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10.1017/dmp.2020.218

http://scihub22266oqcxt.onion/10.1017/dmp.2020.218
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32576313!7360945!32576313
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suck abstract from ncbi

pmid32576313      Disaster+Med+Public+Health+Prep 2020 ; 14 (5): e11-e15
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  • A Proposed COVID-19 Testing Algorithm #MMPMID32576313
  • Hart A; Bortolin M; Awoniyi O; Alhajjaj F; Ciottone GR
  • Disaster Med Public Health Prep 2020[Oct]; 14 (5): e11-e15 PMID32576313show ga
  • 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.
  • |*Algorithms[MESH]
  • |COVID-19 Testing/*methods/standards/trends[MESH]
  • |COVID-19/*diagnosis/epidemiology/transmission[MESH]
  • |Delivery of Health Care/methods[MESH]
  • |Disaster Planning/methods/trends[MESH]
  • |Humans[MESH]
  • |Pandemics/prevention & control[MESH]
  • |Physical Distancing[MESH]


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