Urban Rail Transportation and SARS-Cov-2 Infections: An Ecological Study in the Lisbon Metropolitan Area
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Abstract
Introduction: The large number of passengers, limited space and shared surfaces can transform public transportation into a hub of epidemic spread. This study was conducted to investigate whether proximity to railway stations, a proxy for utilization, was associated with higher rates of SARS-CoV-2 infection across small-areas of the Lisbon Metropolitan Area (Portugal).
Methods: The number of SARS-CoV-2 confirmed infections from March 2 until July 5, 2020 at the parish-level was obtained from the National Epidemiological Surveillance System. A Geographic Information System was used to estimate proximity to railway stations of the six railway lines operating in the area. A quasi- Poisson generalized linear regression model was fitted to estimate the relative risks (RR) and corresponding 95% confidence intervals (95%CI).
Results: Between May 2 and July 5, 2020, there were a total of 17,168 SARS-CoV-2 infections in the Lisbon Metropolitan Area, with wide disparities between parishes. Overall, parishes near any of the railway stations of the Sintra line presented significantly higher SARS-CoV-2 infection rates ( RR = 1.42, 95%CI 1.16, 1.75) compared to parishes located farther away from railway stations, while the opposite was observed for parishes near other railway stations ( Sado and Fertagus lines), where infection rates were significantly lower than those observed in parishes located farther away from railway stations ( RR = 0.66, 95%CI 0.50, 0.87). The associations varied according to the stage of the epidemic and to the mitigation measures enforced. Regression results also revealed an increasing influence of socioeconomic deprivation on SARS-CoV-2 infections.
Conclusions: No consistent association between proximity to railway stations and SARS-CoV-2 infection rates in the most affected metropolitan area of Portugal was observed, suggesting that other factors (e.g., socioeconomic deprivation) may play a more prominent role in the epidemic dynamics.
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SciScore for 10.1101/2020.09.18.20195776: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:This study has limitations that need to be considered. First, the data and analyses were derived from an ecological approach due to the lack of information of individual use of rail transport, weakening causal inference at the individual level. Ecological designs also limit our capacity to control for confounding, meaning that other …
SciScore for 10.1101/2020.09.18.20195776: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:This study has limitations that need to be considered. First, the data and analyses were derived from an ecological approach due to the lack of information of individual use of rail transport, weakening causal inference at the individual level. Ecological designs also limit our capacity to control for confounding, meaning that other factors (for which information was unavailable) rather than proximity to railway stations or socioeconomic deprivation may partially explain our findings (e.g. other modes of transportation, types of activities taking place in each area, population ethnic composition, etc.). Second, our study may be affected by the Modifiable Areal Unit Problem (MAUP) (27), which happens when the number of spatial units (the scale) used to define the same area affects the study conclusions. If the geographical units are large, it is more likely that associations found at the aggregate level will diverge from the same associations found at individual level leading to the so-called ecological fallacy (28). In our study, we used the smallest geographical unit available to minimize this problem. A third issue, is the Uncertain Geographic Context Problem (UGCoP) (29). Case data is available according to the parish of occurrence, but focusing only on occurrence location may introduce uncertainty in research results, because people may spend a considerable amount of time in other parishes and may acquire the disease in these locations (e.g. work, transportation, etc.) (3...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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