Author: Hayden C. Metsky; Catherine A. Freije; Tinna-Solveig F. Kosoko-Thoroddsen; Pardis C. Sabeti; Cameron Myhrvold
Title: CRISPR-based surveillance for COVID-19 using genomically-comprehensive machine learning design Document date: 2020_3_2
ID: 7tkvl894_2
Snippet: There are several challenges associated with surveillance during the current SARS-CoV-2 outbreak. First, high case counts overwhelm diagnostic testing capacity, underscoring the need for a rapid pipeline for sample processing [5, 6] . Second, SARS-CoV-2 is closely related to other important coronavirus subspecies and species, so detection assays can yield false positives if they are not exquisitely specific to SARS-CoV-2. Third, suspected SARS-Co.....
Document: There are several challenges associated with surveillance during the current SARS-CoV-2 outbreak. First, high case counts overwhelm diagnostic testing capacity, underscoring the need for a rapid pipeline for sample processing [5, 6] . Second, SARS-CoV-2 is closely related to other important coronavirus subspecies and species, so detection assays can yield false positives if they are not exquisitely specific to SARS-CoV-2. Third, suspected SARS-CoV-2 patients sometimes have a different respiratory viral infection or have co-infections with SARS-CoV-2 and other respiratory viruses [7] . Therefore, it is important to characterize these other pathogens, for both patient diagnostics and outbreak response.
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