Evidence map›Paper›PMID 35664727›Full record

ArticleTransport policy2022

Socio-economic disparities in activity-travel behavior adaptation during the COVID-19 pandemic in North Carolina.

Jueyu Wang, Nikhil Kaza, Noreen C McDonald, Kshitiz Khanal

Abstract read
In one paragraph

Article in Transport policy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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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

4 authors.

Jueyu WangDepartment of City and Regional Planning, University of North Carolina, Chapel Hill, New East Building, CB3140, Chapel Hill, NC, 27599, USA.
Nikhil KazaDepartment of City and Regional Planning, University of North Carolina, Chapel Hill, New East Building, CB3140, Chapel Hill, NC, 27599, USA.
Noreen C McDonaldDepartment of City and Regional Planning, University of North Carolina, Chapel Hill, New East Building, CB3140, Chapel Hill, NC, 27599, USA.
Kshitiz KhanalDepartment of City and Regional Planning, University of North Carolina, Chapel Hill, New East Building, CB3140, Chapel Hill, NC, 27599, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic significantly affected human mobility. This study examines the changes in people's activity-travel behavior over 23 months (from Jan 2020 to Nov 2021) and how these changes are associated with the socio-economic status (SES) at the block group level in North Carolina. We identified 5 pandemic stages with different restriction regimes: the pre-pandemic, lockdown, reopening stage, restriction, and complete opening stage. Using the block-group mobility data from SafeGraph, we quantify visits to 8 types of destinations during the 5 stages. We construct regression models with interaction terms between SES and stages and find that visit patterns during the pandemic vary for different types of destinations and SES areas. Specifically, we show that visits to retail stores have a slight decrease for low and medium SES areas, and visits to retail stores and restaurants and bars bounced back immediately after the lockdown for all SES areas. The results suggest that people in low SES areas continued traveling during the pandemic. Transportation planners and policymakers should carefully design the transportation system to satisfy travel needs of those residents. Furthermore, the results also highlight the importance of designing mitigation policies that recognize the immediate recovery of visits to retail locations, restaurants, and bars.

Indexed as

COVID-19EquityMobile device dataMobilityTravel behavior

Identifiers

PMID35664727
PMCPMC9140319

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.