Journal of Transport and Supply Chain Management (Jun 2022)

Revealed and future travel impacts of COVID-19 in sub-Saharan Africa: Results of big data analysis and a Delphi panel survey

  • Roger Behrens,
  • Alexandra Newlands

DOI
https://doi.org/10.4102/jtscm.v16i0.758
Journal volume & issue
Vol. 16, no. 0
pp. e1 – e12

Abstract

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Background: After coronavirus disease 2019 (COVID-19) was declared a pandemic, movement restrictions were implemented across sub-Saharan Africa. There has been much speculation on what the long-term impacts on urban transport might be. Objectives: The aim of this paper is to identify the revealed and future travel impacts of the pandemic. Method: To pursue this aim, evidence was compiled from two sources: secondary big data; and a (n = 15) two-wave Delphi panel survey of experts in the region. Results: It is predicted that longer-term impacts will take the form of: reduced travel by, and accessibility for, low-income households residing in peripheral locations because of decreased welfare; reduced transport service availability; operator reduction (particularly amongst unsubsidised formal operators); increased remote activity participation for a minority of better resourced households with white-collar workers; and disrupted trip distributions as the mix of city-centre land use changes in response to business attrition in economic recession rather than to disrupted bid rents. Conclusion: The major impact of the pandemic is likely to be on welfare, rather than on trip substitution. There is a need, therefore, to focus policy on the mitigation of these impacts and, more particularly, on ways of measuring changes in transport disadvantage and exclusion so that reliable data are available to inform mitigation strategies. The mitigation strategies considered should include investment in affordable ‘digital connectivity’ as a means of complementing accessibility from physical proximity and mobility. The pandemic also highlights the need to develop more robust transport planning practices to deal with uncertainty.

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