Background Since 2005, Russia has made substantial progress, experiencing an almost doubling of per-capita gross domestic product by purchasing power parity (GDP [PPP]) to US$24 800 and witnessing a 6-year increase in life expectancy, reaching 71•4 years by 2015. Even greater gains in GDP (PPP) were seen for Moscow, the Russian capital, reaching $43 000 in 2015 and with a life expectancy of 75•5 years. We aimed to investigate whether mortality levels now seen in Russia are consistent with what would be expected given this new level of per-capita wealth. Methods We used per-capita GDP (PPP) and life expectancy from 61 countries in 2014-15, plus those of Russia as a whole and its capital Moscow, to construct a Preston curve expressing the relationship between mortality and national wealth and to examine the positions of Russia and other populations relative to this curve. We adjusted life expectancy values for Moscow for underestimation of mortality at older ages. For comparison, we constructed another Preston curve based on the same set of countries for the year 2005. We used the stepwise replacement algorithm to decompose mortality differences between Russia or Moscow and comparator countries with similar incomes into age and causeof-death components. Findings Life expectancy in 2015 for both Russia and Moscow lay below the Preston-curve-based expectations by 6•5 years and 4•9 years, respectively. In 2015, Russia had a lower per-capita income than 36 of the comparator countries but lower life expectancy than 60 comparator countries. However, the gaps between the observed and the Preston-expected life expectancy values for Russia have diminished by about 25% since 2005, when the life expectancy gap was 8•9 years for Russia and 6•6 years for Moscow. When compared with countries with similar level of income, the largest part of the life expectancy deficit was produced by working-age mortality from external causes for Russia and cardiovascular disease at older ages for Moscow. Interpretation Given the economic wealth of Russia, its life expectancy could be substantially higher. Sustaining the progress seen over the past decade depends on the ability of the Russian Government and society to devote adequate resources to people's health.

Geographical variation in severe acute respiratory syndrome coronavirus 2 (SARS­‐CoV­‐2) spread requires seroprevalence studies based on local tests, but robust validation is needed. We summarize an evaluation of antibody tests used in a serological study of SARS‐­CoV­‐2 in Saint Petersburg, Russia. We validated three different antibody assays: chemiluminescent microparticle immunoassay (CMIA) Abbott Architect SARS‐­CoV­‐2 immunoglobulin G (IgG), enzyme­ linked immunosorbent assay (ELISA) CoronaPass total antibodies test, and ELISA SARS­‐CoV‐­2‐­IgG‐­EIA‐­BEST. Clinical sensitivity was estimated with the SARS­‐CoV­‐2 polymerase chain reaction (PCR) test as the gold standard using manufacturer recommended cutoff. Specificity was estimated using pre­pandemic sera samples. The median time between positive PCR test results and antibody tests was 21 weeks. Measures of concordance were calculated against the microneutralization test (MNA).Sensitivity was equal to 91.1% (95% confidence intervbal [CI]: 78.8–97.5), 90% (95% CI: 76.4–96.4), and 63.1% (95% CI [50.2–74.7]) for ELISA Coronapass, ELISA Vector­Best, and CMIA Abbott, respectively. Specificity was equal to 100% for all the tests. Comparison of receiver operating characteristics has shown lower AUC for CMIA Abbott. The cut­off SC/O ratio of 0.28 for CMIA Abbott resulted in a sensitivity of 80% at the same level of specificity. Less than 33% of the participants with positive antibody test results had neutralizing antibodies in titers 1:80 and above. Antibody assays results and MNA correlated moderately. This study encourages the use of local antibody tests and sets the reference for seroprevalence correction. Available tests' sensitivity allows detecting antibodies within the majority of PCR­ positive individuals. The Abbott assay sensitivity can be improved by incorporating a new cut­off. Manufacturers' test characteristics may introduce bias into the study results.

Background The COVID-19 pandemic in Russia has already resulted in 500,000 excess deaths, with more than 5.6 million cases registered officially by July 2021. Surveillance based on case reporting has become the core pandemic monitoring method in the country and globally. However, population-based seroprevalence studies may provide an unbiased estimate of the actual disease spread and, in combination with multiple surveillance tools, help to define the pandemic course. This study summarises results from four consecutive serological surveys conducted between May 2020 and April 2021 at St. Petersburg, Russia and combines them with other SARS-CoV-2 surveillance data. Methods We conducted four serological surveys of two random samples (May–June, July–August, October–December 2020, and February–April 2021) from adults residing in St. Petersburg recruited with the random digit dialing (RDD), accompanied by a telephone interview to collect information on both individuals who accepted and declined the invitation for testing and account for non-response. We have used enzyme-linked immunosorbent assay CoronaPass total antibodies test (Genetico, Moscow, Russia) to report seroprevalence. We corrected the estimates for non-response using the bivariate probit model and also accounted the test performance characteristics, obtained from independent assay evaluation. In addition, we have summarised the official registered cases statistics, the number of hospitalised patients, the number of COVID-19 deaths, excess deaths, tests performed, data from the ongoing SARS-CoV-2 variants of concern (VOC) surveillance, the vaccination uptake, and St. Petersburg search and mobility trends. The infection fatality ratios (IFR) have been calculated using the Bayesian evidence synthesis model. Findings After calling 113,017 random mobile phones we have reached 14,118 individuals who responded to computer-assisted telephone interviewing (CATI) and 2,413 provided blood samples at least once through the seroprevalence study. The adjusted seroprevalence in May–June, 2020 was 9.7% (95%: 7.7–11.7), 13.3% (95% 9.9–16.6) in July–August, 2020, 22.9% (95%: 20.3–25.5) in October–December, 2021 and 43.9% (95%: 39.7–48.0) in February–April, 2021. History of any symptoms, history of COVID-19 tests, and non-smoking status were significant predictors for higher seroprevalence. Most individuals remained seropositive with a maximum 10 months follow-up. 92.7% (95% CI 87.9–95.7) of participants who have reported at least one vaccine dose were seropositive. Hospitalisation and COVID-19 death statistics and search terms trends reflected the pandemic course better than the official case count, especially during the spring 2020. SARS-CoV-2 circulation showed rather low genetic SARS-CoV-2 lineages diversity that increased in the spring 2021. Local VOC (AT.1) was spreading till April 2021, but B.1.617.2 substituted all other lineages by June 2021. The IFR based on the excess deaths was equal to 1.04 (95% CI 0.80–1.31) for the adult population and 0.86% (95% CI 0.66–1.08) for the entire population. Conclusion Approximately one year after the COVID-19 pandemic about 45% of St. Petersburg, Russia residents contracted the SARS-CoV-2 infection. Combined with vaccination uptake of about 10% it was enough to slow the pandemic at the present level of all mitigation measures until the Delta VOC started to spread. Combination of several surveillance tools provides a comprehensive pandemic picture.

No abstract

Background: The COVID-19 pandemic in Russia has already resulted in 500,000 excess deaths, with more than 5.6 million cases registered officially by July 2021. Surveillance based on case reporting has become the core pandemic monitoring method in the country and globally. However, population-based seroprevalence studies may provide an unbiased estimate of the actual disease spread and, in combination with multiple surveillance tools, help to define the pandemic course. This study summarises results from four consecutive serological surveys conducted between May 2020 and April 2021 at St.Petersburg, Russia and combines them with other SARS-CoV-2 surveillance data. Methods: We conducted four serological surveys of two random samples (May-June, July-August, October--December 2020, and February-April 2021) from adults residing in St.Petersburg recruited with the random digit dialing (RDD), accompanied by a telephone interview to collect information on both individuals who accepted and declined the invitation for testing and account for non-response. We have used enzyme-linked immunosorbent assay CoronaPass total antibodies test (Genetico, Moscow, Russia) to report seroprevalence. We corrected the estimates for non-response using the bivariate probit model and also accounted the test performance characteristics, obtained from independent assay evaluation. In addition, we have summarised the official registered cases statistics, the number of hospitalised patients, the number of COVID-19 deaths, excess deaths, tests performed, data from the ongoing SARS-CoV-2 variants of concern (VOC) surveillance, the vaccination uptake, and St. Petersburg search and mobility trends. The infection fatality ratios (IFR) have been calculated using the Bayesian evidence synthesis model. Findings: After calling 113,017 random mobile phones we have reached 14,118 individuals who responded to computer-assisted telephone interviewing (CATI) and 2,413 provided blood samples at least once through the seroprevalence study. The adjusted seroprevalence in May-June, 2020 was 9.7% (95%: 7.7-11.7), 13.3% (95% 9.9-16.6) in July-August, 2020, 22.9% (95%: 20.3-25.5) in October-December, 2021 and 43.9% (95%: 39.7-48.0) in February-April, 2021. History of any symptoms, history of COVID-19 tests, and non-smoking status were significant predictors for higher seroprevalence. Most individuals remained seropositive with a maximum 10 months follow-up. 92.7% (95% CI 87.9-95.7) of participants who have reported at least one vaccine dose were seropositive. Hospitalisation and COVID-19 death statistics and search terms trends reflected the pandemic course better than the official case count, especially during the spring 2020. SARS-CoV-2 circulation showed rather low genetic SARS-CoV-2 lineages diversity that increased in the spring 2021. Local VOC (AT.1) was spreading till April 2021, but B.1.617.2 substituted all other lineages by June 2021. The IFR based on the excess deaths was equal to 1.04 (95% CI 0.80-1.31) for the adult population and 0.86% (95% CI 0.66-1.08) for the entire population. Conclusion: Approximately one year after the COVID-19 pandemic about 45% of St. Petersburg, Russia residents contracted the SARS-CoV-2 infection in, or 2.2 mln people. Combined with vaccination uptake of about 10% it was enough to slow the pandemic until the Delta VOC started to spread. Combination of several surveillance tools provides a comprehensive pandemic picture. Funding: Polymetal International plc.