Participation in prevention measures during the corona pandemic in Germany in 2020/21

Background

The availability and use of preventive measures such as diet courses, sports groups, and counselling services were hindered by containment measures set by the German government and local authorities to reduce the spread of the COVID-19 pandemic. Regulations on contact restriction, closure of sport and leisure facilities made it difficult to use prevention programs in 2020 and 2021. So far, no information is available to what extent the participation of the population in prevention programs has changed as a result of the pandemic and whether there are group differences regarding socio-demographic characteristics.

Methods

We used standardized telephone interviews of the adult German-speaking population to ask for changes in the participation in prevention measures in the last 12 months as a result of the corona pandemic. The data were collected between 17.3.2021 and 18.08.2021 in four cross-sectional surveys and is representative of the population aged 18 years and older in Germany. Analyses of the weighted and pooled data were conducted for n = 3,998 individuals by gender, age and education.

Results

Almost one third of the respondents reported a lower use of programs (28.3%). An unchanged use of the programs was stated by 6.5%, a higher use by 2.1%. 63.2% said they did not use such programs. More women (33.6%) than men (22.7%) reported reduced pandemic-related use (p < 0.0001). For women, we observed a difference between age and education groups, but not for men: Lower participation was reported by a higher proportion of older than younger women (p < 0.0001). More women with high education reported an increased use than ones with low education (p = 0.003) (preliminary results).

Conclusions

The observed differences indicate to different barriers to use prevention measures during the pandemic, especially for women. To promote equal opportunities, resilient structures of prevention and health promotion should be built for future crises in advance.

Key messages

A dynamic transmission model to calculate vaccination coverage needed to control COVID-19 in Germany

Background

Control of the 2019 coronavirus disease (COVID-19) pandemic in Germany and return to pre-pandemic behaviour can only be achieved through natural or vaccine-induced immunity. Sufficient vaccine capacity promotes interest in the necessary and feasible target vaccination coverage.

Methods

An age and risk group stratified SEIR transmission model was used to assess the impact of vaccination coverage ranging 65%-95% for 12-59-year-olds and 90%-95% for ≥ 60-year-olds on COVID-19 incidence and intensive care unit (ICU) utilization between 01.07.2021-31.03.2022. Separate implementation of licensed vaccines allows to consider different efficacies, delivery rates and age-specific national vaccination recommendations. The analysis was conducted under different assumptions about contact behaviour during summer, reduction of daily contacts with increasing number of cases, daily vaccination uptake and the dominant variant. Data from the COVIMO study (N = 3004, data collection: 17.05.-09.06.2021) were used to define the population percentage willing to be vaccinated.

Results

The COVIMO study indicates an achievable vaccination compliance rate of 83.9% among 12-59-year-olds and 94.8% among those ≥ 60-year-olds. Maximum incidence or ICU utilization during observation period decreases from 385 to 61 and 6220 to 2800, respectively, with an increase in vaccination coverage from 65% to 95% of 12-59-year-olds, 90% vaccination rate among ≥ 60-year-olds, compared to pre-pandemic reduced contact behaviour in summer and reduction of contacts as case numbers increase.

Conclusions

The vaccination campaign should be continued at high intensity until at least 85% of 12-59-year-olds or 90% of ≥ 60-year-olds are fully vaccinated against COVID-19. Based on the population's willingness to be vaccinated, this goal seemed feasible.

Key messages

• Mathematical modeling was used to determine an evidence-based target vaccination coverage of ≥ 85%.

• Expertise in modeling should be further strengthened.