Hubin Pierre, Van den Borre Laura, Braeye Toon, Cavillot Lisa, Billuart Matthieu, Stouten Veerle, Nasiadka Léonore, Vermeiren Elias, Van Evercooren Izaak, Devleesschauwer Brecht, Catteau Lucy, van Loenhout Joris A F
Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Interface Demography, Department of Sociology, Vrije Universiteit Brussel, Brussels, Belgium.
Vaccine X. 2024 May 3;18:100496. doi: 10.1016/j.jvacx.2024.100496. eCollection 2024 Jun.
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 socio-economic 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 socio-economic 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.
疫苗接种在战胜新冠疫情中发挥了重要作用。然而，疫苗接种状况可能会受到个体层面和地区层面的人口统计学及社会经济因素的影响。在“LINK-VACC项目”的背景下，比利时新冠疫苗接种活动的疫苗接种登记册在个体层面与其他登记册相关联，特别是新冠病毒实验室检测结果以及来自DEMOBEL数据库的人口统计学和社会经济变量。本文旨在调查新冠疫苗接种状况在多大程度上与地区层面和/或个体层面的人口统计学及社会经济因素相关。从所有接受新冠病毒检测的个体样本（LINK-VACC样本）中得出人口统计学和社会经济指标，并对其在汇总地理层面（市镇）上对疫苗接种覆盖率的影响进行量化。为比利时全体人口计算相同的指标，从而能够评估LINK-VACC样本在人口统计学和社会经济差异对疫苗接种影响方面的代表性。第二步，将分层模型应用于个体层面的LINK-VACC数据，以区分个体和市镇的影响，从而能够评估在此背景下个体层面数据可用性的附加价值。在个体层面观察到的最重要影响反映在市镇层面的汇总数据中。多层次分析表明，尽管在个体层面分析中考虑地区层面会改善整体描述，但对疫苗接种的大多数人口统计学和社会经济影响是在个体层面捕捉到的。
