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Reducing the Impact of the Next Influenza Pandemic Using Household-Based Public Health Interventions

Identifieur interne : 000C22 ( Pmc/Curation ); précédent : 000C21; suivant : 000C23

Reducing the Impact of the Next Influenza Pandemic Using Household-Based Public Health Interventions

Auteurs : Joseph T. Wu [République populaire de Chine, États-Unis] ; Steven Riley [République populaire de Chine] ; Christophe Fraser [Royaume-Uni] ; Gabriel M. Leung [République populaire de Chine]

Source :

RBID : PMC:1526768

Abstract

Background

The outbreak of highly pathogenic H5N1 influenza in domestic poultry and wild birds has caused global concern over the possible evolution of a novel human strain [1]. If such a strain emerges, and is not controlled at source [2,3], a pandemic is likely to result. Health policy in most countries will then be focused on reducing morbidity and mortality.

Methods and Findings

We estimate the expected reduction in primary attack rates for different household-based interventions using a mathematical model of influenza transmission within and between households. We show that, for lower transmissibility strains [2,4], the combination of household-based quarantine, isolation of cases outside the household, and targeted prophylactic use of anti-virals will be highly effective and likely feasible across a range of plausible transmission scenarios. For example, for a basic reproductive number (the average number of people infected by a typically infectious individual in an otherwise susceptible population) of 1.8, assuming only 50% compliance, this combination could reduce the infection (symptomatic) attack rate from 74% (49%) to 40% (27%), requiring peak quarantine and isolation levels of 6.2% and 0.8% of the population, respectively, and an overall anti-viral stockpile of 3.9 doses per member of the population. Although contact tracing may be additionally effective, the resources required make it impractical in most scenarios.

Conclusions

National influenza pandemic preparedness plans currently focus on reducing the impact associated with a constant attack rate, rather than on reducing transmission. Our findings suggest that the additional benefits and resource requirements of household-based interventions in reducing average levels of transmission should also be considered, even when expected levels of compliance are only moderate.


Url:
DOI: 10.1371/journal.pmed.0030361
PubMed: 16881729
PubMed Central: 1526768

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PMC:1526768

Le document en format XML

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<article-id pub-id-type="pmid">16881729</article-id>
<article-id pub-id-type="pmc">1526768</article-id>
<article-id pub-id-type="doi">10.1371/journal.pmed.0030361</article-id>
<article-id pub-id-type="publisher-id">06-PLME-RA-0258R2</article-id>
<article-id pub-id-type="sici">plme-03-09-02</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Research Article</subject>
</subj-group>
<subj-group subj-group-type="Discipline">
<subject>Infectious Diseases</subject>
<subject>Epidemiology/Public Health</subject>
</subj-group>
<subj-group subj-group-type="System Taxonomy">
<subject>Public Health</subject>
<subject>Health Policy</subject>
<subject>Infectious Diseases</subject>
<subject>Health Services Administration/Management</subject>
<subject>Resource allocation and rationing</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Reducing the Impact of the Next Influenza Pandemic Using Household-Based Public Health Interventions</article-title>
<alt-title alt-title-type="running-head">Household Interventions for Pandemic Flu</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" equal-contrib="yes">
<name>
<surname>Wu</surname>
<given-names>Joseph T</given-names>
</name>
<xref ref-type="aff" rid="aff1">1</xref>
<xref ref-type="aff" rid="aff2">2</xref>
</contrib>
<contrib contrib-type="author" equal-contrib="yes">
<name>
<surname>Riley</surname>
<given-names>Steven</given-names>
</name>
<xref ref-type="aff" rid="aff1">1</xref>
<xref ref-type="corresp" rid="cor1">*</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Fraser</surname>
<given-names>Christophe</given-names>
</name>
<xref ref-type="aff" rid="aff3">3</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Leung</surname>
<given-names>Gabriel M</given-names>
</name>
<xref ref-type="aff" rid="aff1">1</xref>
</contrib>
</contrib-group>
<aff id="aff1">
<label>1</label>
Department of Community Medicine and School of Public Health, Faculty of Medicine, University of Hong Kong, Hong Kong, Special Administrative Region, People's Republic of China</aff>
<aff id="aff2">
<label>2</label>
School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America</aff>
<aff id="aff3">
<label>3</label>
Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom</aff>
<contrib-group>
<contrib contrib-type="editor">
<name>
<surname>Wallinga</surname>
<given-names>Jacco</given-names>
</name>
<role>Academic Editor</role>
<xref ref-type="aff" rid="edit1"></xref>
</contrib>
</contrib-group>
<aff id="edit1">National Institute for Public Health and the Environment, Netherlands</aff>
<author-notes>
<corresp id="cor1">* To whom correspondence should be addressed. E-mail:
<email>steven.riley@hku.hk</email>
</corresp>
</author-notes>
<pub-date pub-type="ppub">
<month>9</month>
<year>2006</year>
</pub-date>
<pub-date pub-type="epub">
<day>8</day>
<month>8</month>
<year>2006</year>
</pub-date>
<volume>3</volume>
<issue>9</issue>
<elocation-id>e361</elocation-id>
<history>
<date date-type="received">
<day>31</day>
<month>3</month>
<year>2006</year>
</date>
<date date-type="accepted">
<day>3</day>
<month>7</month>
<year>2006</year>
</date>
</history>
<permissions>
<copyright-statement> © 2006 Wu et al.</copyright-statement>
<copyright-year>2006</copyright-year>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<license-p>This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.</license-p>
</license>
</permissions>
<abstract>
<sec id="st1">
<title>Background</title>
<p>The outbreak of highly pathogenic H5N1 influenza in domestic poultry and wild birds has caused global concern over the possible evolution of a novel human strain [
<xref rid="pmed-0030361-b001" ref-type="bibr">1</xref>
]. If such a strain emerges, and is not controlled at source [
<xref rid="pmed-0030361-b002" ref-type="bibr">2</xref>
,
<xref rid="pmed-0030361-b003" ref-type="bibr">3</xref>
], a pandemic is likely to result. Health policy in most countries will then be focused on reducing morbidity and mortality.</p>
</sec>
<sec id="st2">
<title>Methods and Findings</title>
<p>We estimate the expected reduction in primary attack rates for different household-based interventions using a mathematical model of influenza transmission within and between households. We show that, for lower transmissibility strains [
<xref rid="pmed-0030361-b002" ref-type="bibr">2</xref>
,
<xref rid="pmed-0030361-b004" ref-type="bibr">4</xref>
], the combination of household-based quarantine, isolation of cases outside the household, and targeted prophylactic use of anti-virals will be highly effective and likely feasible across a range of plausible transmission scenarios. For example, for a basic reproductive number (the average number of people infected by a typically infectious individual in an otherwise susceptible population) of 1.8, assuming only 50% compliance, this combination could reduce the infection (symptomatic) attack rate from 74% (49%) to 40% (27%), requiring peak quarantine and isolation levels of 6.2% and 0.8% of the population, respectively, and an overall anti-viral stockpile of 3.9 doses per member of the population. Although contact tracing may be additionally effective, the resources required make it impractical in most scenarios.</p>
</sec>
<sec id="st3">
<title>Conclusions</title>
<p>National influenza pandemic preparedness plans currently focus on reducing the impact associated with a constant attack rate, rather than on reducing transmission. Our findings suggest that the additional benefits and resource requirements of household-based interventions in reducing average levels of transmission should also be considered, even when expected levels of compliance are only moderate.</p>
</sec>
</abstract>
<abstract abstract-type="toc">
<p>Voluntary household-based quarantine and external isolation are likely to be effective in limiting the morbidity and mortality of an influenza pandemic, even if such a pandemic cannot be entirely prevented, and even if compliance with these interventions is moderate.</p>
</abstract>
<abstract abstract-type="editor">
<title>Editors' Summary</title>
<sec id="sb1">
<title></title>
<sec id="sb1a">
<title>Background.</title>
<p>Naturally occurring variation in the influenza virus can lead both to localized annual epidemics and to less frequent global pandemics of catastrophic proportions. The most destructive of the three influenza pandemics of the 20th century, the so-called Spanish flu of 1918–1919, is estimated to have caused 20 million deaths. As evidenced by ongoing tracking efforts and news media coverage of H5N1 avian influenza, contemporary approaches to monitoring and communications can be expected to alert health officials and the general public of the emergence of new, potentially pandemic strains before they spread globally.</p>
</sec>
<sec id="sb1b">
<title>Why Was This Study Done?</title>
<p>In order to act most effectively on advance notice of an approaching influenza pandemic, public health workers need to know which available interventions are likely to be most effective. This study was done to estimate the effectiveness of specific preventive measures that communities might implement to reduce the impact of pandemic flu. In particular, the study evaluates methods to reduce person-to-person transmission of influenza, in the likely scenario that complete control cannot be achieved by mass vaccination and anti-viral treatment alone.</p>
</sec>
<sec id="sb1c">
<title>What Did the Researchers Do and Find?</title>
<p>The researchers developed a mathematical model—essentially a computer simulation—to simulate the course of pandemic influenza in a hypothetical population at risk for infection at home, through external peer networks such as schools and workplaces, and through general community transmission. Parameters such as the distribution of household sizes, the rate at which individuals develop symptoms from nonpandemic viruses, and the risk of infection within households were derived from demographic and epidemiologic data from Hong Kong, as well as empirical studies of influenza transmission. A model based on these parameters was then used to calculate the effects of interventions including voluntary household quarantine, voluntary individual isolation in a facility outside the home, and contact tracing (that is, asking infectious individuals to identify people whom they may have infected and then warning those people) on the spread of pandemic influenza through the population. The model also took into account the anti-viral treatment of exposed, asymptomatic household members and of individuals in isolation, and assumed that all intervention strategies were put into place before the arrival of individuals infected with the pandemic virus.</p>
<p>  Using this model, the authors predicted that even if only half of the population were to comply with public health interventions, the proportion infected during the first year of an influenza pandemic could be substantially reduced by a combination of household-based quarantine, isolation of actively infected individuals in a location outside the household, and targeted prophylactic treatment of exposed individuals with anti-viral drugs. Based on an influenza-associated mortality rate of 0.5% (as has been estimated for New York City in the 1918–1919 pandemic), the magnitude of the predicted benefit of these interventions is a reduction from 49% to 27% in the proportion of the population who become ill in the first year of the pandemic, which would correspond to 16,000 fewer deaths in a city the size of Hong Kong (6.8 million people). In the model, anti-viral treatment appeared to be about as effective as isolation when each was used in combination with household quarantine, but would require stockpiling 3.9 doses of anti-viral for each member of the population. Contact tracing was predicted to provide a modest additional benefit over quarantine and isolation, but also to increase considerably the proportion of the population in quarantine.</p>
</sec>
<sec id="sb1d">
<title>What Do These Findings Mean?</title>
<p>This study predicts that voluntary household-based quarantine and external isolation can be effective in limiting the morbidity and mortality of an influenza pandemic, even if such a pandemic cannot be entirely prevented, and even if compliance with these interventions is far from uniform. These simulations can therefore inform preparedness plans in the absence of data from actual intervention trials, which would be impossible outside (and impractical within) the context of an actual pandemic. Like all mathematical models, however, the one presented in this study relies on a number of assumptions regarding the characteristics and circumstances of the situation that it is intended to represent. For example, the authors found that the efficacy of policies to reduce the rate of infection vary according to the ease with which a given virus spreads from person to person. Because this parameter (known as the basic reproductive ratio,
<italic>R</italic>
<sub>0</sub>
) cannot be reliably predicted for a new viral strain based on past epidemics, the authors note that in an actual influenza pandemic rapid determinations of
<italic>R</italic>
<sub>0</sub>
in areas already involved would be necessary to finalize public health responses in threatened areas. Further, the implementation of the interventions that appear beneficial in this model would require devoting attention and resources to practical considerations, such as how to staff isolation centers and provide food and water to those in household quarantine. However accurate the scientific data and predictive models may be, their effectiveness can only be realized through well-coordinated local, as well as international, efforts.</p>
</sec>
<sec id="sb1e">
<title>Additional Information.</title>
<p>Please access these Web sites via the online version of this summary at
<ext-link ext-link-type="uri" xlink:href="http://dx.doi.org/10.1371/journal.pmed.0030361">http://dx.doi.org/10.1371/journal.pmed.0030361</ext-link>
.</p>
<p>• World Health Organization
<ext-link ext-link-type="uri" xlink:href="http://www.who.int/csr/disease/influenza/pandemic/en">influenza pandemic preparedness page</ext-link>
</p>
<p>• US Department of Health and Human Services
<ext-link ext-link-type="uri" xlink:href="http://www.pandemicflu.gov">avian and pandemic flu information site</ext-link>
</p>
<p>• 
<ext-link ext-link-type="uri" xlink:href="http://www.phac-aspc.gc.ca/influenza/pandemic_e.html">Pandemic influenza page</ext-link>
from the Public Health Agency of Canada</p>
<p>• 
<ext-link ext-link-type="uri" xlink:href="http://www.dh.gov.uk/PolicyAndGuidance/EmergencyPlanning/PandemicFlu/fs/en">Emergency planning page on pandemic flu</ext-link>
from the England Department of Health</p>
<p>• 
<ext-link ext-link-type="uri" xlink:href="http://en.wikipedia.org/wiki/Pandemic_influenza">Wikipedia entry on pandemic influenza</ext-link>
with links to individual country resources (note: Wikipedia is a free Internet encyclopedia that anyone can edit)</p>
</sec>
</sec>
</abstract>
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<page-count count="9"></page-count>
</counts>
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<meta-name>citation</meta-name>
<meta-value>Wu JT, Riley S, Fraser C, Leung GM (2006) Reducing the impact of the next influenza pandemic using household-based public health interventions. PLoS Med 3(9): e361. DOI:
<ext-link ext-link-type="doi" xlink:href="10.1371/journal.pmed.0030361">10.1371/journal.pmed.0030361</ext-link>
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