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An evaluation of the impact of COVID-19 safety measures in public transit spaces on riders' Worry of virus contraction.

ABSTRACT: The coronavirus pandemic has brought about global change in travel behavior. Transit ridership volumes have dropped to record lows. Concerning environmental, health, and social consequences lie in store if transit networks are not able to regain a substantial portion of pre-pandemic users. Transit providers have implemented several interventions aimed at both slowing the spread of the virus and retaining riders as travel restrictions lift. While the effectiveness of these measures has been evaluated with respect to spread rate reduction, little consideration has been given to their impact on riders' feelings of worry regarding virus contraction. By deploying a photo-simulation approach in a randomized control trial, this study finds that level of compliance with safety measures and the conditions of transit spaces themselves significantly impact riders' levels of worry. Given these findings, a series of recommendations are made regarding compliance practices that are expected to lessen rider worry regarding the risks of COVID-19 infection.

SUBMITTER: Navarrete-Hernandez P

PROVIDER: S-EPMC9682465 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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An evaluation of the impact of COVID-19 safety measures in public transit spaces on riders' Worry of virus contraction.

Navarrete-Hernandez Pablo P Rennert Lindiwe L Balducci Alessandro A

Transport policy 20221123

The coronavirus pandemic has brought about global change in travel behavior. Transit ridership volumes have dropped to record lows. Concerning environmental, health, and social consequences lie in store if transit networks are not able to regain a substantial portion of pre-pandemic users. Transit providers have implemented several interventions aimed at both slowing the spread of the virus and retaining riders as travel restrictions lift. While the effectiveness of these measures has been evalu ...[more]

PMID: 36439031

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Project description:Background During the COVID-19 pandemic, many urban residents stopped riding public transit despite their reliance on it to reach essential services like healthcare. Few studies have examined the implications of public transit reliance on riders’ ability to reach healthcare when transit is disrupted. To understand how shocks to transportation systems impact healthcare access, this study measures the impact of avoiding public transit on the ability of riders to access healthcare and pharmacy services during lockdowns. Methods We deployed a cross-sectional survey of residents of Toronto and Vancouver in May 2020 through Facebook advertisements and community list-serves. Eligibility criteria included riding transit at least weekly prior to the pandemic and subsequent cessation of transit use during the pandemic. We applied multivariable modified Poisson models to identify socio-demographic, transportation, health-related, and neighborhood predictors of experiencing increased difficulty accessing healthcare and getting prescriptions while avoiding public transit. We also predicted which respondents reported deferring medical care until they felt comfortable riding transit again. Results A total of 4367 former transit riders were included (64.2% female, 56.1% Toronto residents). Several factors were associated with deferring medical care including: being non-White (Toronto, APR, 1.14; 95% CI, 1.00-1.29; Vancouver, APR, 1.52; 95% CI, 1.26-1.84), having a physical disability (Toronto, APR, 1.20; 95% CI, 1.00-1.45; Vancouver, APR, 1.42; 95% CI, 1.08-1.87), having no vehicle access (Toronto, APR, 1.74; 95% CI, 1.51-2.00; Vancouver, APR, 2.74; 95% CI, 2.20-3.42), and having low income (Toronto, APR, 1.77; 95% CI, 1.44-2.17; Vancouver, APR, 1.51; 95% CI, 1.06-2.14). Discussion During COVID-19 in two major Canadian cities, former transit riders from marginalized groups were more likely to defer medical care than other former riders. COVID-19 related transit disruptions may have imposed a disproportionate burden on the health access of marginalized individuals. Policymakers should consider prioritizing healthcare access for vulnerable residents during crises.

Project description:Urbanization is an important factor contributing to the global spread of dengue in recent decades, especially in tropical regions. However, the impact of public transportation system on local spread of dengue in urban settings remains poorly understood, due to the difficulty in collecting relevant locality, transportation and disease incidence data with sufficient detail, and in suitably quantifying the combined effect of proximity and passenger flow. We quantify proximity and passenger traffic data relating to 2014-2015 dengue outbreaks in Kaohsiung, Taiwan by introducing a "Risk Associated with Metro Passengers Presence" (RAMPP), which considers the passenger traffic of stations located within a fixed radius, giving more weight to the busier and/or closer stations. In order to analyze the contagion risk associated with nearby presence of one or more Kaohsiung Rapid Transit (KRT) stations, we cluster the Li's (the fourth level administrative subdivision in Taiwan) of Kaohsiung based on their RAMPP value using the K-means algorithm. We then perform analysis of variance on distinct clusterings and detect significant differences for both years. The subsequent post hoc tests (Dunn) show that yearly incidence rate observed in the areas with highest RAMPP values is always significantly greater than that recorded with smaller RAMPP values. RAMPP takes into account of population mobility in urban settings via the use of passenger traffic information of urban transportation system, that captures the simple but important idea that large amount of passenger flow in and out of a station can dramatically increase the contagion risk of dengue in the neighborhood. Our study provides a new perspective in identifying high-risk areas for transmissions and thus enhances our understanding of how public rapid transit system contributes to disease spread in densely populated urban areas, which could be useful in the design of more effective and timely intervention and control measures for future outbreaks.

Project description:A SIRU-type epidemic model is employed for the prediction of the COVID-19 epidemy evolution in Brazil, and analyze the influence of public health measures on simulating the control of this infectious disease. The proposed model allows for a time variable functional form of both the transmission rate and the fraction of asymptomatic infectious individuals that become reported symptomatic individuals, to reflect public health interventions, towards the epidemy control. An exponential analytical behavior for the accumulated reported cases evolution is assumed at the onset of the epidemy, for explicitly estimating initial conditions, while a Bayesian inference approach is adopted for the estimation of parameters by employing the direct problem model with the data from the first phase of the epidemy evolution, represented by the time series for the reported cases of infected individuals. The evolution of the COVID-19 epidemy in China is considered for validation purposes, by taking the first part of the dataset of accumulated reported infectious individuals to estimate the related parameters, and retaining the rest of the evolution data for direct comparison with the predicted results. Then, the available data on reported cases in Brazil from 15 February until 29 March, is used for estimating parameters and then predicting the first phase of the epidemy evolution from these initial conditions. The data for the reported cases in Brazil from 30 March until 23 April are reserved for validation of the model. Then, public health interventions are simulated, aimed at evaluating the effects on the disease spreading, by acting on both the transmission rate and the fraction of the total number of the symptomatic infectious individuals, considering time variable exponential behaviors for these two parameters. This first constructed model provides fairly accurate predictions up to day 65 below 5% relative deviation, when the data starts detaching from the theoretical curve. From the simulated public health intervention measures through five different scenarios, it was observed that a combination of careful control of the social distancing relaxation and improved sanitary habits, together with more intensive testing for isolation of symptomatic cases, is essential to achieve the overall control of the disease and avoid a second more strict social distancing intervention. Finally, the full dataset available by the completion of the present work is employed in redefining the model to yield updated epidemy evolution estimates.

Dataset Information

An evaluation of the impact of COVID-19 safety measures in public transit spaces on riders' Worry of virus contraction.

Publications

An evaluation of the impact of COVID-19 safety measures in public transit spaces on riders' Worry of virus contraction.

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