Evidence map›Paper›PMID 36945346›Full record

ArticleHeliyon2023

The COVID-19 pandemic in various restriction policy scenarios based on the dynamic social contact rate.

Hui Hu, Shuaizhou Xiong, Xiaoling Zhang, Shuzhou Liu, Lin Gu, Yuqi Zhu, Dongjin Xiang, Martin Skitmore

Abstract read
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

8 authors.

Hui HuEconomic Development Research Centre, Wuhan University, Hubei, China.
Shuaizhou XiongSchool of Economics & Management, Wuhan University, Hubei, China.
Xiaoling ZhangDepartment of Public and International Affairs, City University of Hong Kong, Kowloon, Hong Kong.
Shuzhou LiuSchool of Mathematics and Physics, China University of Geosciences, Hubei, China.
Lin GuRIKEN Center for Advanced Intelligence Project (AIP), Tokyo, Japan.
Yuqi ZhuSchool of Economics & Management, Wuhan University, Hubei, China.
Dongjin XiangSchool of Mathematics and Physics, China University of Geosciences, Hubei, China.
Martin SkitmoreBond University, Brisbane, Queensland, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The social contact rate has influenced the transmission of COVID-19, with more social contact resulting in more contagion cases. We chose 18 countries with the most confirmed cases in the first 200 days after the Wuhan lockdown. This was the first study using the dynamic social contact rate to simulate the epidemic under diverse restriction policies over 500 days since the COVID-19 outbreak. The developed General Dynamic Model suggested that the probability of contagion ranged from 12.52% to 39.39% in the epidemic. The geometric mean of the social contact rates differed from 18.21% to 96.00% between countries. The restriction policies in developed economies were 3.5 times more efficient than in developing economies. We compare the effectiveness of different policies for disease prevention and discuss the influence of policy adjustment frequency for each country. Maintaining the tightest restriction or alternate tightening and loosening restrictions was recommended, with each having an average 72.45% and 79.78% reduction in maximum active cases, respectively.

Indexed as

COVID-19Delayed-rejection adaptive metropolis methodDynamic social contact rateEpidemic controlGeneral dynamic modelRestriction policy

Identifiers

PMID36945346
PMCPMC10017169

What OpenQuestion holds

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Registered trials

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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.