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孟加拉国 COVID-19 大流行期间的超额死亡率——来自农村调查的证据。

Excess mortality during COVID-19 pandemic in Bangladesh - evidence from a rural survey.

机构信息

Maternal and Child Health Division, International Centre for Diarrhoeal Disease Research, Dhaka, Bangladesh.

Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden.

出版信息

J Glob Health. 2024 Oct 25;14:05031. doi: 10.7189/jogh.14.05031.

DOI:10.7189/jogh.14.05031
PMID:39450614
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11503508/
Abstract

BACKGROUND

The coronavirus disease 2019 (COVID-19) had a profound impact worldwide. In Bangladesh, the official number of deaths for COVID-19 was around 29 000. However, many countries including Bangladesh experienced substantial underreporting of COVID-19 deaths due to lack of complete national civil registration system. This study aims to estimate excess mortality in 2020, identify risk factors, and determine leading causes of death in Bangladesh.

METHODS

In February 2021, we conducted a cross-sectional household survey in Sitakunda, a subdistrict of Chattogram, identifying deaths from January 2018 to December 2020. Excess mortality was quantified using the p-score and incidence rate ratio (IRR) utilising Poisson segmented regression. We employed the InterVA-5 algorithm to attribute causes of death. Proportional distribution and cause-specific mortality rates (CSMR) per 100 000 individuals were compared between pre-pandemic and pandemic periods.

RESULTS

Among 1748 deaths from 25 669 households, we found 1.4 (95% confidence interval (CI) = 1.2-1.4) times excess mortality in 2020 compared to 2018-2019. Leading causes of death in 2020 included cardiac disease (CSMR = 121.0, CI = 115.8-127.3), stroke (CSMR = 108.0, CI = 102.6-114.0), and acute respiratory infection (CSMR = 61.0, CI = 55.1-66.5), all displaying significantly higher mortality rates than in previous years. Older age (IRR = 1.6), less education (IRR = 1.8), and lower socio-economic groups (IRR = 2.1) had higher mortality rates in 2020 compared to pre-pandemic years.

CONCLUSION

Our study suggests high rural excess mortality during COVID-19 including cardiac disease, stroke and acute respiratory infection as the leading causes of deaths. We require targeted strategies to identify high-risk patients with comorbidity and social vulnerabilities that contribute to mortality to guide the preparedness strategy for future pandemics.

摘要

背景

2019 年冠状病毒病(COVID-19)在全球范围内造成了深远影响。在孟加拉国,COVID-19 的官方死亡人数约为 29000 人。然而,由于缺乏完整的国家民事登记系统,许多国家(包括孟加拉国)都存在 COVID-19 死亡人数的大量漏报。本研究旨在估计 2020 年的超额死亡率,确定风险因素,并确定孟加拉国的主要死亡原因。

方法

2021 年 2 月,我们在吉大港的一个分区锡塔库达进行了一项横断面家庭调查,确定了 2018 年 1 月至 2020 年 12 月期间的死亡人数。使用分段泊松回归分析 p 分数和发病率比值(IRR)来量化超额死亡率。我们采用 InterVA-5 算法来归因于死亡原因。比较了大流行前和大流行期间每 100000 人个体的比例分布和特定原因死亡率(CSMR)。

结果

在来自 25669 户家庭的 1748 例死亡中,我们发现 2020 年的超额死亡率是 2018-2019 年的 1.4 倍(95%置信区间(CI)=1.2-1.4)。2020 年的主要死亡原因包括心脏病(CSMR=121.0,CI=115.8-127.3)、中风(CSMR=108.0,CI=102.6-114.0)和急性呼吸道感染(CSMR=61.0,CI=55.1-66.5),所有这些疾病的死亡率都明显高于往年。与大流行前年份相比,年龄较大(IRR=1.6)、受教育程度较低(IRR=1.8)和社会经济地位较低(IRR=2.1)的人群在 2020 年的死亡率更高。

结论

我们的研究表明,在 COVID-19 期间,农村地区的超额死亡率较高,包括心脏病、中风和急性呼吸道感染,这些是死亡的主要原因。我们需要采取有针对性的策略,确定患有合并症和社会脆弱性的高危患者,这些因素导致死亡率上升,以指导为未来的大流行做好准备的战略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cae3/11503508/ded8edd17bd5/jogh-14-05031-F5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cae3/11503508/4b9511cc2c19/jogh-14-05031-F1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cae3/11503508/349f8185c9ac/jogh-14-05031-F2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cae3/11503508/5388b2678e87/jogh-14-05031-F3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cae3/11503508/18e3ac739a1b/jogh-14-05031-F4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cae3/11503508/ded8edd17bd5/jogh-14-05031-F5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cae3/11503508/4b9511cc2c19/jogh-14-05031-F1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cae3/11503508/349f8185c9ac/jogh-14-05031-F2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cae3/11503508/5388b2678e87/jogh-14-05031-F3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cae3/11503508/18e3ac739a1b/jogh-14-05031-F4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cae3/11503508/ded8edd17bd5/jogh-14-05031-F5.jpg

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