Evidence map›Paper›PMID 37153194›Full record

ArticleTransportation research record2023

Telecommuting and Travel during COVID-19: An Exploratory Analysis across Different Population Geographies in the U.S.A.

Rezwana Rafiq, Michael G McNally, Md Yusuf Sarwar Uddin

Open access · greenAbstract read
In one paragraph

Article in Transportation research record, 2023. 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
2.5field-weighted citation impact, top 11% 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, 11 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

3 authors at 2 institutions in 1 country.

Rezwana RafiqInstitute of Transportation Studies, University of California, Irvine, CA.ORCID https://orcid.org/0000-0002-7177-5415
Michael G McNallyDepartment of Civil & Environmental Engineering, Institute of Transportation Studies, University of California, Irvine, CA.ORCID https://orcid.org/0000-0003-2799-5389
Md Yusuf Sarwar UddinDepartment of Computer Science and Electrical Engineering, University of Missouri-Kansas City, Kansas City, MO.ORCID https://orcid.org/0000-0003-2184-0140
University of California, Irvine · USUniversity of Missouri–Kansas City · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study explores the impact of the COVID-19 pandemic on telecommuting (working from home) and travel during the first year of the pandemic in the U.S.A. (from March 2020 to March 2021), with a particular focus on examining the variation in impact across different U.S. geographies. We divided 50 U.S. states into several clusters based on their geographic and telecommuting characteristics. Using K-means clustering, we identified four clusters comprising 6 small urban states, 8 large urban states, 18 urban-rural mixed states, and 17 rural states. Combining data from multiple sources, we observed that nearly one-third of the U.S. workforce worked from home during the pandemic, which was six times higher than the pre-pandemic period, and that these fractions varied across the clusters. More people worked from home in urban states compared with rural states. As well as telecommuting, we examined several activity travel trends across these clusters: reduction in the number of activity visits; changes in the number of trips and vehicle-miles traveled; and mode usage. Our analysis showed there was a greater reduction in the number of workplace and nonworkplace visits in urban states compared with rural states. The number of trips in all distance categories decreased except for long-distance trips, which increased during the summer and fall of 2020. The changes in overall mode usage frequency were similar across urban and rural states with a large drop in ride-hailing and transit use. This comprehensive study can provide a better understanding of the regional variation in the impact of the pandemic on telecommuting and travel, which can facilitate informed decision-making.

Indexed as

big datacluster analysisCOVID-19 pandemicruraltelecommutingtravelurbanVMTworking from home

Identifiers

PMID37153194
PMCPMC10149499
OpenAlexW4287958451

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.