, Australia, using the FluSurge model. Modifications to the model were made on the basis of emergent evidence and results provided to local hospitals to inform resource planning for the forthcoming pandemic. To evaluate the fit of the model, a comparison between the model’s predictions and actual hospitalizations was made. In early 2010, a Web-based survey was undertaken to evaluate the model’s usefulness. Predictions based on modified assumptions arising from the new pandemic gained better fit than results from the default model. The survey identified that the modeling support was helpful and useful to service planning for local hospitals. Our research illustrates an integrated framework involving post hoc comparison and evaluation for implementing epidemiologic modeling in response to a public health emergency.
topic viruses
influenza
human influenza
influenza A virus
pandemic (H1N1) 2009
pandemic
url https://wwwnc.cdc.gov/eid/article/17/9/10-2012_article
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