Evidence map›Paper›PMID 36530669›Full record

ArticleFrontiers in public health2022

Optimizing national border reopening policies in the COVID-19 pandemic: A modeling study.

Jiaoling Huang, Ying Qian, Wuzhi Shen, Yong Chen, Laijun Zhao, Siqi Cao, Eliot Rich, John Pastor Ansah, Fan Wu

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in public health, 2022. 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
1.0field-weighted citation impact, top 19% of its field
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, 3 citations in OpenAlex.

  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

9 authors at 7 institutions in 4 countries.

Jiaoling HuangSchool of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Ying QianBusiness School, University of Shanghai for Science and Technology, Shanghai, China.
Wuzhi ShenFaculty of Social Sciences, University of Bergen, Bergen, Norway.
Yong ChenDepartment of Profession Management, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China.
Laijun ZhaoBusiness School, University of Shanghai for Science and Technology, Shanghai, China.
Siqi CaoBusiness School, University of Shanghai for Science and Technology, Shanghai, China.
Eliot RichSchool of Business, University at Albany, State University of New York, New York, NY, United States.
John Pastor AnsahCase Western Reserve University, Center for Community Health Integration, Duke-NUS Medical School, Singapore, Singapore.
Fan WuShanghai Institute of Infectious Disease and Biosecurity, School of Public Health, Fudan University, Shanghai, China.
University of Shanghai for Science and Technology · CNDuke-NUS Medical School · SGFudan University · CNShanghai Jiao Tong University · CNShanghai Municipal Center For Disease Control Prevention · CNUniversity at Albany, State University of New York · USUniversity of Bergen · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: After emergence of the COVID-19 pandemic and subsequent restrictions, countries worldwide have sought to reopen as quickly as possible. However, reopening involves the risk of epidemic rebound. In this study, we investigated the effective policy combination to ensure safe reopen. Methods: On the basis of the classical SEIR epidemic model, we constructed a COVID-19 system dynamics model, incorporating vaccination, border screening, and fever clinic unit monitoring policies. The case of China was used to validate the model and then to test policy combinations for safe reopening. Findings: Vaccination was found to be crucial for safe reopening. When the vaccination rate reached 60%, the daily number of newly confirmed COVID-19 cases began to drop significantly and stabilized around 1,400 [1/1,000,000]. The border screening policy alone only delayed epidemic spread for 8 days but did not reduce the number of infections. Fever clinic unit monitoring alone could reduce the peak of new confirmed cases by 44% when the case identification rate rose from 20 to 80%. When combining polices, once the vaccination rate reached 70%, daily new confirmed cases stabilized at 90 [0.64/1,000,000] with an 80% case identification rate at fever clinic units and border screening. For new variants, newly confirmed cases did not stabilize until the vaccination rate reached 90%. Conclusion: High vaccination rate is the base for reopening. Vaccination passport is less effective compared with a strong primary care monitoring system for early detection and isolation of the infected cases.

Indexed as

COVID-19ChinaHumansPandemicsPolicyborder reopeningborder screeningfever clinic unit monitoringSEIR modelvaccination

Identifiers

PMID36530669
PMCPMC9749815
OpenAlexW4310477424

What OpenQuestion 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 OpenQuestion graph.