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“Back to the future” projections for COVID-19 surges

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  • J Sunil Rao
  • Tianhao Liu
  • Daniel Andrés Díaz-Pachón

Abstract

We argue that information from countries who had earlier COVID-19 surges can be used to inform another country’s current model, then generating what we call back-to-the-future (BTF) projections. We show that these projections can be used to accurately predict future COVID-19 surges prior to an inflection point of the daily infection curve. We show, across 12 different countries from all populated continents around the world, that our method can often predict future surges in scenarios where the traditional approaches would always predict no future surges. However, as expected, BTF projections cannot accurately predict a surge due to the emergence of a new variant. To generate BTF projections, we make use of a matching scheme for asynchronous time series combined with a response coaching SIR model.

Suggested Citation

  • J Sunil Rao & Tianhao Liu & Daniel Andrés Díaz-Pachón, 2024. "“Back to the future” projections for COVID-19 surges," PLOS ONE, Public Library of Science, vol. 19(1), pages 1-16, January.
    • Handle: RePEc:plo:pone00:0296964
    DOI: 10.1371/journal.pone.0296964
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    References listed on IDEAS

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    3. Stoll, Hans R. & Whaley, Robert E., 1990. "The Dynamics of Stock Index and Stock Index Futures Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 25(4), pages 441-468, December.
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