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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">JDS</journal-id>
      <journal-title-group>
        <journal-title>Journal of Data Science</journal-title>
      </journal-title-group>
      <issn pub-type="epub">1680-743X</issn>
      <issn pub-type="ppub">1680-743X</issn>
      <publisher>
        <publisher-name>SOSRUC</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="publisher-id">JULY4</article-id>
      <article-id pub-id-type="doi">10.6339/JDS.202007_18(3).0010</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Tracking Reproductivity of COVID-19 Epidemic in China with Varying Coefficient SIR Model</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Sun</surname>
            <given-names>Haoxuan</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_000"/>
        </contrib>
        <aff id="j_JDS_aff_000">Center for Data Science, Peking University, Beijing, China</aff>
        <contrib contrib-type="author">
          <name>
            <surname>Qiu</surname>
            <given-names>Yumou</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_001"/>
        </contrib>
        <aff id="j_JDS_aff_001">Department of Statistics, Iowa State University, Ames, Iowa, USA</aff>
        <contrib contrib-type="author">
          <name>
            <surname>Yan</surname>
            <given-names>Han</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_002"/>
        </contrib>
        <aff id="j_JDS_aff_002">School of Mathematical Sciences, Sichuan University, Chengdu, Sichuan, China</aff>
        <contrib contrib-type="author">
          <name>
            <surname>Huang</surname>
            <given-names>Yaxuan</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_003"/>
        </contrib>
        <aff id="j_JDS_aff_003">Yuanpei College, Peking University, Beijing, China</aff>
        <contrib contrib-type="author">
          <name>
            <surname>Zhu</surname>
            <given-names>Yuru</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_004"/>
        </contrib>
        <aff id="j_JDS_aff_004">Center for Statistical Science, Peking University, Beijing, China</aff>
        <contrib contrib-type="author">
          <name>
            <surname>Gu</surname>
            <given-names>Jia</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_005"/>
        </contrib>
        <aff id="j_JDS_aff_005">Center for Statistical Science, Peking University, Beijing, China</aff>
        <contrib contrib-type="author">
          <name>
            <surname>Chen</surname>
            <given-names>Songxi</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_006"/>
        </contrib>
        <aff id="j_JDS_aff_006">Center for Statistical Science, Peking University, Beijing, China
Guanghua School of Management, Peking University, Beijing China</aff>
      </contrib-group>
      <volume>18</volume>
      <issue>3</issue>
      <fpage>455</fpage>
      <lpage>472</lpage>
      <permissions>
        <ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/>
      </permissions>
      <abstract>
        <p>We propose a varying coefficient Susceptible-Infected-Removal (vSIR) model that allows changing infection and removal rates for the latest corona virus (COVID-19) outbreak in China. The vSIR model together with proposed estimation procedures allow one to track the reproductivity of the COVID-19 through time and to assess the effectiveness of the control measures implemented since Jan 23 2020 when the city of Wuhan was lockdown followed by an extremely high level of self-isolation in the population. Our study finds that the reproductivity of COVID-19 had been significantly slowed down in the three weeks from January 27th to February 17th with 96.3% and</p>
        <p>95.1% reductions in the effective reproduction numbers R among the 30 provinces and 15 Hubei cities, respectively. Predictions to the ending times and the total numbers of infected are made under three scenarios of the removal rates. The paper provides a timely model and associated estimation and prediction methods which may be applied in other countries to track, assess and predict the epidemic of the COVID-19 or other infectious diseases</p>
      </abstract>
      <kwd-group>
        <label>Keywords</label>
        <kwd>epidemic assessment</kwd>
        <kwd>estimation of basic reproductive number</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
