The authors of this report provide a framework for assessing a model's suitability to address policy questions regarding the coronavirus disease 2019 pandemic in the Commonwealth of Virginia. The authors suggest assessment criteria for early-stage and late-stage models that consider the effects of the pandemic on behavior, policy, health outcomes, and the economy, informed by a review of available models and the relevant literature.

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A Framework for Assessing Models of the COVID-19 Pandemic to Inform Policymaking in Virginia

by Carter C. Price, Adrienne M. Propp

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Research Question

  1. What constitutes a suitable model for forecasting the relevant trends for COVID-19, assessing the effects of the pandemic, and informing policy responses?

Models have been widely used to inform policymakers about the implications of coronavirus disease 2019 (COVID-19) and the effects of policy responses to it. The authors of this report reviewed available models and the relevant literature to produce a framework for assessing a model's suitability for policymakers in the Commonwealth of Virginia.

Virginia's government first announced the presence of a COVID-19 case on March 7, 2020. The first interventions were put in place with only a few dozen confirmed cases having been reported, and Virginia had just over 1,000 confirmed cases when the stay-at-home order was implemented.

When assessing whether a model is suitable for informing policy, it is important to consider whether the data being used are relevant, whether the model design is appropriate, how the model has performed in the past, and the degree of transparency in the model. In this report, the authors examine assessment criteria for early-stage and late-stage models, taking into account the effects of the COVID-19 pandemic on behavior, policy, health outcomes, and the economy.

Key Findings

  • In the early stage, before the peak in the spread, modeling generally focuses on the timing and level of the peak. Statistical models are most suitable for forecasting trends, rather than comparing policies. Systems dynamics models are well suited for comparing policies, as long as the policies in question operate through mechanisms that are captured by the model.
  • Some models will cease to be useful after the early phase, or after certain policy responses to the pandemic have been phased in or out. New models might be needed as the policy environment changes.
  • Late-stage models—those examining trends after the peak—should incorporate economic, social, and other concerns, in addition to the health risks, so that policymakers can have an understanding of potential trade-offs.
  • Late-stage models should account for the major components of available reopening plans, including the gradual relaxation of physical-distancing measures, widespread testing and contact tracing, and improved health care capacity.
  • The extent and efficacy of such measures as widespread testing and contact tracing need to be considered in any model, because these measures likely will play a key role in successful reopening.
  • If and when a vaccine is developed, models should help inform the dissemination of the vaccine to minimize the risk of death from COVID-19.

Table of Contents

  • Chapter One

    Background

  • Chapter Two

    Assessing the Suitability of Modeling

  • Chapter Three

    Assessment Criteria for Early-Stage Models

  • Chapter Four

    Assessment Criteria for Late-Stage Models

  • Chapter Five

    Additional Considerations

  • Chapter Six

    Conclusions

  • Chapter Seven

    References

Research conducted by

This research was funded by the Virginia Department of Emergency Management and carried out jointly within the Access and Delivery Program in RAND Health Care and the Community Health and Environmental Policy Program within RAND Social and Economic Well-Being.

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