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A Proposed COVID-19 Testing Algorithm

Published online by Cambridge University Press:  24 June 2020

Alexander Hart*
Affiliation:
Beth Israel Deaconess Medical Center, Emergency Medicine, Boston, MA
Michelangelo Bortolin
Affiliation:
Beth Israel Deaconess Medical Center, Emergency Medicine, Boston, MA Servizio Emergenza Territoriale 118, Torino, Italy
Oluwafunbi Awoniyi
Affiliation:
Beth Israel Deaconess Medical Center, Emergency Medicine, Boston, MA
Fahad Alhajjaj
Affiliation:
Beth Israel Deaconess Medical Center, Emergency Medicine, Boston, MA Unaizah College of Medicine at Qassim University, Emergency Medicine, Unaizah, Saudi Arabia
Gregory R. Ciottone
Affiliation:
Beth Israel Deaconess Medical Center, Emergency Medicine, Boston, MA
*
Correspondence and reprint requests to Alexander Hart (e-mail: ahart1@bidmc.harvard.edu).
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Abstract

The 2019 coronavirus disease (COVID-19) pandemic has led to physical distancing measures in numerous countries in an attempt to control the spread. However, these measures are not without cost to the health and economies of the nations in which they are enacted. Nations are now looking for methods to remove physical distancing measures and return to full functioning. To prevent a massive second wave of infections, this must be done with a data-driven methodology. The purpose of this article is to propose an algorithm for COVID-19 testing that would allow for physical distancing to be scaled back in a stepwise manner, which limits ensuing infections and protects the capacity of the health care system.

Information

Type
Policy Analysis
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © 2020 Society for Disaster Medicine and Public Health, Inc.