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Modeling and public health emergency responses: Lessons from SARS
Modelers published thoughtful articles after the 2003 SARS crisis, but had limited if any real-time impact on the global response and may even have inadvertently contributed to a lingering misunderstanding of the means by which the epidemic was controlled. The impact of any intervention depends on i...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7105002/ https://www.ncbi.nlm.nih.gov/pubmed/21420657 http://dx.doi.org/10.1016/j.epidem.2011.01.001 |
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author | Glasser, John W. Hupert, Nathaniel McCauley, Mary M. Hatchett, Richard |
author_facet | Glasser, John W. Hupert, Nathaniel McCauley, Mary M. Hatchett, Richard |
author_sort | Glasser, John W. |
collection | PubMed |
description | Modelers published thoughtful articles after the 2003 SARS crisis, but had limited if any real-time impact on the global response and may even have inadvertently contributed to a lingering misunderstanding of the means by which the epidemic was controlled. The impact of any intervention depends on its efficiency as well as efficacy, and efficient isolation of infected individuals before they become symptomatic is difficult to imagine. Nonetheless, in exploring the possible impact of quarantine, the product of efficiency and efficacy was varied over the entire unit interval. Another mistake was repeatedly fitting otherwise appropriate gamma distributions to times to event regardless of whether they were stationary or not, particularly onset-isolation intervals whose progressive reduction evidently contributed to SARS control. By virtue of their unknown biology, newly-emerging diseases are more challenging than familiar human scourges. Influenza, for example, recurs annually and has been modeled more thoroughly than any other infectious disease. Moreover, models were integrated into preparedness exercises, during which working relationships were established that bore fruit during the 2009 A/H1N1 pandemic. To provide the most accurate and timely advice possible, especially about the possible impact of measures designed to control diseases caused by novel human pathogens, we must appreciate the value and difficulty of policy-oriented modeling. Effective communication of insights gleaned from modeling SARS will help to ensure that policymakers involve modelers in future outbreaks of newly-emerging infectious diseases. Accordingly, we illustrate the increasingly timely care-seeking by which, together with increasingly accurate diagnoses and effective isolation, SARS was controlled via heuristic arguments and descriptive analyses of familiar observations. |
format | Online Article Text |
id | pubmed-7105002 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-71050022020-03-31 Modeling and public health emergency responses: Lessons from SARS Glasser, John W. Hupert, Nathaniel McCauley, Mary M. Hatchett, Richard Epidemics Article Modelers published thoughtful articles after the 2003 SARS crisis, but had limited if any real-time impact on the global response and may even have inadvertently contributed to a lingering misunderstanding of the means by which the epidemic was controlled. The impact of any intervention depends on its efficiency as well as efficacy, and efficient isolation of infected individuals before they become symptomatic is difficult to imagine. Nonetheless, in exploring the possible impact of quarantine, the product of efficiency and efficacy was varied over the entire unit interval. Another mistake was repeatedly fitting otherwise appropriate gamma distributions to times to event regardless of whether they were stationary or not, particularly onset-isolation intervals whose progressive reduction evidently contributed to SARS control. By virtue of their unknown biology, newly-emerging diseases are more challenging than familiar human scourges. Influenza, for example, recurs annually and has been modeled more thoroughly than any other infectious disease. Moreover, models were integrated into preparedness exercises, during which working relationships were established that bore fruit during the 2009 A/H1N1 pandemic. To provide the most accurate and timely advice possible, especially about the possible impact of measures designed to control diseases caused by novel human pathogens, we must appreciate the value and difficulty of policy-oriented modeling. Effective communication of insights gleaned from modeling SARS will help to ensure that policymakers involve modelers in future outbreaks of newly-emerging infectious diseases. Accordingly, we illustrate the increasingly timely care-seeking by which, together with increasingly accurate diagnoses and effective isolation, SARS was controlled via heuristic arguments and descriptive analyses of familiar observations. Elsevier 2011-03 2011-01-28 /pmc/articles/PMC7105002/ /pubmed/21420657 http://dx.doi.org/10.1016/j.epidem.2011.01.001 Text en 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 Glasser, John W. Hupert, Nathaniel McCauley, Mary M. Hatchett, Richard Modeling and public health emergency responses: Lessons from SARS |
title | Modeling and public health emergency responses: Lessons from SARS |
title_full | Modeling and public health emergency responses: Lessons from SARS |
title_fullStr | Modeling and public health emergency responses: Lessons from SARS |
title_full_unstemmed | Modeling and public health emergency responses: Lessons from SARS |
title_short | Modeling and public health emergency responses: Lessons from SARS |
title_sort | modeling and public health emergency responses: lessons from sars |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7105002/ https://www.ncbi.nlm.nih.gov/pubmed/21420657 http://dx.doi.org/10.1016/j.epidem.2011.01.001 |
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