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Timely identification of optimal control strategies for emerging infectious diseases☆

Identifieur interne : 000C60 ( Pmc/Checkpoint ); précédent : 000C59; suivant : 000C61

Timely identification of optimal control strategies for emerging infectious diseases☆

Auteurs : Zhilan Feng [États-Unis] ; Yiding Yang [États-Unis] ; Dashun Xu [États-Unis] ; Pei Zhang [États-Unis] ; Mary Mason Mccauley [États-Unis] ; John W. Glasser [États-Unis]

Source :

RBID : PMC:7126620

Abstract

Background

Health authorities must rely on quarantine, isolation, and other non-pharmaceutical interventions to contain outbreaks of newly emerging human diseases.

Methods

We modeled a generic disease caused by a pathogen apparently transmitted by close interpersonal contact, but about which little else is known. In our model, people may be infectious while incubating or during their prodrome or acute illness. We derived an expression for , the reproduction number, took its partial derivatives with respect to control parameters, and encoded these analytical results in a user-friendly Mathematica™ notebook. With biological parameters for SARS estimated from the initial case series in Hong Kong and infection rates from hospitalizations in Singapore, we determined 's sensitivity to control parameters.

Results

Stage-specific infection rate estimates from cases hospitalized before quarantine began exceed those from the entire outbreak, but are qualitatively similar: infectiousness was negligible until symptom onset, and increased 10-fold from prodrome to acute illness. Given such information, authorities might instead have emphasized a strategy whose efficiency more than compensates for any possible reduction in efficacy.

Conclusions

In future outbreaks of new human diseases transmitted via close interpersonal contact, it should be possible to identify the optimal intervention early enough to facilitate effective decision-making.


Url:
DOI: 10.1016/j.jtbi.2009.03.006
PubMed: 19289133
PubMed Central: 7126620


Affiliations:


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PMC:7126620

Le document en format XML

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<sup>
<xref ref-type="fn" rid="d32e3322"></xref>
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<name>
<surname>Feng</surname>
<given-names>Zhilan</given-names>
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<xref rid="aff1" ref-type="aff">a</xref>
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<name>
<surname>Yang</surname>
<given-names>Yiding</given-names>
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<xref rid="aff1" ref-type="aff">a</xref>
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<name>
<surname>Xu</surname>
<given-names>Dashun</given-names>
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<xref rid="aff1" ref-type="aff">a</xref>
<xref rid="fn1" ref-type="fn">1</xref>
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<name>
<surname>Zhang</surname>
<given-names>Pei</given-names>
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<xref rid="aff1" ref-type="aff">a</xref>
<xref rid="fn2" ref-type="fn">2</xref>
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Department of Mathematics, Purdue University, 150 North University Street, West Lafayette, IN 47907, USA</aff>
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National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, 1600 Clifton Road, NE Atlanta, GA 30333, USA</aff>
<author-notes>
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<label></label>
Corresponding author. Tel.: +1 404 639 8780; fax: +1 404 639 1307.
<email>jglasser@cdc.gov</email>
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<fn id="fn1">
<label>1</label>
<p>Mathematics Department, Southern Illinois University, Mail Code 4408, 1245 Lincoln Drive, Carbondale, IL 62901, USA.</p>
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<fn id="fn2">
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<p>1130 South Michigan Avenue, Apartment 3305, Chicago, IL 60605, USA.</p>
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<permissions>
<license>
<license-p>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.</license-p>
</license>
</permissions>
<abstract>
<sec>
<title>Background</title>
<p>Health authorities must rely on quarantine, isolation, and other non-pharmaceutical interventions to contain outbreaks of newly emerging human diseases.</p>
</sec>
<sec>
<title>Methods</title>
<p>We modeled a generic disease caused by a pathogen apparently transmitted by close interpersonal contact, but about which little else is known. In our model, people may be infectious while incubating or during their prodrome or acute illness. We derived an expression for
<inline-formula>
<mml:math id="M1" altimg="si1.gif" overflow="scroll">
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<mml:mo></mml:mo>
</mml:mrow>
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, the reproduction number, took its partial derivatives with respect to control parameters, and encoded these analytical results in a user-friendly Mathematica™ notebook. With biological parameters for SARS estimated from the initial case series in Hong Kong and infection rates from hospitalizations in Singapore, we determined
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's sensitivity to control parameters.</p>
</sec>
<sec>
<title>Results</title>
<p>Stage-specific infection rate estimates from cases hospitalized before quarantine began exceed those from the entire outbreak, but are qualitatively similar: infectiousness was negligible until symptom onset, and increased 10-fold from prodrome to acute illness. Given such information, authorities might instead have emphasized a strategy whose efficiency more than compensates for any possible reduction in efficacy.</p>
</sec>
<sec>
<title>Conclusions</title>
<p>In future outbreaks of new human diseases transmitted via close interpersonal contact, it should be possible to identify the optimal intervention early enough to facilitate effective decision-making.</p>
</sec>
</abstract>
<kwd-group>
<title>Keywords</title>
<kwd>Mathematical modeling</kwd>
<kwd>Emerging infections</kwd>
<kwd>Outbreak-control strategies</kwd>
<kwd>Social responses</kwd>
</kwd-group>
</article-meta>
</front>
</pmc>
<affiliations>
<list>
<country>
<li>États-Unis</li>
</country>
<region>
<li>Géorgie (États-Unis)</li>
<li>Indiana</li>
</region>
</list>
<tree>
<country name="États-Unis">
<region name="Indiana">
<name sortKey="Feng, Zhilan" sort="Feng, Zhilan" uniqKey="Feng Z" first="Zhilan" last="Feng">Zhilan Feng</name>
</region>
<name sortKey="Glasser, John W" sort="Glasser, John W" uniqKey="Glasser J" first="John W." last="Glasser">John W. Glasser</name>
<name sortKey="Mccauley, Mary Mason" sort="Mccauley, Mary Mason" uniqKey="Mccauley M" first="Mary Mason" last="Mccauley">Mary Mason Mccauley</name>
<name sortKey="Xu, Dashun" sort="Xu, Dashun" uniqKey="Xu D" first="Dashun" last="Xu">Dashun Xu</name>
<name sortKey="Yang, Yiding" sort="Yang, Yiding" uniqKey="Yang Y" first="Yiding" last="Yang">Yiding Yang</name>
<name sortKey="Zhang, Pei" sort="Zhang, Pei" uniqKey="Zhang P" first="Pei" last="Zhang">Pei Zhang</name>
</country>
</tree>
</affiliations>
</record>

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