Vaccine effectiveness against transmission (VET) of SARS-CoV-2-infection can be estimated from secondary attack rates observed during contact tracing. We estimated VET, the vaccine-effect on infectiousness of the index case and susceptibility of the high-risk exposure contact (HREC). We fitted RT-PCR-test results from HREC to immunity status (vaccine schedule, prior infection, time since last immunity-conferring event), age, sex, calendar week of sampling, household, background positivity rate and dominant VOC using a multilevel Bayesian regression-model. We included Belgian data collected between January 2021 and January 2022. For primary BNT162b2-vaccination we estimated initial VET at 96% (95%CI 95–97) against Alpha, 87% (95%CI 84–88) against Delta and 31% (95%CI 25–37) against Omicron. Initial VET of booster-vaccination (mRNA primary and booster-vaccination) was 87% (95%CI 86–89) against Delta and 68% (95%CI 65–70) against Omicron. The VET-estimate against Delta and Omicron decreased to 71% (95%CI 64–78) and 55% (95%CI 46–62) respectively, 150–200 days after booster-vaccination. Hybrid immunity, defined as vaccination and documented prior infection, was associated with durable and higher or comparable (by number of antigen exposures) protection against transmission. While we observed VOC-specific immune-escape, especially by Omicron, and waning over time since immunization, vaccination remained associated with a reduced risk of SARS-CoV-2-transmission.

The objective of this study was to investigate the incidence and risk factors associated with COVID-19 vaccine breakthrough infections. We included all persons ≥18 years that had been fully vaccinated against COVID-19 for ≥14 days, between 1 February 2021 and 5 December 2021, in Belgium. The incidence of breakthrough infections (laboratory confirmed SARS-CoV-2-infections) was determined. Factors associated with breakthrough infections were analyzed using COX proportional hazard models. Among 8,062,600 fully vaccinated adults, we identified 373,070 breakthrough infections with an incidence of 11.2 (95%CI 11.2–11.3)/100 person years. Vaccination with Ad26.COV2.S (HR1.54, 95%CI 1.52–1.56) or ChAdOx1 (HR1.68, 95%CI 1.66–1.69) was associated with a higher risk of a breakthrough infection compared to BNT162b2, while mRNA-1273 was associated with a lower risk (HR0.68, 95%CI 0.67–0.69). A prior COVID-19-infection was protective against a breakthrough infection (HR0.23, 95%CI 0.23–0.24), as was an mRNA booster (HR0.44, 95%CI 0.43–0.45). During a breakthrough infection, those who had a prior COVID-19 infection were less likely to have COVID-19 symptoms of almost all types than naïve persons. We identified risk factors associated with breakthrough infections, such as vaccination with adenoviral-vector vaccines, which could help inform future decisions on booster vaccination strategies. A prior COVID-19 infection lowered the risk of breakthrough infections and of having symptoms, highlighting the protective effect of hybrid immunity.

Vaccination has played a major role in overcoming the COVID-19 pandemic. However, vaccination status can be influenced by demographic and socio-economic factors at individual and area level. In the context of the LINK-VACC project, the Belgian vaccine register for the COVID-19 vaccination campaign was linked at individual level with other registers, notably the COVID-19 laboratory test results and demographic and socio-economic variables from the DEMOBEL database. The present article aims at investigating to which extent COVID-19 vaccination status is associated with area level and/or individual level demographic and socioeconomic factors. From a sample of all individuals tested for SARS-CoV-2 (LINK-VACC sample) demographic and socio-economic indicators are derived and their impact on vaccination coverages at an aggregated geographical level (municipality) is quantified. The same indicators are calculated for the full Belgian population, allowing to assess the representativeness of the LINK-VACC sample with respect to the impact of demographic and socioeconomic disparities on vaccination uptake. In a second step, hierarchical models are fitted to the individual level LINK-VACC data to disentangle the individual and municipality effects allowing to evaluate the added value of the availability of individual level data in this context. The most important effects observed at the individual level are reflected in the aggregated data at the municipality level. Multilevel analyses show that most of the demographic and socio-economic impacts on vaccination are captured at the individual level, although accounting for area level in individual level analyses improve the overall description.

Objective: This study aimed to investigate factors influencing the uptake of first and second COVID-19 booster vaccines among adults in Belgium, particularly age, sex, region of residence and laboratory confirmed COVID-19 infection history. Results: A binomial regression model was used with having received the first or second booster as outcome and age, sex, region of residence and infection history as fixed variables. Among adults, there was generally a higher uptake to receive the first booster among older age groups compared to younger ones. Females, individuals residing in Flanders and those with no previous COVID-19 infection were more likely to receive the first booster. For the second booster, the same age trend was seen as for the first booster. Males, individuals residing in Flanders and those who tested positive for COVID-19 once after first booster were more likely to receive the second booster. Individuals with multiple positive COVID-19 tests before and after primary course or first booster were less likely to receive the subsequent booster dose compared to COVID-naïve individuals. This information could be used to guide future vaccination campaigns during a pandemic and can provide valuable insights into booster uptake patterns.

1. The COVID-19 vaccination campaign in Belgium aimed to reduce disease spread and severity. We quantified the observed vaccine effectiveness (VE) against symptomatic infection (VEi) and hospitalization (VEh). Exhaustive data on testing and vaccination was combined with a clinical hospital survey. We estimated VEi using a test negative design and VEh using a proportional hazard analysis. We controlled for prior infection, age, sex, province of residence and calendar week of sampling. Variant of concern specific VE-estimates were obtained by time since vaccination from July 2021 to April 2022. We included 1,433,135 persons. VEi against Delta waned from an initial estimate of 81% (95%CI 80- 82) to 56% (95%CI 56-57) 100-150 days after primary-vaccination. Booster-vaccination increased initial VEi to 84% (95%CI 83-85). Against Omicron, an initial VEi of 37% (95%CI 34-40) waned to 18% (95%CI 17-20) 100-150 days after primary-vaccination. Booster-vaccination increased VEi to 52% (95%CI 51-53) and waned to 25% (95%CI 24-27) 100-150 days after vaccination. Hybrid immunity conferred by prior infection and booster-vaccination outperformed booster-vaccination only even if the infection was over one year ago, 67% (95%CI 66-68). Initial VEh for booster-vaccination decreased from 93% (95%CI 93-94) against Delta to 87% (95%CI 85-89) against Omicron. VEh for Omicron waned to 66% (95%CI 63-70) 100-150 days after booster-vaccination. In conclusion, we report significant immune-escape by Omicron. VEh was less affected than VEi and immune-escape was attenuated by booster-vaccination. Waning further reduced VEi- and VEh- estimates. Infection-acquired immunity offered additional protection against symptomatic infection in vaccinated persons which lasted at least one year.

To effectively address the complexities of vaccination across the EU, EUVABECO’s 14 partners are implementing a comprehensive, interdisciplinary approach. Twelve pilot projects will be implemented from September 2024 to August 2025 in six MS (BE, DE, EL, LV, LU, PL, PT). These pilots will test innovative tools across five domains-medical, social, industrial, modelling and forecasting, and digital-to optimize vaccination outcomes: Medical/Clinical Tool: A decision support system that aids patients and healthcare professionals by providing current, evidence-based information tailored to individuals, thereby facilitating informed vaccination decisions. Social Tool: Data linkage on an individual level, to enhance the targeting and monitoring of vaccine campaigns, and ensuring equitable access to vaccines, especially for vulnerable populations. Industrial Tool: An electronic vaccine leaflet that boosts the flexibility and responsiveness of vaccine distribution by offering dynamic, real-time information in local languages to both healthcare providers and patients - regardless of the source and point of use of the vaccine. Modelling and Forecasting Tool: A disease simulator that models infection dynamics and evaluates the impact of public health interventions, crucial for strategic planning and resource allocation. Digital Tool: A citizen-held digital vaccination card that enables individuals to maintain a comprehensive, accessible record of their own vaccination histories, enhancing continuity of care across borders.