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            <name>Title</name>
            <description>A name given to the resource</description>
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                <text>Coronavirus</text>
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                <text>Dominio científico: Coronavirus</text>
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          <name>Title</name>
          <description>A name given to the resource</description>
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              <text>COVID-19 mortality dynamics: The future modelled as a (mixture of) past(s).</text>
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          <name>Creator</name>
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              <text>Samuel Soubeyrand, Mélina Ribaud, Virgile Baudrot, Denis Allard, Denys Pommeret, Lionel Roques</text>
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              <text>Discrepancies in population structures, decision making, health systems and numerous other factors result in various COVID-19-mortality dynamics at country scale, and make the forecast of deaths in a country under focus challenging. However, mortality dynamics of countries that are ahead of time implicitly include these factors and can be used as real-life competing predicting models. We precisely propose such a data-driven approach implemented in a publicly available web app timely providing mortality curves comparisons and real-time short-term forecasts for about 100 countries. Here, the approach is applied to compare the mortality trajectories of second-line and front-line European countries facing the COVID-19 epidemic wave. Using data up to mid-April, we show that the second-line countries generally followed relatively mild mortality curves rather than fast and severe ones. Thus, the continuation, after mid-April, of the COVID-19 wave across Europe was likely to be mitigated and not as strong as it was in most of the front-line countries first impacted by the wave (this prediction is corroborated by posterior data).</text>
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              <text>2020</text>
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          <name>Identifier</name>
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              <text>10.1371/journal.pone.0238410</text>
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          <name>Source</name>
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              <text>Epidemiology and Health</text>
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          <name>Publisher</name>
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              <text>Korean Society of Epidemiology</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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              <text>Science, Medicine</text>
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