Evaluation of serological lateral flow assays for severe acute respiratory syndrome coronavirus-2

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Sejal Jain

Yikai Kuo

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Tal Gilboa

Maia Norman

Daimon P Simmons

Jina Ko

Edmond Wong

Wen Zhou

Megan Kwock

Aditi Hazra

Leo Cheng

Sally Zhou

Petr Jarolim

David Walt

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BackgroundCOVID-19 has resulted in significant morbidity and mortality worldwide. Lateral flow assays can detect anti-Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) antibodies to monitor transmission. However, standardized evaluation of their accuracy and tools to aid in interpreting results are needed. MethodsWe evaluated 20 IgG and IgM assays selected from available tests in April 2020. We evaluated the assays performance using 56 pre-pandemic negative and 56 SARS-CoV-2-positive plasma samples, collected 10-40 days after symptom onset, confirmed by a molecular test and analyzed by an ultra-sensitive immunoassay. Finally, we developed a user-friendly web app to extrapolate the positive predictive values based on their accuracy and local prevalence. ResultsCombined IgG+IgM sensitivities ranged from 33.9% to 94.6%, while combined specificities ranged from 92.6% to 100%. The highest sensitivities were detected in Lumiquick for IgG (98.2%), BioHit for both IgM (96.4%), and combined IgG+IgM sensitivity (94.6%). Furthermore, 11 LFAs and 8 LFAs showed perfect specificity for IgG and IgM, respectively, with 15 LFAs showing perfect combined IgG+IgM specificity. Lumiquick had the lowest estimated limit-of-detection (LOD) (0.1 g/mL), followed by a similar LOD of 1.5 g/mL for CareHealth, Cellex, KHB, and Vivachek. ConclusionWe provide a public resource of the accuracy of select lateral flow assays with potential for home testing. The cost-effectiveness, scalable manufacturing process, and suitability for self-testing makes LFAs an attractive option for monitoring disease prevalence and assessing vaccine responsiveness. Our web tool provides an easy-to-use interface to demonstrate the impact of prevalence and test accuracy on the positive predictive values.

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