Pooling sample can increase SARS-CoV-2 capacity testing in resource limiting settings

ABSTRACT

Introduction/ Background: The global spread of SARS-CoV-2 and high demand for reagents may cause a challenge in procurement and the testing process, impacting turnaround times and the epidemiological data for optimal response mainly in low-income countries. To overcome this bottleneck, evaluating pooling system in the testing could be a solution Methods: For pooling strategy, 100 ul of each sample were pooled for up to 4 samples and extract using the same technology. The swabs were Oropharyngeal and nasopharyngeal swabs collected from individual attending clinic at Thies région and tested by Real-Time PCR after inactivation and RNA extraction using KingFisher Flex machine from ThermoFisher according to the manufacturer. SARS-CoV-2 detection were done using AllplexTM 2019-nCoV assay from Seegene targetting N, E, RdRp Gene in Biorad CFX96. All Samples are test individually and pooled. Ct values were compared between positives samples and result obtained with pooling. Results: We include in this analysis 43 pool of 4 samples each including 54 positive SARS-CoV-2 pooled with 114 negative samples and 40 pool of 4 negatives samples. Among positives sample included in the pool, 19 had Ct between 17 and 25, 23 between 25 to 30 and 12 had more than 30. Our result confirms that all 54 positives samples pooled in negatives samples were detected by pooling. The pooling was associated with a loss of 0.8 average of Ct ranging between -1.2 to 2.8. All samples individually negatives were also negatives in the pooling. The complete analysis is ongoing. Impact This study indicates that pooling sample is practical and can be used for community surveillance, testing of low-risk populations, and in resourcelimited settings to mitigate reagent stock out. This can allow to reduce testing turnaround times and faster public health authorities' response to the global pandemic, especially in low-income countries. Conclusion: Our preliminary data confirms that pooling sample correctly identifies SARS-CoV-2 infected individual in 100% of our sample with an expected average of loss of ct of 0.8. This strategy can increase testing throughput in RLS and reduce turnaround time.