Evidence map›Paper›PMID 41492749›Full record

ArticleZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences

[Association of public health and social measures with the effectiveness of COVID-19 epidemic control].

Huiying Zong, Donghe Li, Yinhuang Dai, Jingtao Zhou, Hao Huang, Guoqing Hu

Abstract readEnglish Abstract
In one paragraph

Article in Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Huiying ZongMedical Records Management and Statistical Information Center, Xiangya Hospital, Central South University, Changsha 410008. zonghuiying@csu.edu.cn.
Donghe LiDepartment of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410013, China. 236912076@csu.edu.cn.
Yinhuang DaiDepartment of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410013, China.
Jingtao ZhouDepartment of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410013, China.
Hao HuangDepartment of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410013, China.
Guoqing HuDepartment of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410013, China. huguoqing@csu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesPublic health and social measures are essential tools for countries to control epidemic transmission but may also disrupt normal socioeconomic activities. This study aims to analyze differences in public health and social measures policy stringency, temporal trends, and their association with corona virus disease 2019 (COVID-19) control outcomes in 118 countries from January 2020 to September 2022, providing evidence to support the formulation of scientifically grounded public health and social measures policies.

methodsBoxplots were used to describe the distribution of overall and individual public health and social measures policy stringency scores across 118 countries during the pandemic. Linear and nonlinear models were fitted to examine temporal trends in public health and social measures policy stringency. A two-way fixed-effects model was applied to analyze the association between public health and social measures policy stringency and the effective reproduction number of COVID-19.

resultsThe overall public health and social measures stringency scores across the 188 countries ranged from 7.78 to 69.75. Among these countries, temporal trend models for public health and social measures stringency were statistically significant in 108 countries (all third-order polynomial models), with coefficients of determination exceeding 0.25. Overall public health and social measures stringency increased over time in 59 countries but decreased in 49 countries. After adjusting for covariates, country-level fixed effects, and time fixed effects, the overall public health and social measures policy stringency score was negatively associated with effective reproduction number (

conclusionsDuring the COVID-19 pandemic, the average intensity of public health and social measures implementation varied widely across 118 countries. School closures, workplace closures, gathering restrictions, domestic movement restrictions, and mask-wearing measures effectively curbed COVID-19 transmission, whereas the effectiveness of international travel restrictions diminished over time.

Indexed as

COVID-19Health PolicyPandemicsPublic HealthHumanscorona virus disease 2019effective reproduction numberpolicy stringencypublic health and social measuresvaccination

Identifiers

PMID41492749
PMCPMC12740735

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.