Evidence map›Paper›PMID 36466107›Full record

ArticleJournal of transport & health2023

Did the COVID-19 vaccine rollout impact transportation demand? A case study in New York City.

Justin Drummond, Md Sami Hasnine

Abstract read
In one paragraph

Article in Journal of transport & health, 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
–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

1 citing paper in PubMed.

  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

2 authors.

Justin DrummondDepartment of Civil and Environmental Engineering, Howard University, 2300 Sixth Street, NW, Washington, DC, 20059, USA.
Md Sami HasnineDepartment of Civil and Environmental Engineering, Howard University, 2300 Sixth Street, NW #1026, Washington, DC, 20059, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: This study investigates the influence of vaccination along with other pandemic-related factors on driving, transit, and walking in New York City (NYC). The results of this study help inform policymakers of the weight of their decisions in a pandemic setting as well as factors to consider when modeling transportation during a pandemic. Methods: In this study, ARIMAX time series analysis was performed on driving, transit, and walking data from Apple Mobility Trends Reports. The data was segmented into two categories "pre-vaccine" and post-vaccine" for both Manhattan and Brooklyn. The independent variables were primarily COVID-19 statistics (vaccination, case counts, deaths, etc.) along with additional predictors aggregated from Google Community Mobility Reports, Google Trends, Citi Bike, National Oceanic and Atmospheric Administration (NOAA), and the Oxford Covid-19 Government Response Tracker (OxCGRT). Results: Vaccination led to increases in driving, transit, and walking in Brooklyn but was not as statistically significant in Manhattan (the only effect being on walking trips). Despite this, vaccination was not the strongest influencer on transportation. The COVID-19 policy score variable had the highest standardized β in nearly every model, indicating that stricter lockdown policies were the main factor discouraging travel. Furthermore, the lifting of these policies contributed to increases in travel numbers more than vaccination. Conclusions: In the event of future pandemics or health crises, NYC policymakers should be aware that they play a significant role in mitigating infectious diseases. The public is seemingly more responsive to policy than anything else. Similar studies should be conducted in other cities as the public response may vary based on other factors.

Indexed as

COVID-19Transportation modelingUrban mobilityVaccination

Identifiers

PMID36466107
PMCPMC9701644

What OpenQuestion holds

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Registered trials

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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.