Evidence map›Paper›PMID 33542248›Full record

ArticleScientific reports2021

Impact of domestic travel restrictions on transmission of COVID-19 infection using public transportation network approach.

Yayoi Murano, Ryo Ueno, Shoi Shi, Takayuki Kawashima, Yuta Tanoue, Shiori Tanaka, Shuhei Nomura, Hiromichi Shoji, Toshiaki Shimizu, Huy Nguyen and 3 more

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

  1. How Will AI Shape the Future of Pandemic Response? Early Clues From Data Analytics.Risk analysis : an official publication of the Society for Risk Analysis · 2025
    Review
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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.

Yayoi MuranoDivision of Biostatistics and Bioinformatics, Graduate School of Public Health, St. Luke's International University, OMURA Susumu and Mieko Memorial, St. Luke's Center for Clinical Academia, 5th Floor 3-6-2 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.
Ryo UenoThe Australian and New Zealand Intensive Care Research Centre, 553 St Kilda Road, Melbourne, VIC, 3004, Australia.
Shoi ShiGraduate School of Medicine, The University of Tokyo, 7-3-1 Hongo Bunkyo-ku, Tokyo, Japan.
Takayuki KawashimaDepartment of Mathematical and Computing Science, Tokyo Institute of Technology, 2-12-1 Ookayama Meguro-ku, Tokyo, Japan.
Yuta TanoueInstitute for Business and Finance, Waseda University, 1-6-1 Nishi-Waseda, Shinjuku-ku, Tokyo, Japan.
Shiori TanakaEpidemiology and Prevention Group, Center for Public Health Sciences, National Cancer Center, 5-1-1 Tsukiji, Chuo-ku, Tokyo, Japan.
Shuhei NomuraGraduate School of Medicine, The University of Tokyo, 7-3-1 Hongo Bunkyo-ku, Tokyo, Japan.
Hiromichi ShojiDepartment of Paediatrics and Adolescents, Juntendo University, 2-1-1 Hongo Bunkyo-ku, Tokyo, Japan.
Toshiaki ShimizuDepartment of Paediatrics and Adolescents, Juntendo University, 2-1-1 Hongo Bunkyo-ku, Tokyo, Japan.
Huy NguyenDivision of Biostatistics and Bioinformatics, Graduate School of Public Health, St. Luke's International University, OMURA Susumu and Mieko Memorial, St. Luke's Center for Clinical Academia, 5th Floor 3-6-2 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.
Hiroaki MiyataDepartment of Health Policy and Management, School of Medicine, Keio University, Endo, Fujisawa-city, Kanagawa, 4411, Japan.
Stuart GilmourDivision of Biostatistics and Bioinformatics, Graduate School of Public Health, St. Luke's International University, OMURA Susumu and Mieko Memorial, St. Luke's Center for Clinical Academia, 5th Floor 3-6-2 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.
Daisuke YoneokaDivision of Biostatistics and Bioinformatics, Graduate School of Public Health, St. Luke's International University, OMURA Susumu and Mieko Memorial, St. Luke's Center for Clinical Academia, 5th Floor 3-6-2 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan. daisuke.yoneoka@slcn.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The international spread of COVID-19 infection has attracted global attention, but the impact of local or domestic travel restriction on public transportation network remains unclear. Passenger volume data for the domestic public transportation network in Japan and the time at which the first confirmed COVID-19 case was observed in each prefecture were extracted from public data sources. A survival approach in which a hazard was modeled as a function of the closeness centrality on the network was utilized to estimate the risk of importation of COVID-19 in each prefecture. A total of 46 prefectures with imported cases were identified. Hypothetical scenario analyses indicated that both strategies of locking down the metropolitan areas and restricting domestic airline travel would be equally effective in reducing the risk of importation of COVID-19. While caution is necessary that the data were limited to June 2020 when the pandemic was in its initial stage and that no other virus spreading routes have been considered, domestic travel restrictions were effective to prevent the spread of COVID-19 on public transportation network in Japan. Instead of lockdown that might seriously damage the economy, milder travel restrictions could have the similar impact on controlling the domestic transmission of COVID-19.

Indexed as

COVID-19HumansJapanPandemicsTransportationTravel

Identifiers

PMID33542248
PMCPMC7862278

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.