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影响新冠疫情曲线的因素:多国分析。

Factors shaping the COVID-19 epidemic curve: a multi-country analysis.

机构信息

Department of Preventive Medicine, Kyung Hee University School of Medicine, Seoul, Korea.

Global Health, School of Public Health and Community Medicine, Institute of Medicine, University of Gothenburg, Medicinaregatan 18A, 41390, Gothenburg, Sweden.

出版信息

BMC Infect Dis. 2021 Oct 2;21(1):1032. doi: 10.1186/s12879-021-06714-3.

Abstract

BACKGROUND

Lockdown measures are the backbone of containment measures for the COVID-19 pandemic both in high-income countries (HICs) and low- and middle-income countries (LMICs). However, in view of the inevitably-occurring second and third global covid-19 wave, assessing the success and impact of containment measures on the epidemic curve of COVID-19 and people's compliance with such measures is crucial for more effective policies. To determine the containment measures influencing the COVID-19 epidemic curve in nine targeted countries across high-, middle-, and low-income nations.

METHODS

Four HICs (Germany, Sweden, Italy, and South Korea) and five LMICs (Mexico, Colombia, India, Nigeria, and Nepal) were selected to assess the association using interrupted time series analysis of daily case numbers and deaths of COVID-19 considering the following factors: The "stringency index (SI)" indicating how tight the containment measures were implemented in each country; and the level of compliance with the prescribed measures using human mobility data. Additionally, a scoping review was conducted to contextualize the findings.

RESULTS

Most countries implemented quite rigorous lockdown measures, particularly the LMICs (India, Nepal, and Colombia) following the model of HICs (Germany and Italy). Exceptions were Sweden and South Korea, which opted for different strategies. The compliance with the restrictions-measured as mobility related to home office, restraining from leisure activities, non-use of local transport and others-was generally good, except in Sweden and South Korea where the restrictions were limited. The endemic curves and time-series analysis showed that the containment measures were successful in HICs but not in LMICs.

CONCLUSION

The imposed lockdown measures are alarming, particularly in resource-constrained settings where such measures are independent of the population segment, which drives the virus transmission. Methods for examining people's movements or hardships that are caused by covid- no work, no food situation are inequitable. Novel and context-adapted approach of dealing with the COVID-19 crisis are therefore crucial.

摘要

背景

封锁措施是高收入国家(HICs)和中低收入国家(LMICs)控制 COVID-19 大流行的核心措施。然而,鉴于不可避免的第二波和第三波全球 COVID-19 浪潮,评估控制措施对 COVID-19 疫情曲线和人们对这些措施的遵守情况对于制定更有效的政策至关重要。为了确定影响高、中、低收入国家 COVID-19 疫情曲线的控制措施。

方法

选择了四个 HICs(德国、瑞典、意大利和韩国)和五个 LMICs(墨西哥、哥伦比亚、印度、尼日利亚和尼泊尔),使用中断时间序列分析方法,考虑以下因素,评估每天 COVID-19 病例和死亡人数的关联:“严格指数(SI)”,表明每个国家实施的控制措施的严格程度;以及使用人类流动性数据评估遵守规定措施的程度。此外,还进行了范围综述以背景化研究结果。

结果

大多数国家实施了相当严格的封锁措施,特别是印度、尼泊尔和哥伦比亚等 LMICs 效仿了 HICs(德国和意大利)的模式。瑞典和韩国是例外,它们选择了不同的策略。限制措施的遵守情况——衡量与在家办公、限制休闲活动、不使用当地交通工具等相关的流动性——总体上较好,除了瑞典和韩国,这两个国家的限制措施有限。地方性曲线和时间序列分析表明,封锁措施在 HICs 中是成功的,但在 LMICs 中则不然。

结论

实施的封锁措施令人震惊,特别是在资源有限的情况下,这些措施不受人口群体的影响,而人口群体是病毒传播的驱动因素。检查人们因 COVID-19 而无法工作、无法获得食物等情况的移动或困难的方法是不公平的。因此,必须采取新的和适应背景的方法来应对 COVID-19 危机。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d18/8487489/e0b6c9f67997/12879_2021_6714_Fig1_HTML.jpg

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