Pooled RNA extraction and PCR assay for efficient SARS-CoV-2 detection

Roni Ben-Ami; Agnes Klochendler; Matan Seidel; Tal Sido; Ori Gurel-Gurevich; Moran Yassour; Eran Meshorer; Gil Benedek; Irit Fogel; Esther Oiknine-Djian; Asaf Gertler; Zeev Rotstein; Bruno Lavi; Yuval Dor; Dana G Wolf; Maayan Salton; Yotam Drier

is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.04.17.20069062 doi: medRxiv preprint probability of a sample to be positive by p (prevalence of detectable COVID-19 patients in the relevant population) and the pool size by n. The efficiency of the algorithms described above depends on both p and n. The best theoretical efficiency is (− " ( ) − (1 − ) " (1 − )) ,! [23] . The efficiency of Dorfman pooling is (1 + 1 / − (1 − ) 0 ) ,! [22] . We chose a pool size of n=8 samples as it allows low false negative rate ( Figure 1 ) and high efficiency for a wide range of COVID-19 prevalence ( Table 2 ). The prevalence of detectable COVID-19 in an asymptomatic population is estimated to be considerably below 1%, and indeed of the 2168 asymptomatic subjects tested in the present study only 0.23% were found positive. Therefore, efficiency is likely to be 5 -7.5.