High concordance in SARSCoV- 2 detection between automated (Abbott m2000) and manual (DaAn gene) RT-PCR systems: The EDCTP PERFECT-Study in Cameroon
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Molecular diagnosis of COVID-19 is critical to the control of the pandemic, which is a major threat to global health. Several molecular tests have been validated by WHO, but would require operational evaluation in the field to ensure their interoperability in diagnosis. In order to ensure field interoperability in molecular assays for detection of SARS-CoV-2 RNA, we evaluated the diagnostic concordance of SARS-CoV-2 between an automated (Abbott) and a manual (DaAn gene) realtime PCR (rRT-PCR), two commonly used assays in Africa. A comparative study was conducted on 287 nasopharyngeal specimens at the Chantal BIYA International Reference Centre (CIRCB) in Yaounde-Cameroon. Samples were tested in parallel with Abbott and DaAn gene rRT-PCR, and performance characteristics were evaluated by Cohen’s coefficient and Spearman’s correlation. A total of 273 participants [median age (IQR) 36 (26-46) years] and 14 EQA specimens were included in the study. Positivity was on 30.0% (86/287) Abbott and 37.6% (108/287) DaAn gene. Overall agreement was 82.6% (237/287), with k=0.82 (95%CI: 0.777-0.863), indicating an excellent diagnostic agreement. The positive and negative agreement was 66.67% (72/108) and 92.18 % (165/179) respectively. Regarding Viral Load (VL), positive agreement was 100% for samples with high VLs (CT<20). Among positive SARS-CoV-2 cases, the mean difference in Cycle Threshold (CT) for the manual and Cycle Number (CN) for the automated was 6.75±0.3. The excellent agreement (>80%) between the Abbott and DaAn gene rRTPCR platforms supports interoperability between the two assays. Discordance occurs at low-VL, thus underscoring these tools as efficient weapons in limiting SARS-CoV-2 community transmission.
Copyright (c) 2022 Nadine Nguendjoung Fainguem, Joseph Fokam, Ezechiel Ngoufack Jagni Semengue, Alex Durand Nka, Désiré Takou, Joshua Ageboh Nkembi-leke, Claudia Alteri, Luna Colagrossi, Roméo Bouba Yagai, Collins Ambe Chenwi, Michel Carlos Tchouaket Tommo, Grace Angong Beloumou, Aude Christelle Ka’e, Sandrine Claire Ndjeyep Djupsa, Aissatou Abba, Laeticia Grace Heunko Yatchou, Krystel Nnomo Zam, Rachel Kamgaing, Samuel Martin Sosso, Lucien Mama, Nicaise Ndembi, Vittorio Colizzi, Carlo-Federico Perno, Giulia Cappelli, Alexis Ndjolo
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