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COVID-19 mortality dynamics: The future modelled as a (mixture of) past(s)

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  • Samuel Soubeyrand
  • Mélina Ribaud
  • Virgile Baudrot
  • Denis Allard
  • Denys Pommeret
  • Lionel Roques

Abstract

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).

Suggested Citation

  • Samuel Soubeyrand & Mélina Ribaud & Virgile Baudrot & Denis Allard & Denys Pommeret & Lionel Roques, 2020. "COVID-19 mortality dynamics: The future modelled as a (mixture of) past(s)," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-9, September.
  • Handle: RePEc:plo:pone00:0238410
    DOI: 10.1371/journal.pone.0238410
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