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            <name>Title</name>
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                <text>Coronavirus</text>
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                <text>Dominio científico: Coronavirus</text>
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          <name>Title</name>
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              <text>Prediction of the Epidemic Peak of Coronavirus Disease in Japan, 2020</text>
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          <name>Creator</name>
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              <text>Toshikazu Kuniya</text>
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          <name>Description</name>
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              <text>The first case of coronavirus disease 2019 (COVID-19) in Japan was reported on 15 January 2020 and the number of reported cases has increased day by day. The purpose of this study is to give a prediction of the epidemic peak for COVID-19 in Japan by using the real-time data from 15 January to 29 February 2020. Taking into account the uncertainty due to the incomplete identification of infective population, we apply the well-known SEIR compartmental model for the prediction. By using a least-square-based method with Poisson noise, we estimate that the basic reproduction number for the epidemic in Japan is      R 0  = 2.6     (    95 %    CI,     2.4    &amp;#8722;    2.8    ) and the epidemic peak could possibly reach the early-middle summer. In addition, we obtain the following epidemiological insights: (1) the essential epidemic size is less likely to be affected by the rate of identification of the actual infective population; (2) the intervention has a positive effect on the delay of the epidemic peak; (3) intervention over a relatively long period is needed to effectively reduce the final epidemic size.</text>
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              <text>2020</text>
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          <name>Subject</name>
          <description>The topic of the resource</description>
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              <text>COVID-19, seir compartmental model, Basic reproduction number</text>
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          <name>Identifier</name>
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              <text>DOI: 10.3390/jcm9030789</text>
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              <text>Journal of Clinical Medicine</text>
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          <name>Publisher</name>
          <description>An entity responsible for making the resource available</description>
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              <text>MDPI AG</text>
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          <name>Coverage</name>
          <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
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            <elementText elementTextId="14479">
              <text>Medicine</text>
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          <name>Language</name>
          <description>A language of the resource</description>
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              <text>EN</text>
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