The impact of COVID-19 vaccination rate on traffic recovery.

Suyanpeng Zhang, Jing Jin, Han Yu, Ying Hong, Neeraj Sood, Sze-Chuan Suen

Abstract read

In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Suyanpeng ZhangDaniel J. Epstein Department of Industrial and Systems Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA. suyanpeng.zhang@northwestern.edu.

Jing JinDaniel J. Epstein Department of Industrial and Systems Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA.

Han YuDaniel J. Epstein Department of Industrial and Systems Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA.

Ying HongDepartment of Mathematics, University of California, Los Angeles, Los Angeles, CA, USA.

Neeraj SoodSol Price School of Public Policy, University of Southern California, Los Angeles, CA, USA.

Sze-Chuan SuenDaniel J. Epstein Department of Industrial and Systems Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA.

Funding

Using Road Traffic Data to Identify COVID-19 Priority Testing Locations in Southern CaliforniaR21LM013697 · NLM · UNIVERSITY OF SOUTHERN CALIFORNIA · PI SUEN, SZE-CHUAN · 2021 to 2022

$309k

NIH HHS 5R21LM013697NLM NIH HHS R21 LM013697

6 · The paper itself

Abstract

At the beginning of the COVID-19 pandemic in the US, traffic sharply fell due to social distancing policies in many locations. Correspondingly, many regions observed an increase in traffic volume (traffic recovery) as the pandemic eased in 2022. We examine how vaccination rates influence traffic recovery in Los Angeles County (LAC), controlling for differences in case counts, demographics, and socioeconomic factors across areas with different vaccination rates. We use arterial road sensor data as a proxy for the traffic volume within each ZIP code, alongside their respective demographic and socioeconomic characteristics. We find that a higher vaccination rate is statistically significantly associated with a larger traffic recovery, a finding that remains consistent across all explored models. This implies that an increased vaccination rate could reduce the public's perception of the risks of disease infection, leading to a larger traffic recovery. Moreover, we found that variables including population, income, race, work industry, and commuting preferences were correlated with vaccination rates. This highlights potential inequalities based on race, income, and industry sectors in the COVID-19 vaccination and a return to normal traffic flow.

Indexed as

COVID-19COVID-19 VaccinesVaccinationHumansLos AngelesPandemicsSARS-CoV-2Socioeconomic FactorsTransportationCOVID-19 Vaccines

Identifiers

PMID39333260

DOI10.1038/s41598-024-73448-y

PMCPMC11436653

What OpenQuestion holds

Textmetadata

LicenceCC BY-NC-ND

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.