[2020 - 2022年刚果民主共和国中部地区Covid-19流行病学特征]。

El-Mouksitou Akinocho, Matthieu Kasongo, Kristel Moerman, Felipe Sere, Yves Coppieters
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引用次数: 1

摘要

刚果民主共和国经历了SARS-CoV-2的广泛社区传播,并从2020年3月至2022年3月连续记录了四波。本研究的目的是确定中部刚果省这些流行波期间Covid-19患者的社会人口统计学特征,并确定与死亡相关的因素。材料和方法:这是一项来自省级监测系统的Covid-19数据的横断面研究。数据包括流行病学监测数据、实验室(检测)数据、医院数据和患者随访数据。我们确定了整个期间阳性病例的特征,并对与死亡相关的因素进行了逻辑回归。结果:在连续几波疫情中,全省共报告阳性病例9573例,其中第一波546例,第四波6346例。年龄介乎25至64岁的人士当中,每10人有7人呈阳性。马塔迪、莫安达和姆班扎-恩贡古地区受影响最严重。年龄大于64岁[OR: 7.2 CI:5.1-10.3]和波2 [OR: 4.4 CI:1.6-12.4]是与死亡相关的统计学因素。结论:与其他非洲国家一样,年龄、合并症、较高的社会专业水平和生活在城市地区是严重形式的疾病和死亡的主要危险因素。我们的分析强调了收集和分析省级以下的几个流行病学变量的重要性,以便更好地持续了解情况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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[Epidemiological characteristics of the Covid-19 epidemic between 2020 and 2022 in Kongo central, DRC].

Introduction: The Democratic Republic of Congo (DRC) has experienced widespread community transmission of SARS-CoV-2 and has recorded four successive waves from March 2020 to March 2022. The objective of this study is to determine the socio-demographic characteristics of Covid-19 patients during these epidemic waves in the province of Kongo central and to identify factors associated with deaths.

Material and methods: This is a cross-sectional study of Covid-19 data from the provincial surveillance system. The data consisted of epidemiological surveillance data, laboratory data (tests), hospital data and patient follow-up data. We determined the characteristics of positive cases throughout the period and implemented logistic regression of factors associated with death.

Results: During the successive waves, 9, 573 positive cases were reported in the province, 546 cases in the first wave and 6, 346 in the fourth wave. Seven positive cases out of 10 concerned people aged 25 to 64. The districts of Matadi, Moanda and Mbanza-Ngungu were the most affected. Age above 64 [OR: 7.2 CI:5.1-10.3] and wave 2 [OR: 4.4 CI:1.6-12.4] were the factors statistically associated with death.

Conclusion: As in other African settings, age, comorbidities, higher socio-professional level and living in urban areas were the major risk factors for severe forms of the disease and death. Our analysis underlines the importance of collecting and analysing several epidemiological variables down to the provincial level over time for a better continuous knowledge of the situation.

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