Evidence map›Paper›PMID 37644012›Full record

ArticleNature communications2023

Effects of public-health measures for zeroing out different SARS-CoV-2 variants.

Yong Ge, Xilin Wu, Wenbin Zhang, Xiaoli Wang, Die Zhang, Jianghao Wang, Haiyan Liu, Zhoupeng Ren, Nick W Ruktanonchai, Corrine W Ruktanonchai and 7 more

Abstract read
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

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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

17 authors.

Yong Ge *State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China. gey@lreis.ac.cn.ORCID http://orcid.org/0000-0002-5175-5812
Xilin Wu *State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.ORCID http://orcid.org/0000-0003-4288-7853
Wenbin Zhang *State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.ORCID http://orcid.org/0000-0002-9295-1019
Xiaoli Wang *Beijing Center for Disease Prevention and Control, Beijing, China.
Die ZhangState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.
Jianghao WangState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.ORCID http://orcid.org/0000-0001-5333-3827
Haiyan LiuMarine Data Center, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China.ORCID http://orcid.org/0000-0003-3158-0661
Zhoupeng RenState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.ORCID http://orcid.org/0000-0003-1766-2820
Nick W RuktanonchaiPopulation Health Sciences, Virginia Tech, Blacksburg, VA, USA.
Corrine W RuktanonchaiPopulation Health Sciences, Virginia Tech, Blacksburg, VA, USA.ORCID http://orcid.org/0000-0002-7889-3473
Eimear ClearyWorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.
Yongcheng YaoWorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.
Amy WesolowskiDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Derek A T CummingsDepartment of Biology and Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA.
Zhongjie LiSchool of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Andrew J TatemWorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.ORCID http://orcid.org/0000-0002-7270-941X
Shengjie LaiWorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK. Shengjie.Lai@soton.ac.uk.ORCID http://orcid.org/0000-0001-9781-8148

Funding

Human mobility models to forecast disease dynamics and the effectiveness of public health interventionsR01AI160780 · NIAID · JOHNS HOPKINS UNIVERSITY · PI CUMMINGS, DEREK A, WESOLOWSKI, AMY · 2021 to 2025
$3.3M
NIAID NIH HHS R01 AI160780
6 · The paper itself

Abstract

Targeted public health interventions for an emerging epidemic are essential for preventing pandemics. During 2020-2022, China invested significant efforts in strict zero-COVID measures to contain outbreaks of varying scales caused by different SARS-CoV-2 variants. Based on a multi-year empirical dataset containing 131 outbreaks observed in China from April 2020 to May 2022 and simulated scenarios, we ranked the relative intervention effectiveness by their reduction in instantaneous reproduction number. We found that, overall, social distancing measures (38% reduction, 95% prediction interval 31-45%), face masks (30%, 17-42%) and close contact tracing (28%, 24-31%) were most effective. Contact tracing was crucial in containing outbreaks during the initial phases, while social distancing measures became increasingly prominent as the spread persisted. In addition, infections with higher transmissibility and a shorter latent period posed more challenges for these measures. Our findings provide quantitative evidence on the effects of public-health measures for zeroing out emerging contagions in different contexts.

Indexed as

COVID-19Public HealthHumansPandemicsSARS-CoV-2

Identifiers

PMID37644012
PMCPMC10465600

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.