A scenario modeling pipeline for COVID-19 emergency planning

Joseph C. Lemaitre, Kyra H. Grantz, Joshua Kaminsky, Hannah R. Meredith, Shaun A. Truelove, Stephen A. Lauer, Lindsay T. Keegan, Sam Shah, Josh Wills, Kathryn Kaminsky, Javier Perez-Saez, Justin Lessler, Elizabeth C. Lee

Research output: Contribution to journalArticlepeer-review

Abstract

Coronavirus disease 2019 (COVID-19) has caused strain on health systems worldwide due to its high mortality rate and the large portion of cases requiring critical care and mechanical ventilation. During these uncertain times, public health decision makers, from city health departments to federal agencies, sought the use of epidemiological models for decision support in allocating resources, developing non-pharmaceutical interventions, and characterizing the dynamics of COVID-19 in their jurisdictions. In response, we developed a flexible scenario modeling pipeline that could quickly tailor models for decision makers seeking to compare projections of epidemic trajectories and healthcare impacts from multiple intervention scenarios in different locations. Here, we present the components and configurable features of the COVID Scenario Pipeline, with a vignette detailing its current use. We also present model limitations and active areas of development to meet ever-changing decision maker needs.

Original languageEnglish (US)
Article number7534
JournalScientific reports
Volume11
Issue number1
DOIs
StatePublished - Dec 2021

ASJC Scopus subject areas

  • General

Fingerprint Dive into the research topics of 'A scenario modeling pipeline for COVID-19 emergency planning'. Together they form a unique fingerprint.

Cite this