Boosting SARS-CoV-2 qRT-PCR detection combining pool sample strategy and mathematical modeling

Abstract

ABSTRACTqRT-PCR is the gold standard technique available for SARS-CoV-2 detection. However, the long test run time and costs associated with this type of molecular testing are a challenge in the actual pandemic scenario. Due to high testing demand, pooling sample strategy is an interesting approach to allow cost savings. We aim to evaluate pooling tests in experimental procedures, as well as perform in silico statistical modeling analysis validated with specimen samples obtained from a mass testing program of Industry Federation of the State of Rio de Janeiro (Brazil). Although the sensitivity reduction in samples pooled with 32 individuals was observed, the high-test sensitivity is maintained even when 16 and 8 samples were pooled. The in silico analysis showed high-cost savings in populations with positive rates lower than 15.0% according to the pool size. This data was validated with the results obtained in our mass testing program: statistical modeling predicted a cost saving of 48.0%, which in practice, was 51.5%, already considering the expenditures with pool sampling that were analyzed individually. Our data confirmed that mathematical modeling is a powerful strategy to improve the pooling approach for SARS-CoV-2 mass testing around the world while maintaining high sensitivity and robustness.