The main strategy for combatting SARS-CoV-2 infections in 2020 consisted of behavioural regulations including contact reduction, maintaining distance, hand hygiene, and mask wearing. COVID-19-related risk perception and knowledge may influence protective behaviour, and education could be an important determinant. The current study investigated differences by education level in risk perception, knowledge and protective behaviour regarding COVID-19 in Germany, exploring the development of the pandemic over time. The COVID-19 Snapshot Monitoring study is a repeated cross-sectional online survey conducted during the pandemic in Germany from 3 March 2020 (waves 1–28: 27,957 participants aged 18–74). Differences in risk perception, knowledge and protective behaviour according to education level (high versus low) were analysed using linear and logistic regression. Time trends were accounted for by interaction terms for education level and calendar week. Regarding protective behaviour, interaction terms were tested for all risk perception and knowledge variables with education level. The strongest associations with education level were evident for perceived and factual knowledge regarding COVID-19. Moreover, associations were found between low education level and higher perceived severity, and between low education level and lower perceived probability. Highly educated men were more worried about COVID-19 than those with low levels of education. No educational differences were observed for perceived susceptibility or fear. Higher compliance with hand washing was found in highly educated women, and higher compliance with maintaining distance was found in highly educated men. Regarding maintaining distance, the impact of perceived severity differed between education groups. In men, significant moderation effects of education level on the association between factual knowledge and all three protective behaviours were found. During the pandemic, risk perception and protective behaviour varied greatly over time. Overall, differences by education level were relatively small. For risk communication, reaching all population groups irrespective of education level is critical.

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Social epidemiological research describes correlations between socioeconomic status and the population’s risk to become diseased or die. Little research of such correlations for SARS-CoV-2 and COVID-19 has so far been conducted. This scoping review provides an overview of the international research literature. Out of the 138 publications found, 46 were later included in the analysis. For the US and the UK, the reported findings indicate the presence of socioeconomic inequalities in infection risks as well as the severity of the course of the disease, with socioeconomically less privileged populations being hit harder. There are far fewer findings for Germany to date, as is the case for most other European countries. However, the scant evidence available so far already indicates that social inequalities are a factor in COVID-19. Most of these analyses have been ecological studies with only few studies considering socioeconomic inequalities at the individual level. Such studies at the individual level are particularly desirable as they could help to increase our understanding of the underlying pathways that lead to the development of inequalities in infection risks and the severity of disease and thereby could provide a basis to counteract the further exacerbation of health inequalities.

Experiences with acute respiratory diseases which caused virus epidemics in the past and initial findings in the research literature on the current COVID-19 pandemic suggest a higher SARS-CoV-2 infection risk for socioeconomically disadvantaged populations. Nevertheless, further research on such a potential association between socioeconomic status and SARS-CoV-2 incidence in Germany is required. This article reports on the results of a first Germany-wide analysis of COVID-19 surveillance data to which an area-level index of socioeconomic deprivation was linked. The analysis included 186,839 laboratory-confirmed COVID-19 cases, the data of which was transferred to the Robert Koch Institute by 16 June 2020, 00:00. During the early stage of the epidemic up to mid-April, the data show a socioeconomic gradient with higher incidence in less deprived regions of Germany. Over the course of the epidemic, however, this gradient becomes less measurable and finally reverses in south Germany, the region hardest hit by the epidemic, to the greater detriment of the more deprived regions. These results highlight the need to continue monitoring social epidemiological patterns in COVID-19 and analysing the underlying causes to detect dynamics and trends early on and countering a potential exacerbation of health inequalities.

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Objective Evidence on socioeconomic inequalities in infections with the novel coronavirus (SARS-CoV-2) is still limited as most of the available studies are ecological in nature and individual-level data is sparse. We therefore analysed individual-level data on socioeconomic differences in the prevalence and perceived dangerousness of SARS-CoV-2 infections in local populations. Data were obtained from a population-based seroepidemiological study of adult individuals in two early German SARS-CoV-2 hotspots (n = 3903). Infection was determined by IgG antibody ELISA, RT-PCR testing and self-reports on prior positive PCR tests. The perceived dangerousness of an infection and socioeconomic position (SEP) were assessed by self-reports. Logistic and linear regression were applied to examine associations of multiple SEP measures with infection status and perceptions of dangerousness. Results We found no evidence of socioeconomic inequalities in SARS-CoV-2 infections by education, occupation, income and subjective social status. Participants with lower education and lower subjective social status perceived an infection as more dangerous than their better-off counterparts. In successfully contained local outbreaks of SARS-CoV-2 in Germany, infections may have been equally distributed across the socioeconomic spectrum. But residents in disadvantaged socioeconomic groups might have experienced a higher level of mental distress due to the higher perceived dangerousness of an infection.

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Background International research shows increased risks for SARS-CoV-2 infection and severe disease progression in people with migration history. In Germany, data on this topic is scarce. Aim of this contribution is to examine the association between migrant status and risk of SARS-CoV-2 infection and discuss potential explanatory mechanisms. Methods We analysed data from the German COVID-19 Snapshot Monitoring online-survey and performed hierarchical multiple regression models to calculate probabilities for a self-reported SARS-CoV-2 infection. Main predictor variable was the migrant status; besides, the association with gender, age, education, household size, household language (German vs. other), and occupation in the health sector was analysed. Results Of 45,858 participants, 3.5% reported a current or previous infection with SARS-CoV-2, 16% reported own or parental history of migration. The probability of reporting an infection was 3.95 percentage points higher among migrants. The effect of different characteristics on self-reported SARS-CoV-2 infection varied. Higher probabilities were shown for individuals living in bigger households and those not speaking German at home. Stepwise integration decreased the observed association with migrant status. When adding an interaction term of migrant status and occupation in the health sector, the probability to report an infection was 11.5 percentage points higher for migrants working in the health sector. Conclusions People with migration history, health sector employees and particular migrant health workers are at a higher risk of SARS-CoV-2 infection. However, the migrant status itself does not determine the risk of infection, but the living and working conditions. Therefore, targeted and multilingual prevention measures are needed that consider living and working conditions. Key messages • Higher SARS-CoV-2 infection risks are not solely determined by migrant status, but were shown for health care workers, people living in bigger households and those not speaking German at home. • As not the migrant status determines infection risks, multilingual and targeted prevention measures considering the living and working conditions of people are necessary.