Evidence map›Paper›PMID 36278241›Full record

ArticleTransport policy2022

Challenges for urban transport policy after the Covid-19 pandemic: Main findings from a survey in 20 European cities.

Panayotis Christidis, Elena Navajas Cawood, Davide Fiorello

Open access · hybridAbstract 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 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
13.5field-weighted citation impact, top 1% 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

9 citing papers in PubMed, 56 citations in OpenAlex.

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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.

Panayotis ChristidisEuropean Commission, Joint Research Centre (JRC), Seville, Spain.
Elena Navajas CawoodEuropean Commission, Joint Research Centre (JRC), Seville, Spain.
Davide FiorelloTRT Transporti e Territorio, Milan, Italy.
Joint Research Center · ESTrasporti e Territorio · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article explores the changes in transport and mobility patterns that were triggered by the Covid-19 pandemic, as well as citizens' potential new expectations arising from this situation regarding public transport policy and urban planning. We conducted an extensive survey in 20 cities across 11 European countries during the second quarter of 2021, with a total of 10000 respondents. The information that we collected covered the change in the frequency of technology-based alternatives to travel -such as teleworking and online shopping-compared to the pre-pandemic period. It also included the change in trip frequency, purpose, mode and destination. Using the survey dataset as input, we applied a classification model that explains the change in mode choice based on the respondent characteristics and preferences. Our findings suggest that the changes in mobility patterns induced by the pandemic are the result of the combination of the degree of mobility restrictions imposed in each city, the adoption of new lifestyle and work patterns, and individual choices that depend on personal risk aversion. We identify three main challenges for urban transport policy: the increasing use of car that can reinforce long-term car dependency, the avoidance of public transport that may lead to financial and operational instability, and the uncertainty as regards the future of innovation in urban transport, especially as regards emerging technologies and business models.

Indexed as

Car dependencyCovid-19PandemicPublic transportTeleworkingUrban mobility

Identifiers

PMID36278241
PMCPMC9576464
OpenAlexW4306665835

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.