Pooled testing for COVID-19 diagnosis by real-time RT-PCR

Abstract

Background & objectives: Public health and diagnostic laboratories are facing huge sample loads for COVID-19 diagnosis by real-time reverse transcription-polymerase chain reaction (RT-PCR). High sensitivity of optimized real-time RT-PCR assays makes pooled testing a potentially efficient strategy for resource utilization when positivity rates for particular regions or groups of individuals are low. We report here a comparative analysis of pooled testing for 5- and 10-sample pools by real-time RT-PCR across 10 COVID-19 testing laboratories in India. Methods: Ten virus research and diagnostic laboratories (VRDLs) testing for COVID-19 by real-time RT-PCR participated in this evaluation. At each laboratory, 100 nasopharyngeal swab samples including 10 positive samples were used to create 5- and 10-sample pools with one positive sample in each pool. RNA extraction and real-time RT-PCR for SARS-CoV-2-specific E gene target were performed for individual positive samples as well as pooled samples. Concordance between individual sample testing and testing in the 5- or 10-sample pools was calculated, and the variation across sites and by sample cycle threshold (C t ) values was analyzed. Results: A total of 110 each of 5- and 10-sample pools were evaluated. Concordance between the 5-sample pool and individual sample testing was 100 per cent in the C t value ≤30 cycles and 95.5 per cent for C t values ≤33 cycles. Overall concordance between the 5-sample pooled and individual sample testing was 88 per cent while that between 10-sample pool and individual sample testing was 66 per cent. Although the concordance rates for both the 5- and 10-sample pooled testing varied across laboratories, yet for samples with C t values ≤33 cycles, the concordance was ≥90 per cent across all laboratories for the 5-sample pools. Interpretation & conclusions: Results from this multi-site assessment suggest that pooling five samples for SARS-CoV-2 detection by real-time RT-PCR may be an acceptable strategy without much loss of sensitivity even for low viral loads, while with 10-sample pools, there may be considerably higher numbers of false negatives. However, testing laboratories should perform validations with the specific RNA extraction and RT-PCR kits in use at their centres before initiating pooled testing.

Pool testing on random and natural clusters of individuals: Optimisation of SARS-CoV-2 surveillance in the presence of low viral load samples

“…However, they suggest that, while high viral load samples seem to be detectable even in pool with 29 negative samples, particular attention should be deserved to specimens with high Ct: we were able to identify one sample with a Ct of 37.3 only in pool with 4 negative specimens. This is in line with results reported elsewhere which show a decreased sensitivity of pool testing in the presence of low viral load samples [ 15 , 18 , 19 ].…”

Testing of four-sample pools offers resource optimization without compromising diagnostic performance of real time reverse transcriptase-PCR assay for COVID-19

“…Accordingly, several groups, including us, have evaluated the cost and time benefit of pooled testing for COVID-19 diagnosis and found that pooling can substantially reduce the cost and turnaround time depending on the pool size and disease prevalence [ 11 – 13 ]. However, in many of these studies including ours [ 15 ], the authors observed a compromised diagnostic sensitivity when compared to the individualized testing [ 14 , 16 , 17 ] leaving behind a pertinent question; what is the perfect pool size for COVID-19 testing?…”

“…Performance of pool sample testing is reported to be influenced by pool size, number of positive sample(s) in the pool and Ct value(s) of the positive samples in the pool [ 14 , 15 , 20 ]. We adopted the strategy of simulated pooling with pre-determined proportion of positive samples in the 5-sample pool format as it was otherwise not feasible to ascertain the exact impact of variables like number of positive sample(s) and their Ct value(s) on the diagnostic sensitivity of rRT-PCR assay.…”

Fighting COVID-19 with Flexible Testing: Models and Insights

“…Recent studies mainly focused on investigating efficiency gains and the accuracy losses of different pooled algorithms [4][5][6][7][8][9][10][11][12][13][14][15][16][17] , such as multi-stages and multi-dimensions procedures. In this study, we focus on the Dorfman's classic two-stage procedure which is the most utilized algorithm in practice because of its simplicity and high efficiency.…”