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Sample pooling, a population screening strategy for SARS-CoV2 to prevent future outbreak and mitigate the second-wave of infection of the virus

Sawarkar, S. S.; Victor, A.; Viotti, M.; Haran, S. P.; Verma, S.; Griffin, D.; Sams, J.

2020-11-03 infectious diseases
10.1101/2020.10.29.20204974 medRxiv
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ProblemHow do we manage treatment and stabilization in clinical settings and static population communities like assisted living facility settings of their patient or resident populations during and post the SARS-CoV-2 pandemic? ScopeThis proposal explores the possible and predicted changes to standard operating procedures to the facility management and associated landscape and focuses on series of deployments, during and post peak SARS-CoV-2 activity, and will outline possible models for the current medical facility model that we operate with. This article primarily focuses on non-emergency facility management. Assumptions and understanding of the fieldWith a reduction in the numbers nationally, patients are highly motivated and likely to seek non-emergency and planned medical procedural treatment as early as possible as social distancing measures are eased and restrictions on non-urgent procedures are lifted. Conclusions and next stepsAn initial pan-national shutdown and suspension of services was necessary in an effort to ensure that essential medical services and resources were not strained. The authors feel that a strategic resumption of regular non-emergency treatments around the United States and continued provision of services at care facilities is possible with innovative testing strategies like pooled screening of large populations at a manageable price point. Moreover, pooling as a strategy when used widely, would be extremely effective at predicting outbreaks of the virus and as an effect help in mitigating the spread of the virus in its "second-wave". We have developed one such innovative pooling strategy that can be easily deployed across laboratories and reduce the cost of population wide COVID-19 testing significantly

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