Analytic comparison between three high-throughput commercial SARS-CoV-2 antibody assays reveals minor discrepancies in a high-incidence population

Author:

Nasrallah Gheyath K.,Dargham Soha R.,Shurrab Farah,Al-Sadeq Duaa W.,Al-Jighefee Hadeel,Chemaitelly Hiam,Al Kanaani Zaina,Al Khal Abdullatif,Al Kuwari Einas,Coyle Peter,Jeremijenko Andrew,Kaleeckal Anvar Hassan,Latif Ali Nizar,Shaik Riyazuddin Mohammad,Rahim Hanan F. Abdul,Yassine Hadi M.,Al Kuwari Mohamed G.,Qotba Hamda,Al Romaihi Hamad Eid,Tang Patrick,Bertollini Roberto,Al-Thani Mohamed H.,Althani Asmaa A.,Abu-Raddad Laith J.

Abstract

AbstractPerformance of three automated commercial serological IgG-based assays was investigated for assessing SARS-CoV-2 “ever” (past or current) infection in a population-based sample in a high exposure setting. PCR and serological testing was performed on 394 individuals. SARS-CoV-2-IgG seroprevalence was 42.9% (95% CI 38.1–47.8%), 40.6% (95% CI 35.9–45.5%), and 42.4% (95% CI 37.6–47.3%) using the CL-900i, VidasIII, and Elecsys assays, respectively. Between the three assays, overall, positive, and negative percent agreements ranged between 93.2–95.7%, 89.3–92.8%, and 93.8–97.8%, respectively; Cohen’s kappa statistic ranged from 0.86 to 0.91; and 35 specimens (8.9%) showed discordant results. Among all individuals, 12.5% (95% CI 9.6–16.1%) had current infection, as assessed by PCR. Of these, only 34.7% (95% CI 22.9–48.7%) were seropositive by at least one assay. A total of 216 individuals (54.8%; 95% CI 49.9–59.7%) had evidence of ever infection using antibody testing and/or PCR during or prior to this study. Of these, only 78.2%, 74.1%, and 77.3% were seropositive in the CL-900i, VidasIII, and Elecsys assays, respectively. All three assays had comparable performance and excellent agreement, but missed at least 20% of individuals with past or current infection. Commercial antibody assays can substantially underestimate ever infection, more so when infection rates are high.

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

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