Evidence map›Paper›PMID 34653737›Full record

ArticlePublic health2021

Investigating the relationship between reopening the economy and implementing control measures during the COVID-19 pandemic.

Jian Zu, Mingwang Shen, Christopher K Fairley, Miaolei Li, Guoqiang Li, Libin Rong, Yanni Xiao, Guihua Zhuang, Lei Zhang, Yan Li

Abstract read
In one paragraph

Article in Public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
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  4. Critical timing and extent of public health interventions to control outbreaks dominated by SARS-CoV-2 variants in Australia: a mathematical modelling study.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2022
    Article
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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

10 authors.

Jian ZuSchool of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Mingwang ShenChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China.
Christopher K FairleyChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China; Melbourne Sexual Health Centre, Alfred Health, Melbourne, Australia; Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia.
Miaolei LiSchool of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Guoqiang LiChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China.
Libin RongDepartment of Mathematics, University of Florida, Gainesville, FL, USA.
Yanni XiaoSchool of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Guihua ZhuangChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China.
Lei ZhangChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China; Melbourne Sexual Health Centre, Alfred Health, Melbourne, Australia; Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia; Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China. Electronic address: lei.zhang1@monash.edu.
Yan LiDepartment of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Obstetrics, Gynaecology, and Reproductive Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA. Electronic address: yan.li1@mountsinai.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe COVID-19 pandemic has resulted in an enormous burden on population health and the economy around the world. Although most cities in the United States have reopened their economies from previous lockdowns, it was not clear how the magnitude of different control measures-such as face mask use and social distancing-may affect the timing of reopening the economy for a local region. This study aimed to investigate the relationship between reopening dates and control measures and identify the conditions under which a city can be reopened safely. STUDY

designThis was a mathematical modeling study.

methodsWe developed a dynamic compartment model to capture the transmission dynamics of COVID-19 in New York City. We estimated model parameters from local COVID-19 data. We conducted three sets of policy simulations to investigate how different reopening dates and magnitudes of control measures would affect the COVID-19 epidemic.

resultsThe model estimated that maintaining social contact at 80% of the prepandemic level and a 50% face mask usage would prevent a major surge of COVID-19 after reopening. If social distancing were completely relaxed after reopening, face mask usage would need to be maintained at nearly 80% to prevent a major surge.

conclusionsAdherence to social distancing and increased face mask usage are keys to prevent a major surge after a city reopens its economy. The findings from our study can help policymakers identify the conditions under which a city can be reopened safely.

Indexed as

COVID-19PandemicsCommunicable Disease ControlHumansMasksSARS-CoV-2United StatesCOVID-19Face maskSecond outbreakSocial distancingTransmission dynamics

Identifiers

PMID34653737
PMCPMC8433041

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.