TRACE-Omicron: Policy Counterfactuals to Inform Mitigation of COVID-19 Spread in the United States

  • David O'Gara
  • , Samuel F. Rosenblatt
  • , Laurent Hébert-Dufresne
  • , Rob Purcell
  • , Matt Kasman
  • , Ross A. Hammond

    Research output: Contribution to journalArticlepeer-review

    4 Scopus citations

    Abstract

    The Omicron wave is the largest wave of COVID-19 pandemic to date, more than doubling any other in terms of cases and hospitalizations in the United States. In this paper, a large-scale agent-based model of policy interventions that could have been implemented to mitigate the Omicron wave is presented. The model takes into account the behaviors of individuals and their interactions with one another within a nationally representative population, as well as the efficacy of various interventions such as social distancing, mask wearing, testing, tracing, and vaccination. We use the model to simulate the impact of different policy scenarios and evaluate their potential effectiveness in controlling the spread of the virus. The results suggest the Omicron wave could have been substantially curtailed via a combination of interventions comparable in effectiveness to extreme and unpopular singular measures such as widespread closure of schools and workplaces, and highlight the importance of early and decisive action.

    Original languageEnglish
    Article number2300147
    JournalAdvanced Theory and Simulations
    Volume6
    Issue number7
    DOIs
    StatePublished - Jul 2023

    Keywords

    • COVID-19
    • agent-based models
    • epidemiology
    • policy
    • vaccination

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