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按国家经济排名划分的COVID-19趋势、公共限制政策和疫苗接种状况:来自110个国家的纵向研究

COVID-19 trends, public restrictions policies and vaccination status by economic ranking of countries: a longitudinal study from 110 countries.

作者信息

Park Myung-Bae, Ranabhat Chhabi Lal

机构信息

Department of Gerontology Health and Welfare, Pai Chai University, Daejeon, Republic of Korea.

Department of Health Promotion and Administration, Eastern Kentucky University, Richmond, KY, USA.

出版信息

Arch Public Health. 2022 Aug 24;80(1):197. doi: 10.1186/s13690-022-00936-w.

Abstract

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic has transitioned to a third phase and many variants have been originated. There has been millions of lives loss as well as billions in economic loss. The morbidity and mortality for COVID-19 varies by country. There were different preventive approaches and public restrictions policies have been applied to control the COVID-19 impacts and usually measured by Stringency Index. This study aimed to explore the COVID-19 trend, public restriction policies and vaccination status with economic ranking of countries.

METHODS

We received open access data from Our World in Data. Data from 210 countries were available. Countries (n = 110) data related to testing, which is a key variable in the present study, were included for the analysis and remaining 100 countries were excluded due to incomplete data. The analysis period was set between January 22, 2020 (when COVID-19 was first officially reported) and December 28, 2021. All analyses were stratified by year and the World Bank income group. To analyze the associations among the major variables, we used a longitudinal fixed-effects model.

RESULTS

Out of the 110 countries included in our analysis, there were 9 (8.18%), 25 (22.72%), 31 (28.18%), and 45 (40.90%) countries from low income countries (LIC), low and middle income countries (LMIC), upper middle income countries (UMIC) and high income countries (HIC) respectively. New case per million was similar in LMIC, UMIC and HIC but lower in LIC. The number of new COVID-19 test were reduced in HIC and LMIC but similar in UMIC and LIC. Stringency Index was negligible in LIC and similar in LMIC, UMIC and HIC. New positivity rate increased in LMIC and UMIC. The daily incidence rate was positively correlated with the daily mortality rate in both 2020 and 2021. In 2020, Stringency Index was positive in LIC and HIC but a negative association in LMIC and in 2021 there was a positive association between UMIC and HIC. Vaccination coverage did not appear to change with mortality in 2021.

CONCLUSION

New COVID-19 cases, tests, vaccinations, positivity rates, and Stringency indices were low in LIC and highest in UMIC. Our findings suggest that the available resources of COVID-19 pandemic would be allocated by need of countries; LIC and UMIC.

摘要

背景

2019年冠状病毒病(COVID-19)大流行已进入第三阶段,并且出现了许多变种。已经有数百万生命丧失,经济损失达数十亿美元。COVID-19的发病率和死亡率因国家而异。各国采取了不同的预防措施,并实施了公共限制政策以控制COVID-19的影响,通常用严格指数来衡量。本研究旨在探讨COVID-19趋势、公共限制政策和疫苗接种状况与各国经济排名的关系。

方法

我们从“Our World in Data”获取了开放获取数据。有来自210个国家的数据。纳入分析的国家(n = 110)有与检测相关的数据,检测是本研究的关键变量,其余100个国家因数据不完整而被排除。分析期设定为2020年1月22日(COVID-19首次正式报告之日)至2021年12月28日。所有分析按年份和世界银行收入组进行分层。为了分析主要变量之间的关联,我们使用了纵向固定效应模型。

结果

在我们分析的110个国家中,分别有9个(8.18%)、25个(22.72%)、31个(28.18%)和45个(40.90%)国家来自低收入国家(LIC)、中低收入国家(LMIC)、中高收入国家(UMIC)和高收入国家(HIC)。每百万人口中的新增病例数在中低收入国家、中高收入国家和高收入国家中相似,但在低收入国家较低。高收入国家和中低收入国家的新增COVID-19检测数量减少,但中高收入国家和低收入国家相似。严格指数在低收入国家可忽略不计,在中低收入国家、中高收入国家和高收入国家中相似。中低收入国家和中高收入国家的新增阳性率上升。2020年和2021年,每日发病率与每日死亡率均呈正相关。2020年,严格指数在低收入国家和高收入国家呈正相关,但在中低收入国家呈负相关,2021年,中高收入国家和高收入国家之间呈正相关。2021年,疫苗接种覆盖率似乎与死亡率无关。

结论

低收入国家的新增COVID-19病例、检测、疫苗接种、阳性率和严格指数较低,中高收入国家最高。我们的研究结果表明,COVID-19大流行的可用资源将根据各国(低收入国家和中高收入国家)的需求进行分配。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1df8/9400224/00cad83d32cb/13690_2022_936_Fig1_HTML.jpg

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