Modeling the effects of the governmental responses to COVID-19 on transit demand: The case of Athens, Greece

Marios Giouroukelis; Stella Papagianni; Nellie Tzivellou; Eleni I Vlahogianni; John C Golias

doi:10.1016/j.cstp.2022.03.023

Modeling the effects of the governmental responses to COVID-19 on transit demand: The case of Athens, Greece

Case Stud Transp Policy. 2022 Jun;10(2):1069-1077. doi: 10.1016/j.cstp.2022.03.023. Epub 2022 Mar 30.

Authors

Marios Giouroukelis¹, Stella Papagianni², Nellie Tzivellou², Eleni I Vlahogianni¹, John C Golias¹

Affiliations

¹ Department of Transportation Planning and Engineering, School of Civil Engineering, National Technical University of Athens, 5 Iroon Polytechniou str, Athens 15 773, Greece.
² Transport for Athens - OASA S.A., 15, Metsovou str, Athens 106 82, Greece.

Abstract

Short-term demand forecasting is essential for the public transit system, allowing for effective operations planning. This is especially relevant in the highly uncertain environment created by the SARS‑CoV‑2 pandemic. In this paper, we attempt to develop accurate prediction models of transit ridership in Athens, Greece, using Autoregressive Fractional Integrated time series models enhanced with SARS‑CoV‑2-related exogenous variables. The selected exogenous variables are, from the one hand, the ratio of weekly SARS‑CoV‑2 infections over the infections 3 weeks before (capturing the dynamics of the pandemic, as a proxy for fear of transmitting the disease while commuting), and from the other hand, an index of the stringency of the government's SARS‑CoV‑2-related measures and regulations. The developed ARFIMAX models have been fitted separately on bus and metro ridership data and wield comparable and statistically significant results. In both models, the exogenous variables prove to be statistically significant and their values are intuitive, suggesting a linear interrelation between them and transit ridership.

Keywords: ARFIMAX; COVID-19; Forecasting; Fractional integration; Transit demand.