RPA-Based Method For The Detection Of SARS-CoV2

Background: Coronavirus disease 2019 (COVID-19) is a highly infectious disease with significant mortality, morbidity, and far-reaching economic and social disruptions. Testing is key in the fight against COVID-19 disease. The gold standard for COVID-19 testing is the reverse transcription polymerase chain reaction (RT-PCR) test. RT-PCR requires highly specialized, expensive, and advanced bulky equipment that is difficult to use in the field or in a point of care setting. There is need for a simpler, inexpensive, convenient, portable and accurate test. Our aims were to: (i) design primer-probe pairs for use in isothermal amplification of the S1, ORF3 and ORF8 regions of the SARS-CoV2 virus; (ii) optimize the recombinase polymerase amplification (RPA) assay for the isothermal amplification of the named SARS-COV2 regions; (iii) detect amplification products on a lateral flow device. and (ii) perform a pilot field validation of RPA on RNA extracted from nasopharyngeal swabs. Results: Assay validation was done at the National Reference Lab (NRL) at the Rwanda Biomedical Center (RBC) in Rwanda. Results were compared to an established, WHO-approved rRT-PCR laboratory protocol. The assay provides a faster and cheaper alternative to rRT-PCR with 100% sensitivity, 93% specificity, and positive and negative predictive agreements of 100% and 93% respectively. Conclusion: To the best of our knowledge, this is the first in-field and comparative laboratory validation of RPA for COVID-19 disease in low resource settings. Further standardization will be required for deployment of the RPA assay in field settings. Keywords: Recombinase Polymerase Amplification, COVID-19

A strategy for finding people infected with SARS-CoV-2: optimizing pooled testing at low prevalence

Suppressing SARS-CoV-2 will likely require the rapid identification and isolation of infected individuals, on an ongoing basis. RT-PCR (reverse transcription polymerase chain reaction) tests are accurate but costly, making regular testing of every individual expensive. The costs are a challenge for all countries and particularly for developing countries. Cost reductions can be achieved by pooling (or combining) subsamples and testing them in groups. We propose an algorithm for pooling subsamples based on the geometry of a hypercube that, at low prevalence, uniquely identifies infected individuals in a small number of tests. We discuss the optimal group size and explain why, given the highly infectious nature of the disease, largely parallel searches are preferred. We report proof of concept experiments in which a positive subsample was detected even when diluted a hundred-fold with negative subsamples. Using these methods, the costs of mass testing could be reduced by a large factor. If infected individuals are quickly and effectively quarantined, the prevalence will fall and so will the cost of regular, mass testing. Such a strategy provides a possible pathway to the longterm elimination of SARS-CoV-2. Field trials of our approach are now under way in Rwanda.