Seroprevalence of SARS-CoV-2 antibodies in Saint Petersburg, Russia: a population-based study

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作者
Anton Barchuk
Dmitriy Skougarevskiy
Kirill Titaev
Daniil Shirokov
Yulia Raskina
Anastasia Novkunkskaya
Petr Talantov
Artur Isaev
Ekaterina Pomerantseva
Svetlana Zhikrivetskaya
Lubov Barabanova
Vadim Volkov
机构
[1] European University at St. Petersburg,Institute for Interdisciplinary Health Research
[2] Clinic “Scandinavia” (LLC Ava-Peter),N.N. Petrov National Research Medical Center of Oncology
[3] The Russian Academy of Sciences Commission for Counteracting the Falsification of Scientific Research,Health Sciences, Faculty of Social Sciences
[4] Center of Genetics and Reproductive Medicine GENETICO LLC,undefined
[5] Human Stem Cells Institute,undefined
[6] Pesochny,undefined
[7] Tampere University,undefined
[8] ITMO University,undefined
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摘要
Properly conducted serological survey can help determine infection disease true spread. This study aims to estimate the seroprevalence of SARS-CoV-2 antibodies in Saint Petersburg, Russia accounting for non-response bias. A sample of adults was recruited with random digit dialling, interviewed and invited for anti-SARS-CoV-2 antibodies. The seroprevalence was corrected with the aid of the bivariate probit model that jointly estimated individual propensity to agree to participate in the survey and seropositivity. 66,250 individuals were contacted, 6,440 adults agreed to be interviewed and blood samples were obtained from 1,038 participants between May 27 and June 26, 2020. Naïve seroprevalence corrected for test characteristics was 9.0% (7.2–10.8) by CMIA and 10.5% (8.6–12.4) by ELISA. Correction for non-response decreased estimates to 7.4% (5.7–9.2) and 9.1% (7.2–10.9) for CMIA and ELISA, respectively. The most pronounced decrease in bias-corrected seroprevalence was attributed to the history of any illnesses in the past 3 months and COVID-19 testing. Seroconversion was negatively associated with smoking status, self-reported history of allergies and changes in hand-washing habits. These results suggest that even low estimates of seroprevalence can be an overestimation. Serosurvey design should attempt to identify characteristics that are associated both with participation and seropositivity.
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