Evidence map›Paper›PMID 36285319›Full record

ArticleChina CDC weekly2022

Travel-related Importation and Exportation Risks of SARS-CoV-2 Omicron Variant in 367 Prefectures (Cities) - China, 2022.

Yuan Bai, Mingda Xu, Caifen Liu, Mingwang Shen, Lin Wang, Linwei Tian, Suoyi Tan, Lei Zhang, Petter Holme, Xin Lu and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in China CDC weekly, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. 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

13 authors.

Yuan BaiWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.
Mingda XuLaboratory of Data Discovery for Health Limited (D24H), Hong Kong Science Park, Hong Kong Special Administrative Region, China.
Caifen LiuWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.
Mingwang ShenChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an City, Shaanxi Province, China.
Lin WangDepartment of Genetics, University of Cambridge, Cambridge CB2 3EH, UK.
Linwei TianWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.
Suoyi TanCollege of Systems Engineering, National University of Defense Technology, Changsha City, Hunan Province, China.
Lei ZhangChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an City, Shaanxi Province, China.
Petter HolmeDepartment of Computer Science, Aalto University, Espoo, Finland.
Xin LuCollege of Systems Engineering, National University of Defense Technology, Changsha City, Hunan Province, China.
Eric H Y LauWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.
Benjamin J CowlingWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.
Zhanwei DuWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Minimizing the importation and exportation risks of coronavirus disease 2019 (COVID-19) is a primary concern for sustaining the "Dynamic COVID-zero" strategy in China. Risk estimation is essential for cities to conduct before relaxing border control measures. Methods: Informed by the daily number of passengers traveling between 367 prefectures (cities) in China, this study used a stochastic metapopulation model parameterized with COVID-19 epidemic characteristics to estimate the importation and exportation risks. Results: Under the transmission scenario ( Conclusions: Estimating COVID-19 importation and exportation risks is necessary for preparedness, prevention, and control measures of COVID-19 - especially when new variants emerge.

Indexed as

COVID-19Importation and exportation risksOmicron

Identifiers

PMID36285319
PMCPMC9579982

What OpenQuestion holds

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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.