Statistical Analysis of Cycling Patterns in Great Britain before and After the COVID-19 Pandemic
Authors
Department of Computer Engineering, Federal University of Technology, Owerri (Nigeria)
Article Information
DOI: 10.51584/IJRIAS.2026.11100040
Subject Category: Social science
Volume/Issue: 11/10 | Page No: 578-588
Publication Timeline
Submitted: 2026-10-17
Accepted: 2026-10-22
Published: 2026-10-31
Abstract
Cycling rose sharply across Britain in 2020. Five years on, it is unclear how much of that increase has held. This study uses 5.27 million hourly manual counts from 43,401 sites (2000–2025) to measure persistence, defines a persistence ratio, and examines changes in where and when people cycle. A flow-weighted, chain-linked index shows cycling at counted sites 50% above its 2019 level in 2020 and 11% above in 2025, a persistence ratio of 0.21. London retained three-quarters of its surge (+39%); the rest of Great Britain retained an eighth (+6%), and several regions ended below 2019. A site fixed-effects index, which weights each site equally, put the typical site 6% below 2019 by 2025: growth has become concentrated in London, whose busy routes dominate a flow-weighted measure. The share of cycling in the two commuting peaks fell 4.2 percentage points between 2019 and 2025 (SE 0.24), with the 07:00 hour hit hardest, while midday cycling grew. Contrary to expectation, the day-of-week pattern did not change once site composition was controlled for. The pandemic left a lasting mark on London’s cycling and on the timing of trips, but outside the capital, cycling volumes have largely returned to their earlier trajectory.
Keywords
cycling; active travel; hybrid working; traffic counts; persistence; Great Britain
Downloads
References
1. Adame Valenzuela, E., Barban, P., Beitel, D., Miranda-Moreno, L. F., & Nguyen, V.-T.-V. (2024). Analyzing the behavior and growth of cycling in four North American cities before, during, and after the COVID-19 pandemic. Transportation Research Record, 2678(12), 420–433. https://doi.org/10.1177/03611981231157396 [Google Scholar] [Crossref]
2. Aldred, R., & Goodman, A. (2021). The impact of low traffic neighbourhoods on active travel, car use, and perceptions of local environment during the COVID-19 pandemic. Findings. https://doi.org/10.32866/001c.21390 [Google Scholar] [Crossref]
3. Aldred, R., Verlinghieri, E., Sharkey, M., Itova, I., & Goodman, A. (2021). Equity in new active travel infrastructure: A spatial analysis of London’s new low traffic neighbourhoods. Journal of Transport Geography, 96, Article 103194. https://doi.org/10.1016/j.jtrangeo.2021.103194 [Google Scholar] [Crossref]
4. Alimo, P. K., Franceschini, M., Manout, O., & Bouzouina, L. (2026). Impact of cycle lanes and public bike parking on bicycle commuting: How to achieve France’s cycling mode share target? Transport Policy, 184, Article 104165. https://doi.org/10.1016/j.tranpol.2026.104165 [Google Scholar] [Crossref]
5. Balbontin, C., Hensher, D. A., & Beck, M. J. (2024). Relationship between commuting and non-commuting travel activity under the growing incidence of working from home and people’s attitudes towards COVID-19. Transportation, 51(6), 2225–2251. https://doi.org/10.1007/s11116-023-10403-2 [Google Scholar] [Crossref]
6. Balbontin, C., Hensher, D. A., Beck, M. J., Giesen, R., Basnak, P., Vallejo-Borda, J. A., & Venter, C. (2021). Impact of COVID-19 on the number of days working from home and commuting travel: A cross-cultural comparison between Australia, South America and South Africa. Journal of Transport Geography, 96, Article 103188. https://doi.org/10.1016/j.jtrangeo.2021.103188 [Google Scholar] [Crossref]
7. Buehler, R., & Pucher, J. (2021). COVID-19 impacts on cycling, 2019–2020. Transport Reviews, 41(4), 393–400. https://doi.org/10.1080/01441647.2021.1914900 [Google Scholar] [Crossref]
8. Buehler, R., & Pucher, J. (2022). Cycling through the COVID-19 pandemic to a more sustainable transport future: Evidence from case studies of 14 large bicycle-friendly cities in Europe and North America. Sustainability, 14(12), Article 7293. https://doi.org/10.3390/su14127293 [Google Scholar] [Crossref]
9. Caldarola, B., & Sorrell, S. (2022). Do teleworkers travel less? Evidence from the English National Travel Survey. Transportation Research Part A: Policy and Practice, 159, 282–303. https://doi.org/10.1016/j.tra.2022.03.026 [Google Scholar] [Crossref]
10. Curtis, C., Olaru, D., Smith, B., Reed, T. W., Knight, C., & Biermann, S. (2025). Sustainable urban mobility transitions through working from home (WFH). Travel Behaviour and Society, 39, Article 100953. https://doi.org/10.1016/j.tbs.2024.100953 [Google Scholar] [Crossref]
11. Department for Transport. (2022). Minor road traffic estimates review: Technical report. https://www.gov.uk/government/statistics/road-traffic-estimates-in-great-britain-2021/minor-road-traffic-estimates-review-technical-report [Google Scholar] [Crossref]
12. Department for Transport. (2026a). Road traffic estimates in Great Britain, 2025: Traffic in Great Britain by vehicle type. https://www.gov.uk/government/statistics/road-traffic-estimates-in-great-britain-2025/road-traffic-estimates-in-great-britain-2025-traffic-in-great-britain-by-vehicle-type [Google Scholar] [Crossref]
13. Department for Transport. (2026b). Road traffic statistics: Raw counts, 2000–2025 [Data set]. Retrieved October 18, 2026, from https://roadtraffic.dft.gov.uk/downloads [Google Scholar] [Crossref]
14. Dudley, G., Banister, D., & Schwanen, T. (2022). Low traffic neighbourhoods and the paradox of UK government control of the active travel agenda. The Political Quarterly, 93(4), 585–593. https://doi.org/10.1111/1467-923X.13198 [Google Scholar] [Crossref]
15. Fuller, G., McGuinness, K., Waitt, G., Buchanan, I., & Lea, T. (2021). The reactivated bike: Self-reported cycling activity during the 2020 COVID-19 pandemic in Australia. Transportation Research Interdisciplinary Perspectives, 10, Article 100377. https://doi.org/10.1016/j.trip.2021.100377 [Google Scholar] [Crossref]
16. Furlong, J., Fevyer, D., Armstrong, B., Edwards, P., Aldred, R., & Goodman, A. (2025). Low traffic neighbourhoods in London reduce road traffic injuries: A controlled before-and-after analysis (2012–2024). Injury Prevention. Advance online publication. https://doi.org/10.1136/ip-2024-045571 [Google Scholar] [Crossref]
17. Goodman, A., Furlong, J., Laverty, A. A., Thomas, A., & Aldred, R. (2021). Impacts of 2020 low traffic neighbourhoods in London on road traffic injuries. Findings. https://doi.org/10.32866/001c.25633 [Google Scholar] [Crossref]
18. Greaves, S., Beck, M., Cobbold, A., Standen, C., Rissel, C., & Crane, M. (2024). Working from home, active travel, health and wellbeing: Legacies of a pandemic. Travel Behaviour and Society, 34, Article 100707. https://doi.org/10.1016/j.tbs.2023.100707 [Google Scholar] [Crossref]
19. Hensher, D. A., Balbontin, C., Beck, M. J., & Wei, E. (2022). The impact of working from home on modal commuting choice response during COVID-19: Implications for two metropolitan areas in Australia. Transportation Research Part A: Policy and Practice, 155, 179–201. https://doi.org/10.1016/j.tra.2021.11.011 [Google Scholar] [Crossref]
20. Heydari, S., Konstantinoudis, G., & Behsoodi, A. W. (2021). Effect of the COVID-19 pandemic on bike-sharing demand and hire time: Evidence from Santander Cycles in London. PLOS ONE, 16(12), Article e0260969. https://doi.org/10.1371/journal.pone.0260969 [Google Scholar] [Crossref]
21. Huang, Z., Loo, B. P. Y., & Axhausen, K. W. (2023). Travel behaviour changes under work-from-home (WFH) arrangements during COVID-19. Travel Behaviour and Society, 30, 202–211. https://doi.org/10.1016/j.tbs.2022.09.006 [Google Scholar] [Crossref]
22. Jia, J., Liu, C., Wang, X., Zhang, H., & Xiao, Y. (2023). Understanding bike-sharing mobility patterns in response to the COVID-19 pandemic. Cities, 142, Article 104554. https://doi.org/10.1016/j.cities.2023.104554 [Google Scholar] [Crossref]
23. Kim, M., & Cho, G.-H. (2022). Examining the causal relationship between bike-share and public transit in response to the COVID-19 pandemic. Cities, 131, Article 104024. https://doi.org/10.1016/j.cities.2022.104024 [Google Scholar] [Crossref]
24. Kraus, S., & Koch, N. (2021). Provisional COVID-19 infrastructure induces large, rapid increases in cycling. Proceedings of the National Academy of Sciences, 118(15), Article e2024399118. https://doi.org/10.1073/pnas.2024399118 [Google Scholar] [Crossref]
25. Li, Z., Zhu, P., Guo, Y., & Chow, J. (2025). Pandemic-era behavioral changes and post-pandemic persistence in the high-density urban context of Hong Kong. Cities, 162, Article 105940. https://doi.org/10.1016/j.cities.2025.105940 [Google Scholar] [Crossref]
26. Möllers, A., Specht, S., & Wessel, J. (2022). The impact of the Covid-19 pandemic and government intervention on active mobility. Transportation Research Part A: Policy and Practice, 165, 356–375. https://doi.org/10.1016/j.tra.2022.09.007 [Google Scholar] [Crossref]
27. Moran, M. E. (2022). Treating COVID with bike lanes: Design, spatial, and network analysis of “pop-up” bike lanes in Paris. Findings. https://doi.org/10.32866/001c.33765 [Google Scholar] [Crossref]
28. Ortar, N., Lejoux, P., & Ovtracht, N. (2025). From temporary bike lanes to a cycling oriented mobility paradigm: The case of Lyon during and after the pandemic of COVID-19. Journal of Urban Mobility, 7, Article 100103. https://doi.org/10.1016/j.urbmob.2025.100103 [Google Scholar] [Crossref]
29. Pritchett, R., Bartington, S., & Thomas, G. N. (2024). Exploring expectations and lived experiences of low traffic neighbourhoods in Birmingham, UK. Travel Behaviour and Society, 36, Article 100800. https://doi.org/10.1016/j.tbs.2024.100800 [Google Scholar] [Crossref]
30. Rérat, P., Haldimann, L., & Widmer, H. (2022). Cycling in the era of Covid-19: The effects of the pandemic and pop-up cycle lanes on cycling practices. Transportation Research Interdisciplinary Perspectives, 15, Article 100677. https://doi.org/10.1016/j.trip.2022.100677 [Google Scholar] [Crossref]
31. Richards, A., Convery, S., O’Mahony, M., & Caulfield, B. (2024). Pre and post Covid preferences for working from home. Travel Behaviour and Society, 34, Article 100679. https://doi.org/10.1016/j.tbs.2023.100679 [Google Scholar] [Crossref]
32. Rotaris, L., Intini, M., & Gardelli, A. (2022). Impacts of the COVID-19 pandemic on bike-sharing: A literature review. Sustainability, 14(21), Article 13741. https://doi.org/10.3390/su142113741 [Google Scholar] [Crossref]
33. Shi, X., Zhao, J., He, J., & Xu, H. (2023). Exploring year-to-year spatiotemporal changes in cycling patterns for bike-sharing system in the pre-, during and post-pandemic periods. Sustainable Cities and Society, 98, Article 104814. https://doi.org/10.1016/j.scs.2023.104814 [Google Scholar] [Crossref]
34. Smith, M. L., & Fu, X. (2025). When bike lanes are not enough: The role of connected low-stress cycling infrastructure on cycle commuting in urban Aotearoa New Zealand. Cities, 156, Article 105526. https://doi.org/10.1016/j.cities.2024.105526 [Google Scholar] [Crossref]
35. Young, M., MacGregor, G., & Tanguay, G. A. (2024). Analyzing the impact of Montreal’s Réseau Express Vélo (REV) on surrounding bike lanes’ ridership and the COVID-19 cycling recovery. Sustainability, 16(14), Article 5992. https://doi.org/10.3390/su16145992 [Google Scholar] [Crossref]
Metrics
Views & Downloads
Similar Articles
- The Impact of Ownership Structure on Dividend Payout Policy of Listed Plantation Companies in Sri Lanka
- Urban Sustainability in North-East India: A Study through the lens of NER-SDG index
- Performance Assessment of Predictive Forecasting Techniques for Enhancing Hospital Supply Chain Efficiency in Healthcare Logistics
- The Fractured Self in Julian Barnes' Postmodern Fiction: Identity Crisis and Deflation in Metroland and the Sense of an Ending
- Impact of Flood on the Employment, Labour Productivity and Migration of Agricultural Labour in North Bihar