Coordinated strategy for a model-based decision support tool for coronavirus disease, Utah, USA

Hannah R. Meredith, Emerson Arehart, Kyra H. Grantz, Alexander Beams, Theresa Sheets, Richard Nelson, Yue Zhang, Russell G. Vinik, Darryl Barfuss, Jacob C. Pettit, Keegan McCaffrey, Angela C. Dunn, Michael Good, Shannon Frattaroli, Matthew H. Samore, Justin Lessler, Elizabeth C. Lee, Lindsay T. Keegan

Research output: Contribution to journalReview articlepeer-review

Abstract

The coronavirus disease pandemic has highlighted the key role epidemiologic models play in supporting public health decision-making. In particular, these models provide estimates of outbreak potential when data are scarce and decision-making is critical and urgent. We document the integrated modeling response used in the US state of Utah early in the coronavirus disease pandemic, which brought together a diverse set of technical experts and public health and healthcare officials and led to an evidence-based response to the pandemic. We describe how we adapted a standard epidemiologic model; harmonized the outputs across modeling groups; and maintained a constant dialogue with policymakers at multiple levels of government to produce timely, evidence-based, and coordinated public health recommendations and interventions during the first wave of the pandemic. This framework continues to support the state's response to ongoing outbreaks and can be applied in other settings to address unique public health challenges.

Original languageEnglish (US)
Pages (from-to)1259-1265
Number of pages7
JournalEmerging infectious diseases
Volume27
Issue number5
DOIs
StatePublished - May 2021

ASJC Scopus subject areas

  • Epidemiology
  • Microbiology (medical)
  • Infectious Diseases

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