COVID-19高水平应对时间与日发病高峰时间之间的关系:对148个国家政府严格程度指数的分析

IF 4.8 1区 医学 Q1 INFECTIOUS DISEASES
Yan Ma, Shiva Raj Mishra, Xi-Kun Han, Dong-Shan Zhu
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引用次数: 25

摘要

背景:2019冠状病毒病(COVID-19)大流行在不同国家或地区的传播动态和严重程度不同。政府政策反应的不同或许可以解释其中的一些差异。我们的目的是比较世界各国政府对COVID-19传播的反应,以检验反应水平、反应时间与流行病轨迹之间的关系。方法:使用冠状病毒政府应对追踪系统(OxCGRT)收集的免费公开数据。从2020年1月1日至5月1日,系统收集了反映148个国家政府反应的9个子指标。对这些分项指标进行评分,并汇总成一个共同的严格程度指数(SI,一个介于0到100之间的数值),该指数反映了政府日常应对的总体严格程度。采用基于群的轨迹建模方法对SI轨迹进行识别。使用多变量线性回归模型来分析达到高水平SI的时间与达到每日新病例高峰数的时间之间的关系。结果:根据疫情开始应对的时间,我们确定了COVID-19传播的四个应对轨迹:1月13日之前、1月13日至2月12日、2月12日至3月11日,以及最后一个阶段——3月11日(世卫组织宣布COVID-19大流行当日)开始。随着COVID-19的进一步传播,各国政府的应对措施有所升级,但各国之间存在很大差异。在调整SI水平、地理区域和发病阶段后,从开始响应开始到高SI水平(SI > 80)的每早一天与每日新病例高峰数相关0.44(标准误差:0.08,P 2 = 0.65)。此外,自首次报告病例之日起,每早一天出现高SI水平与每日新病例高峰数早0.65天(标准误差:0.08,P 2 = 0.42)相关。结论:早开始高水平应对COVID-19与早到达每日新病例高峰数有关。这可能有助于减少流行病曲线趋于平缓至低传播水平的延迟。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

The relationship between time to a high COVID-19 response level and timing of peak daily incidence: an analysis of governments' Stringency Index from 148 countries.

The relationship between time to a high COVID-19 response level and timing of peak daily incidence: an analysis of governments' Stringency Index from 148 countries.

The relationship between time to a high COVID-19 response level and timing of peak daily incidence: an analysis of governments' Stringency Index from 148 countries.

The relationship between time to a high COVID-19 response level and timing of peak daily incidence: an analysis of governments' Stringency Index from 148 countries.

Background: The transmission dynamics and severity of coronavirus disease 2019 (COVID-19) pandemic is different across countries or regions. Differences in governments' policy responses may explain some of these differences. We aimed to compare worldwide government responses to the spread of COVID-19, to examine the relationship between response level, response timing and the epidemic trajectory.

Methods: Free publicly-accessible data collected by the Coronavirus Government Response Tracker (OxCGRT) were used. Nine sub-indicators reflecting government response from 148 countries were collected systematically from January 1 to May 1, 2020. The sub-indicators were scored and were aggregated into a common Stringency Index (SI, a value between 0 and 100) that reflects the overall stringency of the government's response in a daily basis. Group-based trajectory modelling method was used to identify trajectories of SI. Multivariable linear regression models were used to analyse the association between time to reach a high-level SI and time to the peak number of daily new cases.

Results: Our results identified four trajectories of response in the spread of COVID-19 based on when the response was initiated: before January 13, from January 13 to February 12, from February 12 to March 11, and the last stage-from March 11 (the day WHO declared a pandemic of COVID-19) on going. Governments' responses were upgraded with further spread of COVID-19 but varied substantially across countries. After the adjustment of SI level, geographical region and initiation stages, each day earlier to a high SI level (SI > 80) from the start of response was associated with 0.44 (standard error: 0.08, P < 0.001, R2 = 0.65) days earlier to the peak number of daily new case. Also, each day earlier to a high SI level from the date of first reported case was associated with 0.65 (standard error: 0.08, P < 0.001, R2 = 0.42) days earlier to the peak number of daily new case.

Conclusions: Early start of a high-level response to COVID-19 is associated with early arrival of the peak number of daily new cases. This may help to reduce the delays in flattening the epidemic curve to the low spread level.

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来源期刊
Infectious Diseases of Poverty
Infectious Diseases of Poverty Medicine-Public Health, Environmental and Occupational Health
CiteScore
16.70
自引率
1.20%
发文量
368
审稿时长
13 weeks
期刊介绍: Infectious Diseases of Poverty is a peer-reviewed, open access journal that focuses on essential public health questions related to infectious diseases of poverty. It covers a wide range of topics and methods, including the biology of pathogens and vectors, diagnosis and detection, treatment and case management, epidemiology and modeling, zoonotic hosts and animal reservoirs, control strategies and implementation, new technologies, and their application. The journal also explores the impact of transdisciplinary or multisectoral approaches on health systems, ecohealth, environmental management, and innovative technologies. It aims to provide a platform for the exchange of research and ideas that can contribute to the improvement of public health in resource-limited settings. In summary, Infectious Diseases of Poverty aims to address the urgent challenges posed by infectious diseases in impoverished populations. By publishing high-quality research in various areas, the journal seeks to advance our understanding of these diseases and contribute to the development of effective strategies for prevention, diagnosis, and treatment.
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