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.

Over the course of the second pandemic wave in late 2020, new infections with severe acute respiratory syndrome coronavirus-2 shifted from the most affluent to the most deprived regions of Germany. This study investigated how this trend in infections played out for deaths due to coronavirus disease 2019 (COVID-19) by examining area-level socio-economic disparities in COVID-19-related mortality during the second pandemic wave in Germany. The analysis was based on nationwide data on notified deaths, which were linked to an area-based index of socio-economic deprivation. In the autumn and winter of 2020/2021, COVID-19-related deaths increased faster among residents in Germany's more deprived districts. From late 2020 onwards, the mortality risks of men and women in the most deprived districts were 1.52 (95% confidence interval [CI] 1.27−1.82] and 1.44 (95% CI 1.19−1.73) times higher than among those in the most affluent districts, respectively, after adjustment for age, urbanization and population density. To promote health equity in the pandemic and beyond, deprived populations should receive increased attention in pandemic planning, infection control and disease prevention.

Zusammenfassung: Hintergrund: Das frühere Versterben in sozioökonomisch benachteiligten Bevölkerungsgruppen stellt eine extreme Ausprägungsform gesundheitlicher Ungleichheit dar. Diese Studie untersucht das Ausmaß, die zeitliche Entwicklung und Reduktionspotenziale regionaler sozioökonomischer Ungleichheiten in der vorzeitigen Sterblichkeit in Deutschland. Methoden: Bundesweite Daten der amtlichen Todesursachenstatistik wurden auf Stadt- und Landkreisebene mit amtlichen Bevölkerungsdaten und dem „German Index of Socioeconomic Deprivation“ (GISD) verknüpft. Altersstandardisierte Mortalitätsraten für unter 75-Jährige wurden stratifiziert nach Geschlecht und Deprivationsquintil berechnet. In einer What-if-Analyse wurde anhand kontrafaktischer Szenarien berechnet, wie viel niedriger die vorzeitige Sterblichkeit insgesamt läge, wenn sozioökonomische Mortalitätsungleichheiten verringert würden. Ergebnisse: Männer und Frauen im höchsten Deprivationsquintil hatten ein 43 % bzw. 33 % höheres Risiko, vorzeitig zu versterben, als Gleichaltrige im niedrigsten Deprivationsquintil. Höhere Mortalitätsraten mit steigender Deprivation zeigten sich für die Herz-Kreislauf- und Krebsmortalität, aber auch für andere Todesursachen. Die sozioökonomischen Mortalitätsungleichheiten nahmen bereits vor der COVID-19-Pandemie zu und verschärften sich in den ersten Jahren der Pandemie weiter. Hätten alle Regionen die gleiche Mortalität wie jene im niedrigsten Deprivationsquintil, läge die vorzeitige Sterblichkeit insgesamt 13 % niedriger. Diskussion: Die zunehmende Ungleichheit in der vorzeitigen Sterblichkeit zwischen deprivierten und wohlhabenden Regionen verdeutlicht, dass die Herstellung gleichwertiger Lebensverhältnisse im Bundesgebiet auch für die Verringerung der gesundheitlichen Ungleichheit ein wichtiges Handlungsfeld darstellt.

HIV infections which are diagnosed at advanced stages are associated with significantly poorer health outcomes. In Germany, the proportion of persons living with HIV who are diagnosed at later stages has remained continuously high. This study examined the impact of regional socioeconomic deprivation on the timing of HIV diagnosis. We used data from the national statutory notification of newly diagnosed HIV infections between 2011 and 2018 with further information on the timing of diagnosis determined by the BED-Capture-ELISA test (BED-CEIA) and diagnosing physicians. Data on regional socioeconomic deprivation were derived from the German Index of Socioeconomic Deprivation (GISD). Outcome measures were a non-recent infection based on the BED-CEIA result or an infection at the stage of AIDS. The effect of socioeconomic deprivation on the timing of diagnosis was analysed using multivariable Poisson regression models with cluster-robust error variance. Overall, 67.5% (n = 10,810) of the persons were diagnosed with a non-recent infection and 15.2% (n = 2746) with AIDS. The proportions were higher among persons with heterosexual contact compared to men who have sex with men (MSM) (76.8% non-recent and 14.9% AIDS vs. 61.7% non-recent and 11.4% AIDS). MSM living in highly deprived regions in the countryside (< 100 k residents) were more likely to have a non-recent infection (aPR: 1.16, 95% CI: 1.05–1.28) as well as AIDS (aPR: 1.41, 95% CI: 1.08–1.85) at the time of diagnosis compared to MSM in less deprived regions in the countryside. No differences were observed among MSM from towns (100 k ≤ 1 million residents) or major cities (≥ 1 million residents), and no differences overall in the heterosexual transmission group. An effect of socioeconomic deprivation on the timing of HIV diagnosis was found only in MSM from countryside regions. We suggest that efforts in promoting HIV awareness and regular HIV testing are increased for heterosexual persons irrespective of socioeconomic background, and for MSM with a focus on those living in deprived regions in the countryside.

Combining the frameworks of fundamental causes theory and diffusion of innovation, scholars had anticipated a delayed COVID-19 vaccination uptake for people in lower socioeconomic position depending on the socioeconomic context. We qualify these propositions and analyze educational differences in COVID-19 vaccination status over the first ten months of Germany’s vaccination campaign in 2021. Data from the study “Corona Monitoring Nationwide” (RKI-SOEP-2), collected between November 2021 and February 2022, is linked with district-level data of the German Index of Socioeconomic Deprivation (GISD). We estimated the proportion of people with at least one vaccination dose stratified by educational groups and within different settings of regional socioeconomic deprivation at three time points. Logistic multilevel regression models were applied to adjust for multiple covariates and to test cross-level-interactions between educational levels and levels of area-level socioeconomic deprivation. Vaccination rates were lower among respondents with lower education. With increasing area-level socioeconomic deprivation, educational differences were larger due to particularly low vaccination rates in groups with low education levels. The analysis of vaccination timing reveals that educational gaps and gaps by area-level socioeconomic deprivation had appeared early in the vaccination campaign and did not close completely before the 4th wave of COVID-19 infections

Research shows that there is an increased risk of SARS-CoV-2 infection in migrants and ethnic minorities. However, increasing evidence indicates that socio-economic factors, such as employment, education and income, contribute to the association between migrant status and SARS-CoV-2 infection. This study aimed to examine the association between migrant status and the risk of SARS-CoV-2 infection in Germany and to discuss potential explanations for these associations. This was a cross-sectional study. Data from the German COVID-19 Snapshot Monitoring online survey were analysed, and hierarchical multiple linear regression models were used to calculate the probabilities of self-reported SARS-CoV-2 infection. Predictor variables were integrated in a stepwise method as follows: (1) migrant status (defined by own or parental country of birth other than Germany); (2) gender, age and education; (3) household size; (4) household language; and (5) occupation in the health sector, including an interaction term of migrant status (yes) and occupation in the health sector (yes). Of 45,858 participants, 3.5% reported a SARS-CoV-2 infection, and 16% were migrants. Migrants, participants in large households, those speaking a language other than German in their household and those working in the health sector were more likely to report SARS-CoV-2 infection. The probability of reporting SARS-CoV-2 infection was 3.95 percentage points higher for migrants than non-migrants; this probability decreased when integrating further predictor variables. The strongest association of reporting a SARS-CoV-2 infection was observed for migrants working in the health sector. Migrants and health sector employees, and especially migrant health workers, are at an increased risk of SARS-CoV-2 infection. The results show that the risk of SARS-CoV-2 infection is determined by living and working conditions rather than migrant status.