文章基本信息

标题：Heterogeneity in subnational mortality in the context of the COVID-19 pandemic: the case of Belgian districts in 2020
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作者：Benjamin-Samuel Schlüter ; Bruno Masquelier ; Carlo Giovanni Camarda 等
期刊名称：Archives of Public Health
印刷版ISSN：0778-7367
电子版ISSN：0778-7367
出版年度：2022
卷号：80
期号：1
页码：1-13
DOI：10.1186/s13690-022-00874-7
语种：English
出版社：BioMed Central
摘要：Abstract Background The COVID-19 pandemic has led to major shocks in mortality trends in many countries. Yet few studies have evaluated the heterogeneity of the mortality shocks at the sub-national level, rigorously accounting for the different sources of uncertainty. Methods Using death registration data from Belgium, we first assess change in the heterogeneity of districts’ standardized mortality ratios in 2020, when compared to previous years. We then measure the shock effect of the pandemic using district-level values of life expectancy, comparing districts’ observed and projected life expectancy, accounting for all sources of uncertainty (stemming from life-table construction at district level and from projection methods at country and district levels). Bayesian modelling makes it easy to combine the different sources of uncertainty in the assessment of the shock. This is of particular interest at a finer geographical scale characterized by high stochastic variation in annual death counts. Results The heterogeneity in the impact of the pandemic on all-cause mortality across districts is substantial: while some districts barely show any impact, the Bruxelles-Capitale and Mons districts experienced a decrease in life expectancy at birth of 2.24 (95% CI:1.33–3.05) and 2.10 (95% CI:0.86–3.30) years, respectively. The year 2020 was associated with an increase in the heterogeneity of mortality levels at a subnational scale in comparison to past years, measured in terms of both standardized mortality ratios and life expectancies at birth. Decisions on uncertainty thresholds have a large bearing on the interpretation of the results. Conclusion Developing sub-national mortality estimates taking careful account of uncertainty is key to identifying which areas have been disproportionately affected.