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

SUBMITTER: Giouroukelis M

PROVIDER: S-EPMC8964442 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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

Giouroukelis Marios M Papagianni Stella S Tzivellou Nellie N Vlahogianni Eleni I EI Golias John C JC

Case studies on transport policy 20220330 2

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 r ...[more]

PMID: 35371920

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Project description:Objective:Fear of COVID-19 was associated with more severe depressive and anxiety symptoms. This study aimed to explore COVID-19-related fear, depressive and anxiety symptoms, social responsibility, and behavioral responses during the COVID-19 pandemic in Greece. Method:A cross-sectional study was conducted from April 10 to April 13, 2020. Members of the Greek general population completed anonymously an online survey, distributed through the social media. Among the 3,700 adult respondents, 3,029 fulfilled inclusion criteria. The survey included sociodemographic questions, questions exploring potential risk factors for increased fear of COVID-19, questions about the employment of safety and checking behaviors, and questions about compliance with public health guidelines. In addition, four psychometric scales were used, the Fear of COVID-19 Scale (FCV-19S), the Brief Patient Health Questionnaire (PHQ-9) depression scale, the Generalized Anxiety Disorder scale (GAD-7), and Steele's Social Responsibility Motivation scale. Multivariate General Linear Models (GLM) were used to depict significant differences among dependent variables (FCV-19S, PHQ-9, GAD-7) and independent variables (potential risk factors, safety and checking behaviors, compliance with guidelines). The relationship between the FCV-19S total score and influencing factors was quantified by linear regression analysis. Results:Several participants reported high levels of COVID-19-related fear (35.7%) and moderate to severe depressive symptoms (22.8%), while a significant proportion reported moderate to severe anxiety symptoms (77.4%). Women scored altogether significantly higher than men. Respondents under the age of 30 reported less fear and depressive symptoms and showed the least social responsibility. Based on GLM, a significant other's COVID-19 illness, being on psychiatric medication, employment of safety and checking behaviors, and compliance with guidelines were associated with higher COVID-19-related fear. Linear regression analysis revealed that gender, age, depressive, and anxiety symptoms modified levels of COVID-19-related fear. Conclusions:Greater behavioral responses to the pandemic, that is, excessive employment of safety/checking behaviors and greater compliance with guidelines, were shown to amplify fear, potentially due to increased contamination awareness. In addition, female gender, older age, and more severe anxiety symptoms were related with higher COVID-19-related fear. Describing and weighing carefully the psychosocial and behavioral impact of the pandemic will enable the implementation of both supportive and preventive interventions.

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

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

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