Forecasting COVID-19 and Analyzing the Effect of Government Interventions

  1. Michael Lingzhi Li
  2. Hamza Tazi Bouardi
  3. Omar Skali Lami
  4. Thomas A. Trikalinos
  5. Nikolaos Trichakis
  6. Dimitris Bertsimas

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Abstract

Statement: Starting in December 2019, the COVID-19 pandemic is an unprecedented humanitarian crisis with millions of deaths worldwide. In “Forecasting COVID-19 and Analyzing the Effect of Government Interventions“, M. L. Li, H. Tazi Bouardi, O. Skali Lami, T. Trikalinos, N. Trichakis, and D. Bertsimas proposed a novel epidemiological model, DELPHI, that combined a novel modeling of government interventions, nonlinear optimization, and compartmental epidemiology models to forecast COVID-19 spread. They used DELPHI to demonstrate how lockdowns reduced the transmission by nearly 80%, whereas earlier societal action could have saved more than 75% of the lives lost in many countries. They also created a scenario analysis toolkit that utilized DELPHI’s modeling of interventions to generate “what if” scenarios under different future interventions. Janssen Pharmaceuticals utilized this toolkit to select optimized locations for the Phase III trial of their COVID-19 vaccine, leading to a trial acceleration of 8 weeks and saving thousands of lives.

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  1. Version published to 10.1287/opre.2022.2306
  2. Version published to 10.1101/2020.06.23.20138693v2 on medRxiv
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    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

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    • No protocol registration statement was detected.

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  4. Version published to 10.1101/2020.06.23.20138693v1 on medRxiv