I-BioStat, Data Science Institute, Hasselt University, 3500 Hasselt, Belgium.
I-BioStat, Data Science Institute, Hasselt University, 3500 Hasselt, Belgium; I-BioStat, Leuven Biostatistics and Statistical Bioinformatics Centre, KU Leuven, 3000 Leuven, Belgium.
Spat Spatiotemporal Epidemiol. 2024 Jun;49:100660. doi: 10.1016/j.sste.2024.100660. Epub 2024 May 20.
Belgium experienced multiple COVID-19 waves that hit various groups in the population, which changed the mortality pattern compared to periods before the pandemic. In this study, we investigated the geographical excess mortality trend in Belgium during the first year of the COVID-19 pandemic.
We retrieved the number of deaths and population data in 2020 based on gender, age, and municipality of residence, and we made a comparison with the mortality data in 2017-2019 using a spatially discrete model.
Excess mortality was significantly associated with age, gender, and COVID-19 incidence, with larger effects in the second half of 2020. Most municipalities had higher risks of mortality with a number of exceptions in the northeastern part of Belgium. Some discrepancies in excess mortality were observed between the north and south regions.
This study offers useful insight into excess mortality and will aid local and regional authorities in monitoring mortality trends.
比利时经历了多波 COVID-19 疫情，这些疫情袭击了人群中的不同群体，与大流行前的时期相比，改变了死亡率模式。在这项研究中，我们调查了 COVID-19 大流行第一年期间比利时的地理性超额死亡率趋势。
我们根据性别、年龄和居住的直辖市检索了 2020 年的死亡人数和人口数据，并使用空间离散模型将其与 2017-2019 年的死亡率数据进行了比较。
超额死亡率与年龄、性别和 COVID-19 发病率显著相关，在 2020 年下半年的影响更大。大多数直辖市的死亡率风险更高，但比利时东北部的一些直辖市除外。在北部和南部地区之间观察到超额死亡率存在一些差异。
这项研究提供了对超额死亡率的有用见解，并将有助于地方和地区当局监测死亡率趋势。
