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A model-based tool to predict the propagation of infectious disease via airports

Epidemics of novel or re-emerging infectious diseases have quickly spread globally via air travel, as highlighted by pandemic H1N1 influenza in 2009 (pH1N1). Federal, state, and local public health responders must be able to plan for and respond to these events at aviation points of entry. The emerg...

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Autores principales: Hwang, Grace M., Mahoney, Paula J., James, John H., Lin, Gene C., Berro, Andre D., Keybl, Meredith A., Goedecke, D. Michael, Mathieu, Jennifer J., Wilson, Todd
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. Published by Elsevier Ltd. 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7185572/
https://www.ncbi.nlm.nih.gov/pubmed/22245113
http://dx.doi.org/10.1016/j.tmaid.2011.12.003
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author Hwang, Grace M.
Mahoney, Paula J.
James, John H.
Lin, Gene C.
Berro, Andre D.
Keybl, Meredith A.
Goedecke, D. Michael
Mathieu, Jennifer J.
Wilson, Todd
author_facet Hwang, Grace M.
Mahoney, Paula J.
James, John H.
Lin, Gene C.
Berro, Andre D.
Keybl, Meredith A.
Goedecke, D. Michael
Mathieu, Jennifer J.
Wilson, Todd
author_sort Hwang, Grace M.
collection PubMed
description Epidemics of novel or re-emerging infectious diseases have quickly spread globally via air travel, as highlighted by pandemic H1N1 influenza in 2009 (pH1N1). Federal, state, and local public health responders must be able to plan for and respond to these events at aviation points of entry. The emergence of a novel influenza virus and its spread to the United States were simulated for February 2009 from 55 international metropolitan areas using three basic reproduction numbers (R(0)): 1.53, 1.70, and 1.90. Empirical data from the pH1N1 virus were used to validate our SEIR model. Time to entry to the U.S. during the early stages of a prototypical novel communicable disease was predicted based on the aviation network patterns and the epidemiology of the disease. For example, approximately 96% of origins (R(0) of 1.53) propagated a disease into the U.S. in under 75 days, 90% of these origins propagated a disease in under 50 days. An R(0) of 1.53 reproduced the pH1NI observations. The ability to anticipate the rate and location of disease introduction into the U.S. provides greater opportunity to plan responses based on the scenario as it is unfolding. This simulation tool can aid public health officials to assess risk and leverage resources efficiently.
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spelling pubmed-71855722020-04-28 A model-based tool to predict the propagation of infectious disease via airports Hwang, Grace M. Mahoney, Paula J. James, John H. Lin, Gene C. Berro, Andre D. Keybl, Meredith A. Goedecke, D. Michael Mathieu, Jennifer J. Wilson, Todd Travel Med Infect Dis Article Epidemics of novel or re-emerging infectious diseases have quickly spread globally via air travel, as highlighted by pandemic H1N1 influenza in 2009 (pH1N1). Federal, state, and local public health responders must be able to plan for and respond to these events at aviation points of entry. The emergence of a novel influenza virus and its spread to the United States were simulated for February 2009 from 55 international metropolitan areas using three basic reproduction numbers (R(0)): 1.53, 1.70, and 1.90. Empirical data from the pH1N1 virus were used to validate our SEIR model. Time to entry to the U.S. during the early stages of a prototypical novel communicable disease was predicted based on the aviation network patterns and the epidemiology of the disease. For example, approximately 96% of origins (R(0) of 1.53) propagated a disease into the U.S. in under 75 days, 90% of these origins propagated a disease in under 50 days. An R(0) of 1.53 reproduced the pH1NI observations. The ability to anticipate the rate and location of disease introduction into the U.S. provides greater opportunity to plan responses based on the scenario as it is unfolding. This simulation tool can aid public health officials to assess risk and leverage resources efficiently. Elsevier Ltd. Published by Elsevier Ltd. 2012-01 2012-01-13 /pmc/articles/PMC7185572/ /pubmed/22245113 http://dx.doi.org/10.1016/j.tmaid.2011.12.003 Text en Copyright © 2012 Elsevier Ltd. Published by Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Hwang, Grace M.
Mahoney, Paula J.
James, John H.
Lin, Gene C.
Berro, Andre D.
Keybl, Meredith A.
Goedecke, D. Michael
Mathieu, Jennifer J.
Wilson, Todd
A model-based tool to predict the propagation of infectious disease via airports
title A model-based tool to predict the propagation of infectious disease via airports
title_full A model-based tool to predict the propagation of infectious disease via airports
title_fullStr A model-based tool to predict the propagation of infectious disease via airports
title_full_unstemmed A model-based tool to predict the propagation of infectious disease via airports
title_short A model-based tool to predict the propagation of infectious disease via airports
title_sort model-based tool to predict the propagation of infectious disease via airports
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7185572/
https://www.ncbi.nlm.nih.gov/pubmed/22245113
http://dx.doi.org/10.1016/j.tmaid.2011.12.003
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