Author:
Lemaitre Joseph C.,Grantz Kyra H.,Kaminsky Joshua,Meredith Hannah R.,Truelove Shaun A.,Lauer Stephen A.,Keegan Lindsay T.,Shah Sam,Wills Josh,Kaminsky Kathryn,Perez-Saez Javier,Lessler Justin,Lee Elizabeth C.
Abstract
AbstractCoronavirus 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.
Funder
Swiss National Science Foundation
State of California
US Department of Health and Human Services
US Department of Homeland Security
US Office of Foreign Disaster Assistance
Centers for Disease Control and Prevention
Publisher
Springer Science and Business Media LLC
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