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Vaughan A, Duffell E, Freidl GS, Lemos DS, Nardone A, Valenciano M, Subissi L, Bergeri I, K Broberg E, Penttinen P, Pebody R, Keramarou M. Systematic review of seroprevalence of SARS-CoV-2 antibodies and appraisal of evidence, prior to the widespread introduction of vaccine programmes in the WHO European Region, January-December 2020. BMJ Open 2023; 13:e064240. [PMID: 37931969 PMCID: PMC10632881 DOI: 10.1136/bmjopen-2022-064240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 09/04/2023] [Indexed: 11/08/2023] Open
Abstract
OBJECTIVES Systematic review of SARS-CoV-2 seroprevalence studies undertaken in the WHO European Region to measure pre-existing and cumulative seropositivity prior to the roll out of vaccination programmes. DESIGN A systematic review of the literature. DATA SOURCES We searched MEDLINE, EMBASE and the preprint servers MedRxiv and BioRxiv in the WHO 'COVID-19 Global literature on coronavirus disease' database using a predefined search strategy. Articles were supplemented with unpublished WHO-supported Unity-aligned seroprevalence studies and other studies reported directly to WHO Regional Office for Europe and European Centre for Disease Prevention and Control. ELIGIBILITY CRITERIA Studies published before the widespread implementation of COVID-19 vaccination programmes in January 2021 among the general population and blood donors, at national and regional levels. DATA EXTRACTION AND SYNTHESIS At least two independent researchers extracted the eligible studies; a third researcher resolved any disagreements. Study risk of bias was assessed using a quality scoring system based on sample size, sampling and testing methodologies. RESULTS In total, 111 studies from 26 countries published or conducted between 1 January 2020 and 31 December 2020 across the WHO European Region were included. A significant heterogeneity in implementation was noted across the studies, with a paucity of studies from the east of the Region. Sixty-four (58%) studies were assessed to be of medium to high risk of bias. Overall, SARS-CoV-2 seropositivity prior to widespread community circulation was very low. National seroprevalence estimates after circulation started ranged from 0% to 51.3% (median 2.2% (IQR 0.7-5.2%); n=124), while subnational estimates ranged from 0% to 52% (median 5.8% (IQR 2.3%-12%); n=101), with the highest estimates in areas following widespread local transmission. CONCLUSIONS The low levels of SARS-CoV-2 antibody in most populations prior to the start of vaccine programmes underlines the critical importance of targeted vaccination of priority groups at risk of severe disease, while maintaining reduced levels of transmission to minimise population morbidity and mortality.
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Affiliation(s)
- Aisling Vaughan
- World Health Organization Regional Office for Europe, Copenhagen, Denmark
| | - Erika Duffell
- European Centre for Disease Prevention and Control, Solna, Sweden
| | - Gudrun S Freidl
- World Health Organization Regional Office for Europe, Copenhagen, Denmark
| | - Diogo Simão Lemos
- World Health Organization Regional Office for Europe, Copenhagen, Denmark
| | | | | | | | | | - Eeva K Broberg
- European Centre for Disease Prevention and Control, Solna, Sweden
| | - Pasi Penttinen
- European Centre for Disease Prevention and Control, Solna, Sweden
| | - Richard Pebody
- World Health Organization Regional Office for Europe, Copenhagen, Denmark
| | - Maria Keramarou
- European Centre for Disease Prevention and Control, Solna, Sweden
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Totolian AA, Smirnov VS, Krasnov AA, Ramsay ES, Dedkov VG, Popova AY. COVID-19 Incidence Proportion as a Function of Regional Testing Strategy, Vaccination Coverage, and Vaccine Type. Viruses 2023; 15:2181. [PMID: 38005859 PMCID: PMC10675075 DOI: 10.3390/v15112181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Revised: 10/25/2023] [Accepted: 10/26/2023] [Indexed: 11/26/2023] Open
Abstract
Introduction: The COVID-19 pandemic has become a serious challenge for humanity almost everywhere globally. Despite active vaccination around the world, the incidence proportion in different countries varies significantly as of May 2022. The reason may be a combination of demographic, immunological, and epidemiological factors. The purpose of this study was to analyze possible relationships between COVID-19 incidence proportion in the population and the types of SARS-CoV-2 vaccines used in different countries globally, taking into account demographic and epidemiological factors. Materials and methods: An initial database was created of demographic and immunoepidemiological information about the COVID-19 situation in 104 countries collected from published official sources and repository data. The baseline included, for each country, population size and density; SARS-CoV-2 testing coverage; vaccination coverage; incidence proportion; and a list of vaccines that were used, including their relative share among all vaccinations. Subsequently, the initial data set was stratified by population and vaccination coverage. The final data set was subjected to statistical processing both in general and taking into account population testing coverage. Results: After formation of the final data set (including 53 countries), it turned out that reported COVID-19 case numbers correlated most strongly with testing coverage and the proportions of vaccine types used, specifically, mRNA (V1); vector (V2); peptide/protein (V3); and whole-virion/inactivated (V4). Due to the fact that an inverse correlation was found between 'reported COVID-19 case numbers' with V2, V3, and V4, these three vaccine types were also combined into one analytic group, 'non-mRNA group' vaccines (Vnmg). When the relationship between vaccine type and incidence proportion was examined, minimum incidence proportion was noted at V1:Vnmg ratios (%:%) from 0:100 to 30:70. Maximum incidence proportion was seen with V1:Vnmg from 80:20 to 100:0. On the other hand, we have shown that the number of reported COVID-19 cases in different countries largely depends on testing coverage. To offset this factor, countries with low and extremely high levels of testing were excluded from the data set; it was then confirmed that the largest number of reported COVID-19 cases occurred in countries with a dominance of V1 vaccines. The fewest reported cases were seen in countries with a dominance of Vnmg vaccines. Conclusion: In this paper, we have shown for the first time that the level of reported COVID-19 incidence proportion depends not only on SARS-CoV-2 testing and vaccination coverage, which is quite logical, but probably also on the vaccine types used. With the same vaccination level and testing coverage, those countries that predominantly use vector and whole-virion vaccines feature incidence proportion that is significantly lower than countries that predominantly use mRNA vaccines.
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Affiliation(s)
- Areg A. Totolian
- Saint Petersburg Pasteur Institute, 197101 St. Petersburg, Russia; (A.A.T.); (V.S.S.); (A.A.K.); (E.S.R.)
| | - Viacheslav S. Smirnov
- Saint Petersburg Pasteur Institute, 197101 St. Petersburg, Russia; (A.A.T.); (V.S.S.); (A.A.K.); (E.S.R.)
| | - Alexei A. Krasnov
- Saint Petersburg Pasteur Institute, 197101 St. Petersburg, Russia; (A.A.T.); (V.S.S.); (A.A.K.); (E.S.R.)
| | - Edward S. Ramsay
- Saint Petersburg Pasteur Institute, 197101 St. Petersburg, Russia; (A.A.T.); (V.S.S.); (A.A.K.); (E.S.R.)
| | - Vladimir G. Dedkov
- Saint Petersburg Pasteur Institute, 197101 St. Petersburg, Russia; (A.A.T.); (V.S.S.); (A.A.K.); (E.S.R.)
| | - Anna Y. Popova
- Federal Service for Supervision of Consumer Rights Protection and Human Welfare, 127994 Moscow, Russia;
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Popova AY, Totolian AA. Methodology for assessing herd immunity to the SARS-CoV-2 virus in the context of the COVID-19 pandemic. RUSSIAN JOURNAL OF INFECTION AND IMMUNITY 2021. [DOI: 10.15789/2220-7619-mfa-1770] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Serological monitoring of the study of population immunity to the SARS-CoV-2 virus in the context of COVID-19 pandemic is a necessary component in epidemiological surveillance, since population epidemiological wellbeing in a context of COVID-19 is determined by state of population immunity to the SARS-CoV-2 virus. The population herd immunity is the limiting factor in spread of the SARS-CoV-2 virus. Information on the state of population immunity is necessary to make a forecast for development of epidemiological situation, as well as to plan measures for specific and non-specific prevention of COVID-19. In this regard, the study of population immunity during the pandemic is necessary to predict development of the epidemic and identify features of epidemic process in any certain region and in the country in general. In May 2020, the Rospotrebnadzor program “Assessment of population immunity to the SARS-CoV-2 virus in the population of the Russian Federation in the context of the COVID-19 pandemic” was developed taking into account WHO recommendations in the format of a longitudinal cohort study with age stratification: at the first stage, a cohort of volunteers is formed; at the second and subsequent stages, the cohort of volunteers formed at the first stage is subject to examination; the number of stages depends on the epidemiological situation. In addition to age-related randomization while forming a cohort, at the first stage, the principle of population coverage uniformity was observed, the participation of volunteers from one institution was excluded, and the use of donated blood or patient blood from medical organizations was excluded. The survey was carried out among 7 age groups of healthy children and adults, regardless present or absent previous COVID-19 disease. Due to the fact that the population study is carried out in the context of COVID-19 pandemic, the optimal timing for collecting biomaterial at each stage is no more than 5–7 days. Questioning, selection of volunteers, their registration for blood donation, as well as processing of the results at the first stage, as well as the implementation of the second and subsequent stages of the Program are carried out only by using cloud service technology. This Program and the technology for its implementation have been successfully tested in 26 regions of the Russian Federation during the implementation of four stages from June 2020 to March 2021. Thus, at present, Rospotrebnadzor has developed a methodology and created an effectively working system of serological monitoring to assess level of herd immunity in different regions of the Russian Federation to predict the epidemiological situation, develop recommendations, and plan vaccination.
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Popova AY, Smirnov VS, Andreeva EE, Babura EA, Balakhonov SV, Bashketova NS, Bugorkova SA, Bulanov MV, Valeullina NN, Vetrov VV, Goryaev DV, Detkovskaya TN, Ezhlova EB, Zaitseva NN, Istorik OA, Kovalchuk IV, Kozlovskikh DN, Kombarova SY, Kurganova OP, Lomovtsev AE, Lukicheva LA, Lyalina LV, Melnikova AA, Mikailova OM, Noskov AK, Noskova LN, Oglezneva EE, Osmolovskaya TP, Patyashina MA, Penkovskaya NA, Samoilova LV, Stepanova TF, Trotsenko OE, Totolian AA. SARS-CoV-2 Seroprevalence Structure of the Russian Population during the COVID-19 Pandemic. Viruses 2021. [PMID: 34452512 DOI: 10.3390/v13081648.pmid:34452512] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/04/2023] Open
Abstract
The SARS-CoV-2 pandemic, which came to Russia in March 2020, is accompanied by morbidity level changes and can be tracked using serological monitoring of a representative population sample from Federal Districts (FDs) and individual regions. In a longitudinal cohort study conducted in 26 model regions of Russia, distributed across all FDs, we investigated the distribution and cumulative proportions of individuals with antibodies (Abs) to the SARS-CoV-2 nucleocapsid antigen (Ag), in the period from June to December 2020, using a three-phase monitoring process. In addition, during the formation of the cohort of volunteers, the number of seropositive convalescents, persons who had contact with patients or COVID-19 convalescents, and the prevalence of asymptomatic forms of infection among seropositive volunteers were determined. According to a uniform methodology, 3 mL of blood was taken from the examined individuals, and plasma was separated, from which the presence of Abs to nucleocapsid Ag was determined on a Thermo Scientific Multiascan FC device using the "ELISA anti-SARS-CoV-2 IgG" reagent set (prod. Scientific Center for Applied Microbiology and Biotechnology), in accordance with the developer's instructions. Volunteers (74,158) were surveyed and divided into seven age groups (1-17, 18-29, 30-39, 40-49, 59-59, 60-69, and 70+ years old), among whom 14,275 were identified as having antibodies to SARS-CoV-2. The average percent seropositive in Russia was 17.8% (IQR: 8.8-23.2). The largest proportion was found among children under 17 years old (21.6% (IQR: 13.1-31.7). In the remaining groups, seroprevalence ranged from 15.6% (IQR: 8-21.1) to 18.0% (IQR: 13.4-22.6). During monitoring, three (immune) response groups were found: (A) groups with a continuous increase in the proportion of seropositive; (B) those with a slow rate of increase in seroprevalence; and (C) those with a two-phase curve, wherein the initial increase was replaced by a decrease in the percentage of seropositive individuals. A significant correlation was revealed between the number of COVID-19 convalescents and contact persons, and between the number of contacts and healthy seropositive volunteers. Among the seropositive volunteers, more than 93.6% (IQR: 87.1-94.9) were asymptomatic. The results show that the COVID-19 pandemic is accompanied by an increase in seroprevalence, which may be important for the formation of herd immunity.
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Affiliation(s)
- Anna Y Popova
- Federal Service for Supervision of Consumer Rights Protection and Human Welfare, 127994 Moscow, Russia
| | | | | | - Elena A Babura
- Rospotrebnadzor Administration in the Kaliningrad Region, 236040 Kaliningrad, Russia
| | | | | | | | - Maxim V Bulanov
- Center for Hygiene and Epidemiology of the Vladimir Region, 600005 Vladimir, Russia
| | - Natalia N Valeullina
- Rospotrebnadzor Administration in the Chelyabinsk Region, 454091 Chelyabinsk, Russia
| | | | - Dmitriy V Goryaev
- Rospotrebnadzor Administration in the Krasnoyarsk Territory, 660049 Krasnoyarsk, Russia
| | | | - Elena B Ezhlova
- Federal Service for Supervision of Consumer Rights Protection and Human Welfare, 127994 Moscow, Russia
| | - Natalia N Zaitseva
- Nizhny Novgorod I. N. Blokhina Research Institute of Epidemiology and Microbiology, 603950 Nizhny Novgorod, Russia
| | - Olga A Istorik
- Rospotrebnadzor Administration in the Leningrad Region, 192029 St. Petersburg, Russia
| | - Irina V Kovalchuk
- Rospotrebnadzor Administration in the Stavropol Territory, 355008 Stavropol, Russia
| | - Dmitriy N Kozlovskikh
- Rospotrebnadzor Administration in the Sverdlovsk Region, 620078 Yekaterinburg, Russia
| | - Svetlana Y Kombarova
- G. N. Gabrichevsky Moscow Research Institute for Epidemiology and Microbiology, 125212 Moscow, Russia
| | - Olga P Kurganova
- Rospotrebnadzor Administration in the Amur Region, 675002 Blagoveshchensk, Russia
| | | | - Lena A Lukicheva
- Rospotrebnadzor Administration in the Murmansk Region, 183038 Murmansk, Russia
| | | | - Albina A Melnikova
- Federal Service for Supervision of Consumer Rights Protection and Human Welfare, 127994 Moscow, Russia
| | - Olga M Mikailova
- Rospotrebnadzor Administration in the Moscow Region, 141014 Mytishchi, Moscow Region, Russia
| | - Alexei K Noskov
- Rostov-on-Don Research Anti-Plague Institute, 344000 Rostov-on-Don, Russia
| | - Ludmila N Noskova
- Rospotrebnadzor Administration for the Astrakhan Region, 414057 Astrakhan, Russia
| | - Elena E Oglezneva
- Rospotrebnadzor Administration in the Belgorod Region, 308023 Belgorod, Russia
| | | | - Marina A Patyashina
- Rospotrebnadzor Administration in the Republic of Tatarstan, 420111 Kazan, Russia
| | | | - Lada V Samoilova
- Rospotrebnadzor Administration in the Novosibirsk Region, 630132 Novosibirsk, Russia
| | - Tatyana F Stepanova
- Tyumen Research Institute of Regional Infectious Pathology, 625026 Tyumen, Russia
| | - Olga E Trotsenko
- Khabarovsk Research Institute of Epidemiology and Microbiology, 680000 Khabarovsk, Russia
| | - Areg A Totolian
- Saint Petersburg Pasteur Institute, 197101 St. Petersburg, Russia
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5
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SARS-CoV-2 Seroprevalence Structure of the Russian Population during the COVID-19 Pandemic. Viruses 2021; 13:v13081648. [PMID: 34452512 PMCID: PMC8402751 DOI: 10.3390/v13081648] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 08/11/2021] [Accepted: 08/11/2021] [Indexed: 12/18/2022] Open
Abstract
The SARS-CoV-2 pandemic, which came to Russia in March 2020, is accompanied by morbidity level changes and can be tracked using serological monitoring of a representative population sample from Federal Districts (FDs) and individual regions. In a longitudinal cohort study conducted in 26 model regions of Russia, distributed across all FDs, we investigated the distribution and cumulative proportions of individuals with antibodies (Abs) to the SARS-CoV-2 nucleocapsid antigen (Ag), in the period from June to December 2020, using a three-phase monitoring process. In addition, during the formation of the cohort of volunteers, the number of seropositive convalescents, persons who had contact with patients or COVID-19 convalescents, and the prevalence of asymptomatic forms of infection among seropositive volunteers were determined. According to a uniform methodology, 3 mL of blood was taken from the examined individuals, and plasma was separated, from which the presence of Abs to nucleocapsid Ag was determined on a Thermo Scientific Multiascan FC device using the “ELISA anti-SARS-CoV-2 IgG” reagent set (prod. Scientific Center for Applied Microbiology and Biotechnology), in accordance with the developer’s instructions. Volunteers (74,158) were surveyed and divided into seven age groups (1–17, 18–29, 30–39, 40–49, 59–59, 60–69, and 70+ years old), among whom 14,275 were identified as having antibodies to SARS-CoV-2. The average percent seropositive in Russia was 17.8% (IQR: 8.8–23.2). The largest proportion was found among children under 17 years old (21.6% (IQR: 13.1–31.7). In the remaining groups, seroprevalence ranged from 15.6% (IQR: 8–21.1) to 18.0% (IQR: 13.4–22.6). During monitoring, three (immune) response groups were found: (A) groups with a continuous increase in the proportion of seropositive; (B) those with a slow rate of increase in seroprevalence; and (C) those with a two-phase curve, wherein the initial increase was replaced by a decrease in the percentage of seropositive individuals. A significant correlation was revealed between the number of COVID-19 convalescents and contact persons, and between the number of contacts and healthy seropositive volunteers. Among the seropositive volunteers, more than 93.6% (IQR: 87.1–94.9) were asymptomatic. The results show that the COVID-19 pandemic is accompanied by an increase in seroprevalence, which may be important for the formation of herd immunity.
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Retrospective of International Serological Studies on the Formation and Dynamics of the Humoral Immune Response to SARS-CoV-2: from 2020 to 2021. ACTA BIOMEDICA SCIENTIFICA 2021. [DOI: 10.29413/abs.2021-6.2.5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Last year the COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has started. The new coronavirus is highly contagious and causes severe complications. The mechanisms of humoral immunity and kinetics of SARS-CoV-2 specific antibodies in a population are not well understood. Therefore, we aimed to summarize and analyze numerous global and Russian serological studies for understanding dynamics of the SARSCoV-2 humoral immune response and getting an accurate picture of the seroprevalence to SARS-CoV-2 in the world population. The PubMed and e-library databases were searched from February 2020 to March 2021 using terms “SARSCoV-2”, “antibodies”, “humoral immunity”. At the beginning of the pandemic first studies were cross-sectional by design and were responsible for determination of the seropositivity and for understanding the fundamental humoral immunity parameters of SARS-CoV-2. Since then, longitudinal seroepidemiological studies have been studying antibody kinetics. Seroconversion time for IgM, IgG antibodies varies, but most researchers report the seroconversion of IgM from the 1st to 14th days after the onset of clinical manifestations, and the seroconversion for IgG is around the 14th day with a concentration peak by the 21st day. Regarding seroprevalence we may say about low herd immunity at the COVID-19 pandemic. Thus, global seroprevalence is about 10 %, and more than 20 % for regions with high incidence and among healthcare workers. Seroprevalence studies have to be continued for more accurate monitoring of long-term humoral immunity to SARS-CoV-2, because the majority of the world’s population is still susceptible to SARS-CoV-2 infection.
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Zurochka A, Dobrinina M, Zurochka V, Hu D, Solovyev A, Ryabova L, Kritsky I, Ibragimov R, Sarapultsev A. Seroprevalence of SARS-CoV-2 Antibodies in Symptomatic Individuals Is Higher than in Persons Who Are at Increased Risk Exposure: The Results of the Single-Center, Prospective, Cross-Sectional Study. Vaccines (Basel) 2021; 9:627. [PMID: 34207919 PMCID: PMC8229032 DOI: 10.3390/vaccines9060627] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Revised: 06/03/2021] [Accepted: 06/08/2021] [Indexed: 01/08/2023] Open
Abstract
The present study aimed to assess antibody seropositivity prevalence among symptomatic individuals and individuals with a high risk of occupational exposure to SARS-CoV-2. Participants from Chelyabinsk (Russian Federation) who were at an increased risk of exposure to SARS-CoV-2 (high-risk group, n = 1091) and participants who either had symptoms consistent with COVID-19 or were suspected to have experienced COVID-19 in the past (symptomatic group, n = 692) were enrolled between 28 September and 30 December 2020. Blood samples were tested by enzyme-linked immunosorbent assay D-5501 SARS-Cov-2-IgG-EIA-BEST and D-5502 SARS-Cov-2-IgM-EIA-BEST (AO Vector-Best, Novosibirsk, Russia). The overall seropositivity rate was 28.33-28.53%. SARS-CoV-2 antibodies were detected in 17.23% (adjusted prevalence of 17.17-17.29%) of participants in the high-risk and 45.95% (adjusted prevalence of 45.91-46.24%) in the symptomatic group. Higher IgG and IgM titers were observed in women compared to men, as well as in participants in the symptomatic group compared to those in the high-risk group. The results indicate that the seroprevalence among residents in several Russian regions is low (28.38%) and inadequate to provide herd immunity. The lower seroprevalence among participants in the high-risk group may be attributed to the enforcement of healthcare protocols and the use of adequate personal protective equipment.
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Affiliation(s)
- Alexandr Zurochka
- School of Medical Biology, South Ural State University, 454080 Chelyabinsk, Russia; (A.Z.); (V.Z.)
- Institute of Immunology and Physiology, Ural Branch of the Russian Academy of Science, 620049 Ekaterinburg, Russia; (M.D.); (I.K.); (R.I.)
| | - Maria Dobrinina
- Institute of Immunology and Physiology, Ural Branch of the Russian Academy of Science, 620049 Ekaterinburg, Russia; (M.D.); (I.K.); (R.I.)
| | - Vladimir Zurochka
- School of Medical Biology, South Ural State University, 454080 Chelyabinsk, Russia; (A.Z.); (V.Z.)
- Institute of Immunology and Physiology, Ural Branch of the Russian Academy of Science, 620049 Ekaterinburg, Russia; (M.D.); (I.K.); (R.I.)
| | - Desheng Hu
- Department of Integrated Traditional Chinese and Western Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 200092, China;
| | - Alexandr Solovyev
- NPO National Medical Association for the Development of the Expert Activities in the Field of Laboratory Diagnostics “MedLabExpert”, 117042 Moscow, Russia;
- LCC GMK MEDMA, 620102 Ekaterinburg, Russia
| | - Liana Ryabova
- Department of Propedeutics of Internal Diseases, South Ural State Medical University, 454092 Chelyabinsk, Russia;
| | - Igor Kritsky
- Institute of Immunology and Physiology, Ural Branch of the Russian Academy of Science, 620049 Ekaterinburg, Russia; (M.D.); (I.K.); (R.I.)
- Institute of Natural Sciences and Mathematics, Ural Federal University Named after the First President of Russia, 620026 Ekaterinburg, Russia
| | - Roman Ibragimov
- Institute of Immunology and Physiology, Ural Branch of the Russian Academy of Science, 620049 Ekaterinburg, Russia; (M.D.); (I.K.); (R.I.)
- Institute of Natural Sciences and Mathematics, Ural Federal University Named after the First President of Russia, 620026 Ekaterinburg, Russia
| | - Alexey Sarapultsev
- School of Medical Biology, South Ural State University, 454080 Chelyabinsk, Russia; (A.Z.); (V.Z.)
- Institute of Immunology and Physiology, Ural Branch of the Russian Academy of Science, 620049 Ekaterinburg, Russia; (M.D.); (I.K.); (R.I.)
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Popova AY, Andreeva EE, Babura EA, Balakhonov SV, Bashketova NS, Bulanov MV, Valeullina NN, Goryaev DV, Detkovskaya NN, Ezhlova EB, Zaitseva NN, Istorik OA, Kovalchuk IV, Kozlovskikh DN, Kombarova SV, Kurganova OP, Kutyrev VV, Lomovtsev AE, Lukicheva LA, Lyalina LV, Melnikova AA, Mikailova OM, Noskov AK, Noskova LN, Oglezneva EE, Osmolovskay TP, Patyashina MA, Penkovskaya NA, Samoilova LV, Smirnov VS, Stepanova TF, Trotsenko OE, Totolyan AA. Features of developing SARS-CoV-2 nucleocapsid protein population-based seroprevalence during the first wave of the COVID-19 epidemic in the Russian Federation. RUSSIAN JOURNAL OF INFECTION AND IMMUNITY 2021. [DOI: 10.15789/2220-7619-fod-1684] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The novel coronavirus (SARS-CoV-2) pandemic, dubbed COVID-19, has become one of the most serious challenges for human populations in the vast majority of countries worldwide. Rapid spreading and increased mortality related to it required new approaches to manage epidemic processes on a global scale. One of such approaches was based on analyzing SARS-CoV-2 seroprevalence associated with COVID-19. Our aim was to summarize the results on assessing seroprevalence to the SARS-CoV-2 nucleocapsid antigen (Nc) in residents from 26 regions of the Russian Federation, carried out during the first wave of the COVID-19 epidemic.Materials and methods. Seroprevalence distribution was examined in 26 model regions of the Russian Federation according to the unified method developed by the Rospotrebnadzor with the participation of the Federal State Institution Saint Petersburg Pasteur Research Institute of Epidemiology and Microbiology. Such approach implied formation of a group of volunteer subjects in model geographic region who were tested by ELISA for anti-Nc serum antibody level in peripheral blood. Analyzed primary data obtained in separate regions were either accepted for publication or released.Results. The current paper finalizes the data obtained in all 26 regions of the Russian Federation. The total SARS-CoV-2 seroprevalence was 19.5 (10.0–25.6)% with the maximum and minimum value found in the Kaliningrad Region and the Republic of Crimea, respectively (50.2% vs. 4.3%). A pattern of age-related seroprevalence distribution indicates insignificant predominance of seroprevalence among subjects of 1–17 years old: 22.1 (13.1–31.8)%. Among COVID-19 convalescents positive for SARS-CoV Nc antibodies it reached 60.0 (40.0–73.3)%. The number of contact persons comprised 6285 subjects or 8.5% of total volunteer cohort, with the level of seroprevalence reaching up to 25.3 (17.95–35.8)%. A direct correlation was revealed between levels of seroprevalence in convalescent and contact volunteers. In addition, the reproductive number for SARS-CoV was calculated comprising 5.8 (4.3–8.5) suggesting that one convalescent subject can infect at least 4 healthy individuals. A high level of asymptomatic forms of COVID-19 among seropositive subjects was confirmed empirically comprising up to 93.6 (87.1–94.9)%.Conclusion. A single cross-sectional study performed during 2020 June–August timeframe allowed to assess pattern of sex- and agerelated COVID-19 seroprevalence for general population in 26 Russian Federation regions. The data obtained may serve as a basis for the longitudinal cohort investigation with serial subject sampling. The timing and duration of study will be determined by dynamics of ongoing COVID-19 epidemic.
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