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利用社区死亡率指标推断叙利亚大马士革的 COVID-19 死亡率和传播动态。

Leveraging community mortality indicators to infer COVID-19 mortality and transmission dynamics in Damascus, Syria.

机构信息

MRC Centre for Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK.

Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK.

出版信息

Nat Commun. 2021 Apr 22;12(1):2394. doi: 10.1038/s41467-021-22474-9.

DOI:10.1038/s41467-021-22474-9
PMID:33888698
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8062464/
Abstract

The COVID-19 pandemic has resulted in substantial mortality worldwide. However, to date, countries in the Middle East and Africa have reported considerably lower mortality rates than in Europe and the Americas. Motivated by reports of an overwhelmed health system, we estimate the likely under-ascertainment of COVID-19 mortality in Damascus, Syria. Using all-cause mortality data, we fit a mathematical model of COVID-19 transmission to reported mortality, estimating that 1.25% of COVID-19 deaths (sensitivity range 1.00% - 3.00%) have been reported as of 2 September 2020. By 2 September, we estimate that 4,380 (95% CI: 3,250 - 5,550) COVID-19 deaths in Damascus may have been missed, with 39.0% (95% CI: 32.5% - 45.0%) of the population in Damascus estimated to have been infected. Accounting for under-ascertainment corroborates reports of exceeded hospital bed capacity and is validated by community-uploaded obituary notifications, which confirm extensive unreported mortality in Damascus.

摘要

COVID-19 大流行在全球范围内造成了大量死亡。然而,迄今为止,中东和非洲国家报告的死亡率明显低于欧洲和美洲。鉴于有报道称卫生系统不堪重负,我们估计在叙利亚大马士革可能低估了 COVID-19 的死亡率。我们利用全因死亡率数据,拟合了 COVID-19 传播的数学模型与报告的死亡率,估计截至 2020 年 9 月 2 日,1.25%的 COVID-19 死亡病例(敏感性范围为 1.00%至 3.00%)已被报告。截至 9 月 2 日,我们估计在大马士革可能有 4380 例(95%CI:3250 至 5550 例)COVID-19 死亡病例被遗漏,估计大马士革 39.0%(95%CI:32.5%至 45.0%)的人口受到感染。考虑到漏报情况,与医院床位容量超标的报告相符,并通过社区上传的讣告通知得到验证,这些通知证实了大马士革大量未报告的死亡人数。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a5b/8062464/4c14bbe0d91c/41467_2021_22474_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a5b/8062464/20508e6e6d26/41467_2021_22474_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a5b/8062464/9022667ad16b/41467_2021_22474_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a5b/8062464/905a99208c6a/41467_2021_22474_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a5b/8062464/3652051daa37/41467_2021_22474_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a5b/8062464/4c14bbe0d91c/41467_2021_22474_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a5b/8062464/20508e6e6d26/41467_2021_22474_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a5b/8062464/9022667ad16b/41467_2021_22474_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a5b/8062464/905a99208c6a/41467_2021_22474_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a5b/8062464/3652051daa37/41467_2021_22474_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a5b/8062464/4c14bbe0d91c/41467_2021_22474_Fig5_HTML.jpg

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