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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Modelling strategies for controlling SARS outbreaks.</title><author><name sortKey="Gumel, Abba B" sort="Gumel, Abba B" uniqKey="Gumel A" first="Abba B." last="Gumel">Abba B. Gumel</name></author><author><name sortKey="Ruan, Shigui" sort="Ruan, Shigui" uniqKey="Ruan S" first="Shigui" last="Ruan">Shigui Ruan</name></author><author><name sortKey="Day, Troy" sort="Day, Troy" uniqKey="Day T" first="Troy" last="Day">Troy Day</name></author><author><name sortKey="Watmough, James" sort="Watmough, James" uniqKey="Watmough J" first="James" last="Watmough">James Watmough</name></author><author><name sortKey="Brauer, Fred" sort="Brauer, Fred" uniqKey="Brauer F" first="Fred" last="Brauer">Fred Brauer</name></author><author><name sortKey="Van Den Driessche, P" sort="Van Den Driessche, P" uniqKey="Van Den Driessche P" first="P." last="Van Den Driessche">P. Van Den Driessche</name></author><author><name sortKey="Gabrielson, Dave" sort="Gabrielson, Dave" uniqKey="Gabrielson D" first="Dave" last="Gabrielson">Dave Gabrielson</name></author><author><name sortKey="Bowman, Chris" sort="Bowman, Chris" uniqKey="Bowman C" first="Chris" last="Bowman">Chris Bowman</name></author><author><name sortKey="Alexander, Murray E" sort="Alexander, Murray E" uniqKey="Alexander M" first="Murray E." last="Alexander">Murray E. Alexander</name></author><author><name sortKey="Ardal, Sten" sort="Ardal, Sten" uniqKey="Ardal S" first="Sten" last="Ardal">Sten Ardal</name></author><author><name sortKey="Wu, Jianhong" sort="Wu, Jianhong" uniqKey="Wu J" first="Jianhong" last="Wu">Jianhong Wu</name></author><author><name sortKey="Sahai, Beni M" sort="Sahai, Beni M" uniqKey="Sahai B" first="Beni M." last="Sahai">Beni M. Sahai</name></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">15539347</idno><idno type="pmc">1691853</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1691853</idno><idno type="RBID">PMC:1691853</idno><idno type="doi">10.1098/rspb.2004.2800</idno><date when="2004">2004</date><idno type="wicri:Area/Pmc/Corpus">000739</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000739</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Modelling strategies for controlling SARS outbreaks.</title><author><name sortKey="Gumel, Abba B" sort="Gumel, Abba B" uniqKey="Gumel A" first="Abba B." last="Gumel">Abba B. Gumel</name></author><author><name sortKey="Ruan, Shigui" sort="Ruan, Shigui" uniqKey="Ruan S" first="Shigui" last="Ruan">Shigui Ruan</name></author><author><name sortKey="Day, Troy" sort="Day, Troy" uniqKey="Day T" first="Troy" last="Day">Troy Day</name></author><author><name sortKey="Watmough, James" sort="Watmough, James" uniqKey="Watmough J" first="James" last="Watmough">James Watmough</name></author><author><name sortKey="Brauer, Fred" sort="Brauer, Fred" uniqKey="Brauer F" first="Fred" last="Brauer">Fred Brauer</name></author><author><name sortKey="Van Den Driessche, P" sort="Van Den Driessche, P" uniqKey="Van Den Driessche P" first="P." last="Van Den Driessche">P. Van Den Driessche</name></author><author><name sortKey="Gabrielson, Dave" sort="Gabrielson, Dave" uniqKey="Gabrielson D" first="Dave" last="Gabrielson">Dave Gabrielson</name></author><author><name sortKey="Bowman, Chris" sort="Bowman, Chris" uniqKey="Bowman C" first="Chris" last="Bowman">Chris Bowman</name></author><author><name sortKey="Alexander, Murray E" sort="Alexander, Murray E" uniqKey="Alexander M" first="Murray E." last="Alexander">Murray E. Alexander</name></author><author><name sortKey="Ardal, Sten" sort="Ardal, Sten" uniqKey="Ardal S" first="Sten" last="Ardal">Sten Ardal</name></author><author><name sortKey="Wu, Jianhong" sort="Wu, Jianhong" uniqKey="Wu J" first="Jianhong" last="Wu">Jianhong Wu</name></author><author><name sortKey="Sahai, Beni M" sort="Sahai, Beni M" uniqKey="Sahai B" first="Beni M." last="Sahai">Beni M. Sahai</name></author></analytic><series><title level="j">Proceedings of the Royal Society B: Biological Sciences</title><idno type="ISSN">0962-8452</idno><idno type="eISSN">1471-2954</idno><imprint><date when="2004">2004</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Severe acute respiratory syndrome (SARS), a new, highly contagious, viral disease, emerged in China late in 2002 and quickly spread to 32 countries and regions causing in excess of 774 deaths and 8098 infections worldwide. In the absence of a rapid diagnostic test, therapy or vaccine, isolation of individuals diagnosed with SARS and quarantine of individuals feared exposed to SARS virus were used to control the spread of infection. We examine mathematically the impact of isolation and quarantine on the control of SARS during the outbreaks in Toronto, Hong Kong, Singapore and Beijing using a deterministic model that closely mimics the data for cumulative infected cases and SARS-related deaths in the first three regions but not in Beijing until mid-April, when China started to report data more accurately. The results reveal that achieving a reduction in the contact rate between susceptible and diseased individuals by isolating the latter is a critically important strategy that can control SARS outbreaks with or without quarantine. An optimal isolation programme entails timely implementation under stringent hygienic precautions defined by a critical threshold value. Values below this threshold lead to control, but those above are associated with the incidence of new community outbreaks or nosocomial infections, a known cause for the spread of SARS in each region. Allocation of resources to implement optimal isolation is more effective than to implement sub-optimal isolation and quarantine together. A community-wide eradication of SARS is feasible if optimal isolation is combined with a highly effective screening programme at the points of entry.</p></div></front></TEI><pmc article-type="research-article"><pmc-comment>The publisher of this article does not allow downloading of the full text in XML form.</pmc-comment>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Proc Biol Sci</journal-id><journal-title>Proceedings of the Royal Society B: Biological Sciences</journal-title><issn pub-type="ppub">0962-8452</issn><issn pub-type="epub">1471-2954</issn></journal-meta><article-meta><article-id pub-id-type="pmid">15539347</article-id><article-id pub-id-type="pmc">1691853</article-id><article-id pub-id-type="pii">PMK2NQTF3MTU37BE</article-id><article-id pub-id-type="doi">10.1098/rspb.2004.2800</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group></article-categories><title-group><article-title>Modelling strategies for controlling SARS outbreaks.</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Gumel</surname><given-names>Abba B.</given-names></name></contrib><contrib contrib-type="author"><name><surname>Ruan</surname><given-names>Shigui</given-names></name></contrib><contrib contrib-type="author"><name><surname>Day</surname><given-names>Troy</given-names></name></contrib><contrib contrib-type="author"><name><surname>Watmough</surname><given-names>James</given-names></name></contrib><contrib contrib-type="author"><name><surname>Brauer</surname><given-names>Fred</given-names></name></contrib><contrib contrib-type="author"><name><surname>van den Driessche</surname><given-names>P.</given-names></name></contrib><contrib contrib-type="author"><name><surname>Gabrielson</surname><given-names>Dave</given-names></name></contrib><contrib contrib-type="author"><name><surname>Bowman</surname><given-names>Chris</given-names></name></contrib><contrib contrib-type="author"><name><surname>Alexander</surname><given-names>Murray E.</given-names></name></contrib><contrib contrib-type="author"><name><surname>Ardal</surname><given-names>Sten</given-names></name></contrib><contrib contrib-type="author"><name><surname>Wu</surname><given-names>Jianhong</given-names></name></contrib><contrib contrib-type="author"><name><surname>Sahai</surname><given-names>Beni M.</given-names></name></contrib></contrib-group><aff>Institute of Industrial and Mathematical Sciences, University of Manitoba, Winnipeg, Manitoba R3T 2N2, Canada.</aff><pub-date pub-type="ppub"><day>7</day><month>11</month><year>2004</year></pub-date><volume>271</volume><issue>1554</issue><fpage>2223</fpage><lpage>2232</lpage><abstract><p>Severe acute respiratory syndrome (SARS), a new, highly contagious, viral disease, emerged in China late in 2002 and quickly spread to 32 countries and regions causing in excess of 774 deaths and 8098 infections worldwide. In the absence of a rapid diagnostic test, therapy or vaccine, isolation of individuals diagnosed with SARS and quarantine of individuals feared exposed to SARS virus were used to control the spread of infection. We examine mathematically the impact of isolation and quarantine on the control of SARS during the outbreaks in Toronto, Hong Kong, Singapore and Beijing using a deterministic model that closely mimics the data for cumulative infected cases and SARS-related deaths in the first three regions but not in Beijing until mid-April, when China started to report data more accurately. The results reveal that achieving a reduction in the contact rate between susceptible and diseased individuals by isolating the latter is a critically important strategy that can control SARS outbreaks with or without quarantine. An optimal isolation programme entails timely implementation under stringent hygienic precautions defined by a critical threshold value. Values below this threshold lead to control, but those above are associated with the incidence of new community outbreaks or nosocomial infections, a known cause for the spread of SARS in each region. Allocation of resources to implement optimal isolation is more effective than to implement sub-optimal isolation and quarantine together. A community-wide eradication of SARS is feasible if optimal isolation is combined with a highly effective screening programme at the points of entry.</p></abstract></article-meta></front></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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