Mobility policies in public transport were guided by the distancing of people during the pandemic. However, its effect on users’ risk perception was not fully established as a discussion axis in the research agenda. Therefore, the study aimed to address this gap by comparing the theoretical structure against the empirical structure analyzed in a systematic review. A cross-sectional and correlational work was carried out with a sample of experts who evaluated the prevalence of the categorical dimensions of risk perception in public transport mobility using the Delphi technique. The results confirm a second-order factor that makes the model extension essential to the state of the art where prevention is highlighted, with practical implications for public health and transport policy.

The COVID-19 pandemic has significantly impacted human mobility patterns and risk attitudes (Chan et al., 2020). Studies have shown that the marked decline in mobility following the World Health Organization's declaration of the pandemic can be attributed to risk attitudes. Several research efforts have been undertaken to assess the spatial and temporal risk of COVID-19 transmission based on mobility data (Rahimi et al., 2021). Using human mobility models to assess transmission risk resulted in generating heat maps indicating the risk of exposure under different scenarios (Jiang et al., 2021). Similarly, a technique for assigning spatial and temporal risk scores uses high-resolution mobility data, focusing on location density and mobility behavior (Lawal & Nwegbu, 2022). Furthermore, studies have explored the use of mobility data for early detection and risk prediction of COVID-19 outbreaks (García et al., 2023). A data-driven framework for assessing neighborhoods and predicting infection risks ahead of outbreaks (Zachreson et al., 2021). In addition, a procedure for producing spatial transmission risk assessments uses population mobility data, highlighting the utility of aggregated human mobility data for estimating transmission risk (Martin & Bergmann, 2021). In addition, the impact of interventions such as mask mandates on mobility behavior and risk compensation has been investigated. Analyzing mobility data to assess the risk-offsetting effects of mask mandates emphasizes the importance of understanding how interventions influence human behavior during the pandemic (Pullan et al., 2020). Overall, research on COVID-19 risk mobility has focused on leveraging mobility data to assess transmission risk, predict outbreaks, and evaluate the impact of interventions on human behavior and risk attitudes (Freudendal-Pedersen & Kesselring, 2021). By using high-resolution mobility data and human mobility models, researchers seek to improve understanding of the spatial and temporal dynamics of COVID-19 transmission and improve response strategies to mitigate the spread of the virus.

Table 1. Comparison of the dimensions of risk perception in public transport mobility during the pandemic

However, studies on mobility and risks have not focused on policies and their effects on risk perception (Luo et al., 2021). Therefore, the objective of this study was to conduct a systematic literature review to reveal metropolitan mobility and peri-urban health policies, focusing the discussion on the effects of public transport safety on users' health. Are there significant differences between risk policies regarding the perception of risks of contagion, illness, and death from COVID-19 in the literature from 2020 to 2024? Given that distancing and confinement policies impact risk perception, significant differences are expected between the literature published from 2020 to 2024 regarding the relative dimensions of public transport's performativity as a route of transmission of COVID-19.

A cross-sectional and correlational study was conducted with a non-probabilistic selection of indexed sources published in international repositories from 2020 to 2024 and searched with keywords. The PRISMA format (see Annex A) was used for the systematic review of the literature, considering seven dimensions related to exposure to risks of contagion, illness, and death from COVID-19 (Rambhatla et al., 2022). Reliability ranged between 0.645 and 0.756 for each of the mobility risk dimensions. Validity was established between 0.337 and 0.561. The sphericity test was significant, and the adequacy exceeded the minimum indispensable value of 0.60.Data were captured in Excel and processed in Google Colab (see Appendix B). Reliability, adequacy, sphericity, validity, adjustment, and residual coefficients were estimated to test the hypothesis regarding significant differences. Values close to one were considered evidence of non-rejection of the null hypothesis.

The analysis of covariances suggests the introduction of other indicators and factors in the model (Figure. 1). The covariances between the dimensions were close to zero, which suggests the inclusion of other indicators and factors not contemplated in the instrument.

Figure 1. Covariances between the first-order factors

The structural analysis captures the relationships between first- and second-order factors (Fig. 2). The findings indicate that the second-order factor, related to risk perception, is indicated by seven factors reported in the literature on mobility policy and transport risk.

Figure 2. Confirmatory factor analysis of the transportation risk policy in Mexico City.The fit and residual values

 suggest that the hypothesis regarding significant differences between the theoretical structure and the empirical analysis is not rejected.

This study's contribution to the state of the art lies in establishing an empirical model to compare with the theoretical model reported in the literature regarding mobility and risk perception in transport during the pandemic. The results highlight the emergence of a second-order factor that the literature identifies as risk perception. Mobility policies reveal the prevention of risk events' effects on users' health (Chang et al., 2021). The data supporting the non-exposure to risk events are derived from mobility policies on public transport safety and users' health (Gibson, 2021). Mobility  policies focused on the effects of transport safety on users' health do not recognize the risks of exposure or the short-, medium--, and long-term consequences.

Unlike the state of the art in which mobility policies are not evaluated from the perspective of risk perception, this work suggests that from the literature reviewed, it is possible to infer risk perception as an effect of confinement and distancing policies. In this sense, it is recommended that the study be extended to the dimensions of mobility and overcrowding to anticipate a scenario of risks of contagion, illness, and death from COVID-19.

The purpose of the study was to compare the theoretical structure reported in the literature from 2020 to 2024 regarding mobility policies concerning an empirical structure analyzed from the perception of risk as an effect of distancing and confinement policies. The results demonstrate the prevalence of a second-order factor that the literature identifies as the perception of mobility risk. In the state of the art in which the association between distancing and confinement policies as axes of mobility in public transport is demonstrated, this work suggests including a second-order factor that the literature identifies as risk perception. It is recommended that the study be extended to the impact of mobility on public transport mediated by the distancing of people.