Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Jul:24:46-56.
doi: 10.1016/j.tbs.2021.02.002. Epub 2021 Mar 2.

Modelling work- and non-work-based trip patterns during transition to lockdown period of COVID-19 pandemic in India

Affiliations

Modelling work- and non-work-based trip patterns during transition to lockdown period of COVID-19 pandemic in India

Digvijay S Pawar et al. Travel Behav Soc. 2021 Jul.

Abstract

COVID-19 pandemic has significantly affected the transportation sector across the world. Implementation of lockdown (that includes restricted travel activities) is a prevention strategy executed by various governments to minimize the spread of COVID-19. India went into complete lockdown from 25th March 2020; however, change in commuter's travel behavior was observed from the third week of March (termed as transition to lockdown) due to pandemic fear. In total 1945 participants participated in the travel behaviour survey and their responses with respect to work-based and non-work-based trips during transition period were analysed to understand their adaptation towards COVID-19. The study also attempted to quantify the effects of influencing factors which can explain change in the commuters' travel behaviour. The findings revealed that one-year increment in traveller's age had 2% reduced probability of no travel during transition than pre-transition. For non-work-related travel, chances of lower travel frequency were significantly greater during the transition period as compared to pre-transition. Compared to the non-essential trips, the chances of reduced travel frequency for the essential trips were found to be lower by 92%. By examining these behavioural changes, the present study aims to assist the policymakers in understanding the dynamics of fluctuating travel demand with respect to trip purpose during pandemic situations like COVID-19.

Keywords: COVID-19; Mobility; Shopping trips; Travel behavior; Trip purpose; Work-based trips.

PubMed Disclaimer

Figures

Fig. 1
Fig. 1
Geographic spread of collected data.
Fig. 2
Fig. 2
Travel frequencies for non-work-based trips before and during the transition to lockdown period.
Fig. 3
Fig. 3
Effect of traveller’s age on work-related travel frequency (Note: The gray band indicates the 95% confidence intervals around the estimated probabilities).
Fig. 4
Fig. 4
Effect of traveller’s income on work-related travel frequency (Note: Error bars indicate 95% confidence intervals around the estimated probabilities).
Fig. 5
Fig. 5
Effect of working days on work-related travel frequency (Note: Error bars indicate 95% confidence intervals around the estimated probabilities).
Fig. 6
Fig. 6
Effect of type of trip on frequency of non-work-based trips (Note: Error bars indicate 95% confidence intervals around the estimated probabilities).
Fig. 7
Fig. 7
Effect of income on frequency of non-work-based trips (Note: Error bars indicate 95% confidence intervals around the estimated probabilities).
Fig. 8
Fig. 8
Effect of safety perceptions on frequency of non-work-based trips (Note: Error bars indicate 95% confidence intervals around the estimated probabilities).

Similar articles

Cited by

References

    1. Arentze T.A., Ettema D., Timmermans H.J. Estimating a model of dynamic activity generation based on one-day observations: method and results. Transp. Res. Part B: Methodol. 2011;45(2):447–460.
    1. Badger, E., 2020. Transit has been Battered by Coronavirus. What’s Ahead may be Worse. The New York Times, 9 April 2020, Available at: https://www.nytimes.com/2020/04/09/upshot/transitbattered-by-coronavirus... (accessed 16 May 2020).
    1. Bansal P., Kockelman K.M., Schievelbein W., Schauer-West S. Indian vehicle ownership and travel behavior: a case study of Bengaluru, Delhi and Kolkata. Res. Transp. Econ. 2018;71:2–8.
    1. Barr M., Raphael B., Taylor M., Stevens G., Jorm L., Giffin M., Lujic S. Pandemic influenza in Australia: using telephone surveys to measure perceptions of threat and willingness to comply. BMC Infect. Dis. 2008;8(1):117. - PMC - PubMed
    1. Basu D., Stefan K.J., Hunt J.D., McCoy M. Modeling choice behavior of non-mandatory tour locations in California – an experience. Travel Behav. Soc. 2017;12:122–129.

LinkOut - more resources