UK Small Area Health Statistics Unit, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
Eur J Public Health. 2023 Aug 1;33(4):695-703. doi: 10.1093/eurpub/ckad075.
Analyses of coronavirus disease 19 suggest specific risk factors make communities more or less vulnerable to pandemic-related deaths within countries. What is unclear is whether the characteristics affecting vulnerability of small communities within countries produce similar patterns of excess mortality across countries with different demographics and public health responses to the pandemic. Our aim is to quantify community-level variations in excess mortality within England, Italy and Sweden and identify how such spatial variability was driven by community-level characteristics.
We applied a two-stage Bayesian model to quantify inequalities in excess mortality in people aged 40 years and older at the community level in England, Italy and Sweden during the first year of the pandemic (March 2020-February 2021). We used community characteristics measuring deprivation, air pollution, living conditions, population density and movement of people as covariates to quantify their associations with excess mortality.
We found just under half of communities in England (48.1%) and Italy (45.8%) had an excess mortality of over 300 per 100 000 males over the age of 40, while for Sweden that covered 23.1% of communities. We showed that deprivation is a strong predictor of excess mortality across the three countries, and communities with high levels of overcrowding were associated with higher excess mortality in England and Sweden.
These results highlight some international similarities in factors affecting mortality that will help policy makers target public health measures to increase resilience to the mortality impacts of this and future pandemics.
对 2019 年冠状病毒病的分析表明，特定的风险因素使各国国内的某些社区更容易或更难受到与大流行相关的死亡影响。目前尚不清楚的是，影响国内小社区脆弱性的特征是否会在各国产生类似的模式，这些国家在人口结构和大流行期间对公共卫生的应对措施方面存在差异。我们的目的是量化英格兰、意大利和瑞典国内社区层面的超额死亡率，并确定社区层面特征如何导致这种空间变异性。
我们应用两阶段贝叶斯模型，在英格兰、意大利和瑞典，在大流行的第一年（2020 年 3 月至 2021 年 2 月），量化 40 岁及以上人群的社区层面超额死亡率的不平等。我们使用社区特征来衡量贫困、空气污染、生活条件、人口密度和人口流动作为协变量，以量化它们与超额死亡率的关系。
我们发现，在英格兰（48.1%）和意大利（45.8%），近一半的社区 40 岁以上男性的超额死亡率超过 300/100000，而瑞典这一比例为 23.1%。我们表明，贫困是这三个国家超额死亡率的一个强有力的预测因素，而且人口过度拥挤的社区与英格兰和瑞典的超额死亡率较高有关。
这些结果突出了一些影响死亡率的国际相似因素，这将有助于决策者针对公共卫生措施，提高对未来大流行的死亡率影响的应对能力。
