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Performance characteristics of the SARS-CoV-2 Isothermal Molecular Assay for point-of-care molecular diagnosis of SARS-CoV-2

Onwuamah, C. K.; Shaibu, J. O.; Amoo, S. O.; Ahmed, A.-R. A.; Abimbola, B. S.; Audu, R. A.; Salako, B. L.

2025-03-30 infectious diseases
10.1101/2025.03.29.25324880 medRxiv
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BackgroundAccess to diagnostics was a significant challenge during the early stages of the COVID-19 pandemic, as laboratory reagents, supplies, and consumables were in short supply and high demand. Central laboratories, equipped with advanced real-time PCR equipment and highly skilled staff, worked long hours to produce test results for travellers, hospital patients, and the general public. We developed a SARS-CoV-2 molecular diagnostic assay suitable for point-of-care testing to address this diagnostic challenge. MethodsRecombinase amplification coupled with fluorescent detection was chosen as the technology, as it was freely available. Using a mobile fluorescent detection device ensures foolproof results interpretation, point-of-care testing and minimal footprint in facilities. Designed as a one-step reverse transcriptase real-time isothermal assay utilising the FAM and ROX channels. Specimens were tested using commercially available real-time PCR assays to evaluate the performance characteristics of the assay. ResultsThe SARS-CoV-2 Isothermal Molecular Assay (SIMA) detects the SARS-CoV-2 ORF1ab gene and a human gene to differentiate poor specimen collection. SIMA runs at 40{degrees}C for 36 minutes, with the first six minutes dedicated to reverse transcription. It has a detection limit of 555 RNA copies/mL. Highly positive specimens are detected within three minutes, but the 30-minute run time allows for detecting low-positive Specimens. Sensitivity was 95%, with 100% specificity, while precision ranged from 4% to 6% ConclusionsWe report the performance characteristics of SIMA, the first molecular diagnostics developed in Nigeria for SARS-CoV-2 point-of-care diagnosis. Its performance and utility give hope for rapid diagnosis and treatment in resource-constrained settings.

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