Seroprevalence trends of anti-SARS-CoV-2 antibodies and associated risk factors: a population-based study

Abstract

Purpose We aimed to assess the seroprevalence trends of SARS-CoV-2 antibodies in several Swiss cantons between May 2020 and September 2021 and investigate risk factors for seropositivity and their changes over time. Methods We conducted repeated population-based serological studies in different Swiss regions using a common methodology. We defined three study periods: May–October 2020 (period 1, prior to vaccination), November 2020–mid-May 2021 (period 2, first months of the vaccination campaign), and mid-May–September 2021 (period 3, a large share of the population vaccinated). We measured anti-spike IgG. Participants provided information on sociodemographic and socioeconomic characteristics, health status, and adherence to preventive measures. We estimated seroprevalence with a Bayesian logistic regression model and the association between risk factors and seropositivity with Poisson models. Results We included 13,291 participants aged 20 and older from 11 Swiss cantons. Seroprevalence was 3.7% (95% CI 2.1–4.9) in period 1, 16.2% (95% CI 14.4–17.5) in period 2, and 72.0% (95% CI 70.3–73.8) in period 3, with regional variations. In period 1, younger age (20–64) was the only factor associated with higher seropositivity. In period 3, being aged ≥ 65 years, with a high income, retired, overweight or obese or with other comorbidities, was associated with higher seropositivity. These associations disappeared after adjusting for vaccination status. Seropositivity was lower in participants with lower adherence to preventive measures, due to a lower vaccination uptake. Conclusions Seroprevalence sharply increased over time, also thanks to vaccination, with some regional variations. After the vaccination campaign, no differences between subgroups were observed.

Socioeconomic Status and Adherence to Preventive Measures During the COVID-19 Pandemic in Switzerland: A Population Based Digital Cohort Analysis

“…This study has some limitations. Firstly, despite a random representative sample of the population being invited, selection bias is probable (e.g., a lower participation of low SES individuals or over-representation of individuals with a low SES and a high health literacy), also due to moderate participation rate (21%) of the Corona Immunitas study [ 41 ]. Additionally, our study relied on a baseline assessment of predictors, and we lacked information about potential changes in equivalized disposable income over time.…”

Bayesian workflow for time-varying transmission in stratified compartmental infectious disease transmission models

“…The laboratory-confirmed SARS-CoV-2 cases are obtained from the Federal Office of Public Health. The serosurvey was performed by the Corona Immunitas Research Group in Switzerland [ 52 ]. As the seroprevalence data were collected over a prolonged period, we decided to use monthly seroprevalence estimates for fitting the model.…”