Whither repeat players? Litigation experience and success in court: Evidence from Russian commercial courts.

This paper tests the party capability theory of Galanter (1974) using the universe of legal entities and their 9.8 million commercial disputes in Russia in 2012-2019. We find that repetitiveness is negatively associated with litigation success in general. We explain this by selection into litigation. Entities engaged in unfair business practices are repeatedly selected into disputes as respondents becoming repeat players in spite of themselves. We argue that repetitiveness should be decoupled from party capability and urge for conceptual revision of the notion of a repeat player in court.

Vaccine effectiveness against referral to hospital after SARS-CoV-2 infection in St. Petersburg, Russia, during the Delta variant surge: a test-negative case-control study.

BACKGROUND: The results of a randomised trial showed the safety and efficacy of Gam-COVID-Vac against COVID-19. However, compared to other vaccines used across the globe, the real-world data on the effectiveness of Gam-COVID-Vac, especially against the disease caused by the Delta variant of concern, was limited. We aimed to assess the effectiveness of vaccination mainly conducted with Gam-COVID-Vac in St. Petersburg, Russia. METHODS: We designed a case-control study to assess the vaccine effectiveness (VE) against referral to hospital. Self-reported vaccination status was collected for individuals with confirmed SARS-CoV-2 infection who were referred for initial low-dose computed tomography (LDCT) triage in two outpatient centres in July 3-August 9, 2021, in St. Petersburg, Russia. We used logistic regression models to estimate the adjusted (for age, sex, and triage centre) VE for complete (14 days or more after the second dose) vaccination. We estimated the VE against referral for hospital admission, COVID-19-related lung injury assessed with LDCT, and decline in oxygen saturation. RESULTS: In the final analysis, 13,893 patients were included, 1291 (9.3%) patients met our criteria for complete vaccination status, and 495 (3.6%) were referred to hospital. In the primary analysis, the adjusted VE against referral to hospital was 81% (95% confidence interval: 68-88) for complete vaccination. The VE against referral to hospital was more pronounced in women (84%, 95% CI: 66-92) compared to men (76%, 95% CI: 51-88). Vaccine protective effect increased with increasing lung injury categories, from 54% (95% CI: 48-60) against any sign of lung injury to 76% (95% CI: 59-86) against more than 50% lung involvement. A sharp increase was observed in the probability of hospital admission with age for non-vaccinated patients in relation to an almost flat relationship for the completely vaccinated group. CONCLUSIONS: COVID-19 vaccination was effective against referral to hospital in patients with symptomatic SARS-CoV-2 infection in St. Petersburg, Russia. This protection is probably mediated through VE against lung injury associated with COVID-19.

Gam-COVID-Vac, EpiVacCorona, and CoviVac effectiveness against lung injury during Delta and Omicron variant surges in St. Petersburg, Russia: a test-negative case-control study.

BACKGROUND: Monitoring vaccine effectiveness (VE) remains a priority for epidemiological research throughout the COVID-19 pandemic. VE against infection declines with the emergence of new SARS-CoV-2 variants of concern (VOC), but VE against the severe disease remains high. Therefore, we aimed to estimate the effectiveness of COVID-19 vaccines used in Russia against lung injury during Delta and Omicron VOC surges. METHODS: We designed a case-control study (test-negative design) to estimate VE against any (any volume of involved lung parenchyma) and severe (>50% of involved parenchyma) lung injury detected on computer tomography and associated with COVID-19 between October 1, 2021-April 28, 2022 (Delta VOC dominance period followed by Omicron dominance period). We included the data of patients with symptomatic confirmed SARS-CoV-2 infection referred to the low-dose computer tomography triage centres. RESULTS: Among 23996 patients in the primary analysis, 13372 (55.7%) had any lung injury, and 338 (1.4%) had severe lung injury. The adjusted for age, sex and triage centre VE estimates against any lung injury were 56% (95% confidence interval 54-59) for two-dose Gam-COVID-Vac (Sputnik V), 71% (68-74) for three-dose Gam-COVID-Vac (booster), 2% (-27 to 24) for EpiVacCorona, and 46% (37-53) for CoviVac. VE estimates against severe lung injury were 76% (67-82) for two-dose Gam-COVID-Vac (Sputnik V), 87% (76-93) for three-dose Gam-COVID-Vac, 36% (-63 to 75) for EpiVacCorona, and 80% (45-92) for CoviVac. CONCLUSIONS: Gam-COVID-Vac remained effective against lung injury associated with COVID-19 during Delta and Omicron VOC surges, and one Gam-COVID-Vac booster could be seen as an appropriate option after a two-dose regimen. CoviVac was also effective against lung injury. EpiVacCorona use in population-based vaccination should be halted until effectiveness and efficacy evidence is provided. Trial registration The joint study of COVID-19 vaccine effectiveness in St. Petersburg was registered at ClinicalTrials.gov (NCT04981405, date of registration-August 4, 2021).

COVID-19 vaccines effectiveness against symptomatic SARS-CoV-2 during Delta variant surge: a preliminary assessment from a case-control study in St. Petersburg, Russia.

BACKGROUND: Studies of mRNA and vector-based vaccines used in different countries report acceptable levels of effectiveness against SARS-CoV-2 infection caused by the Delta variants of SARS-CoV-2. No studies estimated vaccine effectiveness (VE) of Gam-COVID-Vac and other vaccines used in Russia against symptomatic infection with Delta variant. In this population-based case-control study, we aimed to estimate the effectiveness of the Russian COVID-19 vaccines against symptomatic SARS-CoV-2 during the recent outbreak caused by the Delta VOC in October 2021 in St. Petersburg, Russia. METHODS: Cases were symptomatic patients with confirmed SARS-CoV-2 (using polymerase chain reaction (PCR) test) referred to low-dose computed tomography (LDCT) triage in two outpatient centres between October 6 and 14, 2021 during the Delta variant outbreak. We recruited the controls during the representative survey of the seroprevalence study conducted during the same period in St. Petersburg using random digit dialling. In the primary analysis, we used logistic regression models to estimate the adjusted (age, sex, and history of confirmed COVID-19) VE against symptomatic SARS-CoV-2 resulted in a referral to triage centre for three vaccines used in Russia: Gam-COVID-Vac, EpiVacCorona, and CoviVac. RESULTS: We included 1,254 cases and 2,747 controls recruited between the 6th and 14th of October in the final analysis. VE was 56% (95% CI: 48 to 63) for Gam-COVID-Vac (Sputnik V), 49% (95% CI: 29 to 63) for 1-dose Gam-COVID-Vac (Sputnik V) or Sputnik Light, -58% (95% CI: -225 to 23) for EpiVacCorona and 40% (95% CI: 3 to 63) for CoviVac. Without adjustment for the history of confirmed COVID-19 VE for all vaccines was lower, except for one-dose Gam-COVID-Vac (Sputnik Light). The adjusted VE was slightly lower in women - 51% (95% CI: 39 to 60) than men - 65% (95% CI: 5 to 73). CONCLUSIONS: Our preliminary results show that in contrast to other Russian vaccines, Gam-COVID-Vac is effective against symptomatic SARS-CoV-2 infection caused by Delta VOC. Effectiveness is likely higher than the estimated 56% due to bias arising from high prevalence of the past COVID-19 in St. Petersburg.

Evaluation of the performance of SARS--CoV--2 antibody assays for a longitudinal population-based study of COVID--19 spread in St. Petersburg, Russia.

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 pre-pandemic 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 Vector-Best, 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 cut-off 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 cut-off. Manufacturers' test characteristics may introduce bias into the study results.

COVID-19 pandemic in Saint Petersburg, Russia: Combining population-based serological study and surveillance data.

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.

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

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.