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<title xml:lang="en">SARS epidemical forecast research in mathematical model</title>
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<name sortKey="Guanghong, Ding" sort="Guanghong, Ding" uniqKey="Guanghong D" first="Ding" last="Guanghong">Ding Guanghong</name>
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<name sortKey="Chang, Liu" sort="Chang, Liu" uniqKey="Chang L" first="Liu" last="Chang">Liu Chang</name>
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<name sortKey="Jianqiu, Gong" sort="Jianqiu, Gong" uniqKey="Jianqiu G" first="Gong" last="Jianqiu">Gong Jianqiu</name>
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<nlm:aff id="Aff1"></nlm:aff>
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<name sortKey="Ling, Wang" sort="Ling, Wang" uniqKey="Ling W" first="Wang" last="Ling">Wang Ling</name>
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<name sortKey="Ke, Cheng" sort="Ke, Cheng" uniqKey="Ke C" first="Cheng" last="Ke">Cheng Ke</name>
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<name sortKey="Di, Zhang" sort="Di, Zhang" uniqKey="Di Z" first="Zhang" last="Di">Zhang Di</name>
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<title xml:lang="en" level="a" type="main">SARS epidemical forecast research in mathematical model</title>
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<nlm:aff id="Aff1"></nlm:aff>
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<name sortKey="Chang, Liu" sort="Chang, Liu" uniqKey="Chang L" first="Liu" last="Chang">Liu Chang</name>
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<name sortKey="Jianqiu, Gong" sort="Jianqiu, Gong" uniqKey="Jianqiu G" first="Gong" last="Jianqiu">Gong Jianqiu</name>
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<nlm:aff id="Aff1"></nlm:aff>
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<name sortKey="Ling, Wang" sort="Ling, Wang" uniqKey="Ling W" first="Wang" last="Ling">Wang Ling</name>
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<name sortKey="Ke, Cheng" sort="Ke, Cheng" uniqKey="Ke C" first="Cheng" last="Ke">Cheng Ke</name>
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<name sortKey="Di, Zhang" sort="Di, Zhang" uniqKey="Di Z" first="Zhang" last="Di">Zhang Di</name>
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<idno type="ISSN">1001-6538</idno>
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<p>The SIJR model, simplified from the SEIJR model, is adopted to analyze the important parameters of the model of SARS epidemic such as the transmission rate, basic reproductive number. And some important parameters are obtained such as the transmission rate by applying this model to analyzing the situation in Hong Kong, Singapore and Canada at the outbreak of SARS. Then forecast of the transmission of SARS is drawn out here by the adjustment of parameters (such as quarantined rate) in the model. It is obvious that inflexion lies on the crunode of the graph, which indicates the big difference in transmission characteristics between the epidemic under control and not under control. This model can also be used in the comparison of the control effectiveness among different regions. The results from this model match well with the actual data in Hong Kong, Singapore and Canada and as a by-product, the index of the effectiveness of control in the later period can be acquired. It offers some quantitative indexes, which may help the further research in epidemic diseases.</p>
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<front>
<journal-meta>
<journal-id journal-id-type="nlm-ta">Chin Sci Bull</journal-id>
<journal-id journal-id-type="iso-abbrev">Chin. Sci. Bull</journal-id>
<journal-title-group>
<journal-title>Chinese Science Bulletin = Kexue Tongbao</journal-title>
</journal-title-group>
<issn pub-type="ppub">1001-6538</issn>
<issn pub-type="epub">1861-9541</issn>
<publisher>
<publisher-name>Science in China Press</publisher-name>
<publisher-loc>Beijing</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="pmid">32214715</article-id>
<article-id pub-id-type="pmc">7089478</article-id>
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<article-id pub-id-type="doi">10.1360/04we0073</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Articles</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>SARS epidemical forecast research in mathematical model</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Guanghong</surname>
<given-names>Ding</given-names>
</name>
<address>
<email>ghding@fudan.edu.cn</email>
</address>
<xref ref-type="aff" rid="Aff1"></xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Chang</surname>
<given-names>Liu</given-names>
</name>
<xref ref-type="aff" rid="Aff1"></xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Jianqiu</surname>
<given-names>Gong</given-names>
</name>
<xref ref-type="aff" rid="Aff1"></xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ling</surname>
<given-names>Wang</given-names>
</name>
<xref ref-type="aff" rid="Aff1"></xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ke</surname>
<given-names>Cheng</given-names>
</name>
<xref ref-type="aff" rid="Aff1"></xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Di</surname>
<given-names>Zhang</given-names>
</name>
<xref ref-type="aff" rid="Aff1"></xref>
</contrib>
<aff id="Aff1">
<institution-wrap>
<institution-id institution-id-type="GRID">grid.8547.e</institution-id>
<institution-id institution-id-type="ISNI">0000000101252443</institution-id>
<institution>Department of Mechanics and Engineering Science, Shanghai Research Center of Acupuncture and Meridians,</institution>
<institution>Fudan University,</institution>
</institution-wrap>
200433 Shanghai, China</aff>
</contrib-group>
<pub-date pub-type="epub">
<day>22</day>
<month>3</month>
<year>2013</year>
</pub-date>
<pub-date pub-type="ppub">
<year>2004</year>
</pub-date>
<volume>49</volume>
<issue>21</issue>
<fpage>2332</fpage>
<lpage>2338</lpage>
<history>
<date date-type="received">
<day>5</day>
<month>4</month>
<year>2004</year>
</date>
<date date-type="accepted">
<day>9</day>
<month>9</month>
<year>2004</year>
</date>
</history>
<permissions>
<copyright-statement>© Science in China Press 2004</copyright-statement>
<license>
<license-p>This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.</license-p>
</license>
</permissions>
<abstract id="Abs1">
<p>The SIJR model, simplified from the SEIJR model, is adopted to analyze the important parameters of the model of SARS epidemic such as the transmission rate, basic reproductive number. And some important parameters are obtained such as the transmission rate by applying this model to analyzing the situation in Hong Kong, Singapore and Canada at the outbreak of SARS. Then forecast of the transmission of SARS is drawn out here by the adjustment of parameters (such as quarantined rate) in the model. It is obvious that inflexion lies on the crunode of the graph, which indicates the big difference in transmission characteristics between the epidemic under control and not under control. This model can also be used in the comparison of the control effectiveness among different regions. The results from this model match well with the actual data in Hong Kong, Singapore and Canada and as a by-product, the index of the effectiveness of control in the later period can be acquired. It offers some quantitative indexes, which may help the further research in epidemic diseases.</p>
</abstract>
<kwd-group xml:lang="en">
<title>Keywords</title>
<kwd>SARS</kwd>
<kwd>quarantined rate</kwd>
<kwd>transmission rate</kwd>
<kwd>basic reproductive number</kwd>
<kwd>SIJR model</kwd>
<kwd>SEIJR model</kwd>
<kwd>inflexion</kwd>
</kwd-group>
<custom-meta-group>
<custom-meta>
<meta-name>issue-copyright-statement</meta-name>
<meta-value>© Science in China Press 2004</meta-value>
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</front>
<back>
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