Evidence map›Paper›PMID 33520611›Full record

ArticleSustainable cities and society2021

Exploring geographical distribution of transportation research themes related to COVID-19 using text network approach.

Boniphace Kutela, Norris Novat, Neema Langa

Open access · greenAbstract read
In one paragraph

Article in Sustainable cities and society, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
5.9field-weighted citation impact, top 3% 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

18 citing papers in PubMed, 71 citations in OpenAlex.

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  6. Insights into the long-term effects of COVID-19 responses on transportation facilities.Transportation research. Part D, Transport and environment · 2022
    Article
  7. Wishful thinking? Addressing the long-term implications of COVID-19 for transport in Nigeria.Transportation research. Part D, Transport and environment · 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

3 authors at 2 institutions in 2 countries.

Boniphace KutelaRoadway Safety Program, Texas A&M Transportation Institute, 1111 RELLIS Pkwy, Bryan, TX 77807, United States.
Norris NovatDepartment of Civil Engineering, Ardhi University, P.O. Box 35176, Dar es Salaam Tanzania.
Neema LangaDepartment of Sociology, University of Nevada, Las Vegas, 4505 S Maryland Pkwy, Las Vegas, NV 89154, United States.
Ardhi University · TZUniversity of Nevada, Las Vegas · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 outbreak has extremely impacted the globe due to travel restrictions and lockdowns. Geographically, COVID-19 has shown disproportional impacts; however, the research themes' distribution is yet to be explored. Thus, this study explored the geographical distribution of the research themes that relate to COVID-19 and the transportation sector. The study applied a text network approach on the bibliometric data of over 400 articles published between December 2019 and December 2020. It was found that the researches and the associated themes were geographically distributed based on the events that took place in the respective countries. Most of the articles were published by the authors from four countries, the USA, China, Japan, and the UK. The text network results revealed that the USA-based studies mainly focused on international travelers, monitoring, travel impacts of COVID-19, and social-distancing measures. The Japanese-based studies focused on the princess diamond cruise ship incident. On the other hand, Chinese authors published articles related to travel to Wuhan and China, passenger health, and public transportation. The UK-based studies had diverse topics of interest. Lastly, the remaining 62 countries' studies focused on returning travelers from China, public transportation, and the global spread of COVID-19. The findings are crucial to the transportation sector's researchers for various applications.

Indexed as

BibliometricCOVID-19Machine learningText networksTransportation

Identifiers

PMID33520611
PMCPMC7825958
OpenAlexW3124652931

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.