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. 2023 Jan 4;31:244–253. doi: 10.1016/j.tbs.2023.01.001

Reactions of the public transport sector to the COVID-19 pandemic. Insights from Belgium

Sara Tori 1,⁎, Alice de Séjournet 1, Cathy Macharis 1
PMCID: PMC9810552  PMID: 36619852

Abstract

Throughout the COVID-19 pandemic, public transport has been one of the hardest hit transport modes, losing ridership due to fear of contagion. This can partially be explained by the lack of preparedness in the sector to a pandemic scenario, as only few cities had epidemic contingency plans for the transport sector. To anticipate disruptions caused by future crises, we look at the preparedness and the response to COVID-19 by the public transport sector in Belgium. We interview all public transport operators in Belgium and analyze the interviews through the disaster management framework. We also aim to distill the lessons that can be learned from the pandemic to increase resilience in future public transport planning. We find that no operator in Belgium had contingency plans ready for a pandemic scenario, but that other plans were deployed to adapt their offer to COVID-19 conditions. Although all operators lost a significant part of ridership, their offer was maintained throughout the crisis, albeit at a decreased level for some operators. The availability of reliable and real-time data is identified as an important learning by the operators, as well as the ability to identify a core response team in case of a crisis. COVID-19 was seen by the operators as a learning platform to face future crises and highlighted the need to increase reactivity through better preparedness and data availability. We recommend the structural use of foresight methods through for example scenario planning to increase the preparedness of operators in the case of future disruptions.

Keywords: Disaster management framework, Public transport, COVID-19, Resilience, Mobility, Crisis response

1. Introduction

In the current context of the climate crisis, public transport has been known to alleviate the negative externalities of transport, such as congestion and pollution, and, at the same time, foster healthier and more livable cities (Camacho et al., 2016). Throughout the COVID-19 crisis that started in March 2020 however, public transport has been one of the hardest hit transport modes, losing out on ridership due to a fear of contagion (Qi et al., 2021) and mandatory telework (de Séjournet et al., 2022). From research done by Zhang et al. (2021) among experts worldwide, it appeared that only about 30 % of cities had guidelines and contingency plans for a public health threat in the transport sector. Similarly, Corazza et al. (2021), based on expert questionnaires worldwide, show that the public transport sector lacked contingency plans for pandemics. Public transport operators therefore responded largely with ad-hoc measures to the disruption represented by COVID-19 (Gkiotsalitis and Cats, 2021). As a result of the measures and the fear of contagion within public transport, a trend has therefore emerged towards the use of individual transport modes instead of public transport (Tirachini and Cats, 2020). Indeed, there is an inherent contradiction between social distancing measures, implemented to reduce the spread of COVID-19, and the nature of public transport (Kopsidas et al., 2021). COVID-19 measures directly affected transport policy measures aimed at sustainable transport, and temporarily replaced typical transport policy measures (Corazza et al., 2021). After two years of the COVID-19 crisis, it is important to look at what the effects of the crisis have been on public transport and how we can learn from it to anticipate future disruptions, especially considering that disruptions can present an opportunity for policy change (Marsden and Docherty, 2013). This is especially important considering that transportation systems are exposed to a wide variety of such disruptions, which can be either natural or man-made disasters (Wan et al., 2018). To remain an attractive alternative to individual modes for travelers, public transport has to be able to withstand or quickly recover from a disruption (Malandri et al., 2018).

The goal of our research is therefore twofold. First, we look at the preparedness and the responses of all four public transport operators in Belgium to the COVID-19 crisis. A second objective is to analyze the recovery of the operators to provide learnings for more resilience in future public transport planning. Now that the initial shock of COVID-19 is behind us, the crisis provides us with an opportunity to develop methods to support more evidence-based decision making (Gkiotsalitis and Cats, 2021), which is one of the best ways to develop transportation policies (Ahmad and Puppim de Oliveira, 2016).

Our analysis is based on the disaster management framework, which consists of four stages of actions in the face of a disaster (Mitigation, Preparedness, Response, Recovery) (Coppola, 2015). A disaster arises due to uncontrollable external factors with a potential for strong change and which lead to the need to respond with exceptional measures (Faulkner, 2001), and, in that sense, COVID-19 can be defined as a disaster (Hao et al., 2020). Although it currently remains unknown what the long-term effects of COVID-19 will be on public transport, an understanding of the crisis in terms of disaster management can help build the resilience of public transport systems and face future crises. Disaster management is key to reduce the harm and the likelihood of disasters (Coppola, 2015).

This paper is structured as follows: in the next section, we provide a brief overview of the effects of COVID-19 on public transport, and of the disaster management framework. In Section 3, we provide details on the country of Belgium and on the methodology we employed. Section 4 shows our results and a discussion, while Section 5 provides concluding remarks.

2. Background and theoretical basis

Coppola (2015) defines a disaster as a hazard that overwhelms a community’s response capability. On March 11th, 2020, when the COVID-19 virus was about to overwhelm health systems around the world, the World Health Organization (WHO) declared it to be a pandemic. The fast spread, the severity and the strong inaction of governments at that time led the WHO to urge governments to prepare, respond, mitigate and learn (WHO, 2020). These relate back to the four key concepts of the disaster management framework, that will be explained in Section 2.2. The direct risks brought on by COVID-19 were on health and on healthcare systems, and, to reduce this risk, containment measures were suddenly put in place by governments around the world. Because of interconnectedness, these measures, such as for example the successive lockdowns, led to cascading risks and impacts across other sectors and systems (UNDRR, & UNU-EHS, 2022). In the next sections, we will look at the effects of the COVID-19 pandemic on public transport and then discuss the disaster management framework.

2.1. Effects of COVID-19 on the public transport sector

Throughout the world, public transport is a sector that has been hit hard by the COVID-19 pandemic (Gkiotsalitis and Cats, 2021). One reason for this is that there was a low percentage of guidelines and contingency plans in the transport sector (Zhang et al., 2021). During the first lockdowns in March 2020, ridership levels in China were estimated to have dropped by 80–90 %, and by up to 70 % in the UK (UITP, 2020b). In an analysis of 113 transit systems in the US, Liu et al. (2020) found an average decrease of −73 %. In Santander, Spain, public transport ridership fell 93 %, whereas the average reduction in mobility for all modes was −76 % (Aloi et al., 2020). This is partially due to the emerging trend of favouring individual motorized mobility over public transport, in line with COVID-19 containment measures (Tirachini and Cats, 2020). Private motorized transport has been depicted as a safe alternative to public transport, thereby rendering public transport less attractive (Corazza et al., 2021). In Brussels, Belgium, public transport has been slower to return to pre-pandemic levels, whereas driving levels returned to pre-pandemic levels at the end of 2021 (de Séjournet et al., 2022). Worldwide, operators have reacted very differently to the pandemic, with some even suspending services altogether, like in the Hubei province of China (Jiang et al., 2020). Reduction of the offer has also been a widespread approach in countries around the world, as was for example seen in Washington DC, where metros were running every twelve minutes instead of every-four to eight (UITP, 2020b). Similarly, Rome, Naples and London suspended night services (UITP, 2020b, UITP, 2020a).

The restrictive measures implemented to reduce the spread of the coronavirus in the spring of 2020 often involved severe lockdowns, and specific measures were taken also within public transport. In a worldwide survey distributed in the spring of 2020, Zhang et al. (2021) find that physical distancing in public transport and at stations/stops are among the most widely implemented measures across the different regions. Other examples include boarding vehicles at the rear to avoid contact with the driver, or opening windows for increased ventilation (Kamga and Eickemeyer, 2021). In half the surveyed cities, it was recommended to restrict the number of passengers on the vehicles, and in one fifth, a booking system for public transport was recommended by local authorities (Zhang et al., 2021). In the US and Canada, Kamga and Eickemeyer (2021) highlight that physical distancing in public transport was enforced in a variety of ways, including limiting the number of people in stations, roping off benches in the station, and reducing seating availability in vehicles. For EU countries, recommendations were also made to have passengers wear face masks, and to increase the frequency of cleaning and disinfection of public transport services (ECDC, 2020). At the onset of the pandemic, in February 2020, the International Association of Public Transport (UITP) shared some guidelines to help the public transport operators prepare business continuity plan. These focused on personal protection, reduction of contacts and reduction of services (UITP, 2020a).

In order to increase resilience of the public transport sector in the face of future pandemics, it is therefore important to rethink transport policy making. Increased preparedness and more flexible planning in transport can ensure that decision-making becomes easier when a disruption strikes, allowing also to take advantage of a crisis (de Séjournet et al., 2022). Overall, the COVID-19 crisis, as a disruption, has the potential to change the path of existing trajectories within the transport sector, but at the same time the pandemic was a rather limited time window in which to enact change to transport policy (Marsden and Docherty, 2021).

2.2. Disaster management framework

The aim of the disaster management framework is to reduce the “harm to life, property and the environment” (Coppola, 2015, p. 1). It is composed of four stages. First, mitigation aims to reduce the risk or the extent to which a hazard impacts society. Then, preparedness is giving the tools to react to those who will be directly impacted by the hazard. These actions are taken before a hazard strikes, to ensure that the response is fast and efficient. These actions involve, but are not limited to, planning, exercises and trainings, investing in the right equipment but also the identification of a statutory authority which will coordinate the response. Third, responses are the actions taken when the hazard strikes to reduce its impact. These actions can be taken before, during and immediately after the hazard event. If this response capacity is overwhelmed then the hazard is qualified as a disaster (Coppola, 2015). Finally, recovery is the phase to regain what has been lost and return to normal or to a new equilibrium. It is also necessary to draw learnings at this stage to reduce the consequence of a future similar hazard (Coppola, 2015). However, although there has been an increase in research on disaster management, it has not necessarily led to an impact on disaster management practice (Donahue and Tuohy, 2006, Kunz et al., 2017). Some of the reasons are a lack of systems to disseminate lessons learned (Donahue and Tuohy, 2006) and a difficult access to data (Kunz et al., 2017).

In the context of the COVID-19 pandemic, the range of responses was different than in traditional emergency management responses to natural hazards such as flooding, earthquakes or wildfires. These require, among other interventions, rescue actions in a specific area. Unlike these other disasters, pandemics do not damage infrastructure (Fletcher et al., 2014). The COVID-19 pandemic was characterized by an exponential spread and by different successive waves, that led to subsequent tightening of governmental response measures (UNDRR, & UNU-EHS, 2022). There were also a lot of uncertainties about its potential spread, which have been increased by the successive variants (UNDRR, & UNU-EHS, 2022). Wankmüller (2021) pointed out that European countries were highly unprepared for this pandemic, despite the warnings that such an event would take place.

Within transport, research on disaster management has focused on how to develop an evacuation plan in emergency circumstances (Coppola, 2015), how to prepare staff to react fast and appropriately in case of an accident (Hofinger et al., 2011), or how to keep a minimal service level while part of the network is damaged by a natural hazard (Berdica, 2002). In the case of the COVID-19 pandemic, the issues are different, as the network did not encounter any damage, and that the time and scope of the hazard are unlike usual network disruptions. Marsden and Docherty (2021) interviewed representatives of government and transport organisations in the UK twice in the early stage of the pandemic, after the first lockdown and before the second wave. They highlighted that transport stakeholders were following public health decisions and that these stakeholders were unprepared for the pandemic. Pandemic contingency plans, if there were any, focused mainly on the impact of staff absence (Marsden and Docherty, 2021).

3. Materials and methods

The goal of our research was to, on the one hand, analyze the preparedness and the response of the public transport sector in Belgium in the face of COVID-19. On the other hand, we aim to understand what lessons can be learned from the current crisis in terms of long-term planning and resilience in public transport. We do this by applying the disaster management framework to the Belgian public transport system, looking at the COVID-19 period between January 2020, and March 2022. To this extent, we conducted interviews with public transport operators at the end of March 2022. This was done after the Belgian government declared ‘code yellow’ in the country on March 5, 2022, putting an end to the epidemiological crisis situation first declared in March 2020 (Belgium.be, 2022).

3.1. The Belgian context

3.1.1. Pre-pandemic situation

Belgium is home to 11,521,238 inhabitants (Statbel, 2021) for a surface area of 30,688 km2 (Belgium.be, 2008a). The country has well-developed road, air, rail, and inland waterway networks. In terms of public transportation, there are four public operators responsible for providing public transport. Railways connect the whole country through a network of 3,602 km (Infrabel, 2016). The national passenger railway system is operated by NMBS-SNCB.

In Flanders, in the north of the country, public transport is provided by De Lijn, who operate bus lines throughout the region, as well as trams in Antwerp, Ghent, and along the coast (Belgium.be, 2008b). In 2019, 201,265,506 km were driven by the operator (De Lijn, 2019). In Wallonia, in the south of the country, bus lines are operated by TEC along with trams in Charleroi. In 2019, 119,346,317 km were driven (TEC, 2019). Public transport in the Brussels Capital Region is operated separately by STIB-MIVB, with a network of buses, trams, and metros. In 2019, 48,300,000 km were driven (STIB, 2019). De Lijn and TEC are also active in Brussels, in collaboration with STIB, for inter-urban lines.

The modal split in the three regions is shown in Fig. 1 , and is based on the last available national mobility survey (FOD Mobiliteit en Vervoer, 2017). From the figure, it becomes apparent that public transport is used most in Brussels, where it accounts for 24 % of all trips.

Fig. 1.

Fig. 1

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Modal split in Belgium per number of trips (FOD Mobiliteit en Vervoer, 2017).

In terms of the use of the different modes for different types of trips, Fig. 2 shows that public transport is used most for school mobility (21 %) and commuting (18 %).

Fig. 2.

Fig. 2

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Modal split in Belgium per type of trip (FOD Mobiliteit en Vervoer, 2017).

3.1.2. Pandemic situation

In Brussels, public transport was one of the modes most affected by the COVID-19 pandemic (de Séjournet et al., 2022). All four Belgian public transport operators were strongly affected by the pandemic, with national railway services, for example, reaching only 5–10 % of their pre-pandemic occupancy rates during the spring 2020 lockdown. The figure below shows, for all operators, the change in occupancy rates over the last two years, compared to their pre-COVID level. Important to mention is that not all operators used the same method to measure the changes in ridership. De Lijn and NMBS used 2019 as a baseline, while STIB used a baseline in January-February 2020. In addition, the occupancy rates for TEC are only indicative, since there has been a strong increase in fraud (from 5 % pre-COVID to around 25 % since the start of the pandemic). Therefore, only the yearly averages are depicted in Fig. 3 . Fig. 3 also shows the evolution of COVID-19 cases in Belgium (Sciensano, 2022).

Fig. 3.

Fig. 3

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Changes in public transport ridership and evolution of COVID-19 cases over the studied period.

3.2. Content analysis

To understand the impact the COVID-19 crisis had on the public transport operators in Belgium and what lessons have been learned from it, we held in-depth semi-structured interviews with representatives from all four public transport operators. Semi-structured interviews were used as they allow for the exploration of the respondents’ answer, as well as for clarification of interesting and relevant issues. In addition, the representatives within the different public transport operators had varied responsibilities, making it more difficult to use a standardized interview schedule (Barriball and While, 1994). The structure and questions of the interview are based on the disaster management cycle. Table 1 shows the focus areas and the pre-identified questions within each area. The definitions of the priority areas were based on the definitions of the phases of the disaster management cycle of Coppola (2015). Important to highlight is that, although the disaster that occurred was the COVID-19 virus, the public transport operators were actually acting on and reacting to the impacts of the various measures imposed by the government.

Table 1.

Interview structure and questions.

Period Phase in the disaster management cycle Priority area Main guiding questions
Pre-COVID Mitigation Reducing the likelihood or the consequences of a disaster.
  • •

    Is there a risk assessment for epidemics in the public transport sector?

  • •

    Are there trainings for epidemic situations for relevant professions?

  • •

    Are there regulations regarding epidemics in the public transport sector?
Preparedness Equipping people who could be impacted or who could help people impacted by a disaster with tools.
  • •

    Are there learnings out of former epidemics (e.g., swine flu or MERS)?

  • •

    Is there trained epidemic staff?



COVID Response Actions to reduce the impact of a disaster.
  • •

    Can the provision of public transport be guaranteed?

  • •

    Have measures to avoid infections been implemented?

  • •

    How is the communication with clients?



“Post”-COVID Recovery Returning back to normal following the impact of the disaster and drawing learnings from it.
  • •

    Can public transport operate as it was before the pandemic?

  • •

    Is there a need for optimization in dealing with epidemics?

  • •

    What are the learnings out of the COVID-19 situation?
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When contacting the operators, we explained the goal of the study and asked to be put in contact with a person within the organization that could answer our questions with regards to pre-COVID preparation, response to COVID-19, and then “post”-COVID-19 longer-term implications for the operator strategy. Table 2 shows an overview of the areas of expertise of the different interviewees. For one of the interviews (De Lijn), three representatives were present because the questions addressed different sectors within the organization.

Table 2.

Overview of interviewee characteristics.

Operator Area of expertise within operator
STIB Network director
De Lijn Risk management, market research, market analysis
TEC Corporate strategy
NMBS Corporate strategy
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The interviews took place digitally through Microsoft Teams in the week of March 28–April 1, 2022. Two interviews were held in Dutch, two in French. Each interview lasted between 45 and 60 min and was recorded with the permission of the interviewees. Afterwards, the interviews were transcribed verbatim, first using the HappyScribe software,1 and then the transcriptions were checked manually.

The interviews were analyzed through content analysis in the NVivo software.2 Content analysis is a qualitative analysis method used to analyze written, verbal, and visual communications (Cole, 1988). The data is coded either through emergent coding, where the codes and the code categories are established by preliminarily examining the data and identifying the emerging coding scheme. Alternatively, a priori coding can be employed, where the coding categories are identified prior to the analysis based on existing theories or frameworks (Stemler, 2000). We coded a priori since our analysis was based on the disaster management cycle. The interviews were coded by two separate researchers to increase the reliability of the coding, so that the coding is consistent (Weber, 1990). In a first round of coding, the goal was to remain very close to the original interview content. This first round of coding was discussed after each researcher coded the material separately. In a second round of coding, codes and themes identified were merged to obtain a final set of relevant themes. The themes focused on the similarities and the differences in the application of the disaster management cycle across operators.

4. Results and discussion

From the interviews that were held with the four Belgian public transport operators, it became clear that the pandemic has had different implications and effects on the different operators. Some of these differences occurred because of the different characteristics of the operators, while others relate to the pre-pandemic levels of readiness in terms of a crisis. In the sections below, we discuss the results of the interviews along the four steps of the disaster management cycle.

4.1. Mitigation

As the first phase of the disaster management framework, mitigation includes measures taken to reduce the likelihood or the consequence of the disaster (Coppola, 2015). In the case of a pandemic, mitigation includes possible risk assessments in the public transport sector, or trainings for personnel, as well as governmental regulations regarding epidemics in public transport. From all interviews, it became clear that there were no such measures in the Belgian public transport sector prior to COVID-19, and that, as such, no risk assessment regarding epidemics was performed by the operators. Similarly, Marsden and Docherty (2021) found that the UK transport sector was unprepared for a pandemic, and Zhang et al., 2021, Corazza et al., 2021 showed similar results in their worldwide surveys. Although COVID-19 first appeared in December 2019 (WHO, n.d.-a), no mitigation strategy was implemented before the start of the lockdown in March 2020, since there was a high level of uncertainty with regards to the potential spread of the virus (UNDRR, & UNU-EHS, 2022). It is important though to highlight that, in February 2020, the international Association of Public Transport (UITP) issued guidelines on the management of COVID-19 (UITP, 2020a). While February 2020 is quite close to the onset of the pandemic, older guidelines on the management of pandemics also existed (Fletcher et al., 2014).

Overall, we can therefore conclude that no mitigation measures were taken within the Belgian public transport sector in terms of epidemics.

4.2. Preparedness

Preparedness in the disaster management framework entails equipping people with tools to counter the effects of a disaster, or to help people impacted by the disaster (Coppola, 2015). In the context of COVID-19, we wanted to understand whether former epidemic scares had led to preparations within the different operators. From the interviews, we saw that the H1N1 (‘swine flu’) pandemic of 2009–2010 (WHO, n.d.-b) had led to epidemic preparedness within one of the operators (TEC). This preparation included a plan ready to be deployed for internal communications towards personnel about personal sanitary measures in the case of an epidemic. However, it was not as well-developed as what was required to face the coronavirus pandemic: “At the very onset of the crisis, this plan helped us. But we quickly realized that the scale was not at all similar…. It was only useful at the very start.” It also did not include any scenarios for the adaptation of the operator’s offer, since a widespread event like COVID-19 had not been anticipated. The lack of preparedness specifically for an epidemic scenario is in line with the findings of Zhang et al. (2021), who found that the majority of cities did not have contingency plans for such an outbreak.

Although there was no preparation within the operators for a widespread pandemic scenario, there were contingency plans that could quickly be deployed in the case of other crises, and that could be adapted to the case of COVID-19. STIB has a ‘SOS’ plan that is used for strikes and other disruptions. This plan consists of a small number of scenarios and is based on the available number of drivers. Depending on the number of drivers, prioritized lines are run. This starts with metro lines, and then above-ground vehicles are operated if sufficient drivers are present. The plan also has a scenario where underground vehicles cannot be operated, which was developed after the terrorist attacks of March 22, 2016 (RTBF, 2016). Similarly, De Lijn has an overview of lines to prioritize in the case of strikes, and NMBS has contingency plans in case of a lack of personnel. Interesting to note as well is that, within De Lijn, business continuity plans are also developed more around organizational structures than around actions; the focus lies on the identification of the right people with the right responsibilities in the case of a crisis. We can conclude that, although the level of preparedness specifically for a pandemic was rather low, broad preparedness for strikes and other crises was available.

4.3. Response

The response part of the disaster management cycle entails actions that can be taken to reduce the impact of a disaster (Coppola, 2015). In the case of COVID-19, although the virus was the disaster event, the operators rather responded to the measures imposed by the government to stop the spread of the virus. In the next sections, we analyze these responses in terms of sanitary measures, ridership and offer, as well as organization.

4.3.1. Sanitary measures

The sanitary measures implemented in public transport were similar across all operators, since they followed the measures imposed by the government. These included the mandatory wearing of masks, a maximum occupancy rate per vehicle to respect social distancing, not boarding buses and trams from the front of the vehicle, and increased cleaning and disinfection of vehicles and stations. In addition, cash payments for tickets on board were forbidden, so on-board cashless payments were introduced by TEC, STIB, and De Lijn. NMBS also employed stewards in 70 of its biggest train stations to guide passengers, and all operators increased passenger communications with regards to the ongoing sanitary measures.

4.3.2. Ridership and offer

Overall, ridership on all four operators suffered a severe blow during the first lockdown in the spring of 2020 (see Fig. 2). However, since all public transport operators in Belgium are public, none stopped with the provision of services. The government explicitly asked the operators to keep their regular offer, which was done by De Lijn, who did not reduce services. The other three operators activated the contingency plans available to them that were discussed in section 4.2 and reduced their offer. As an important side note however, although the government asked all operators to keep riding, there were also explicit governmental communications to avoid public transport because of the risk of contagion, and to therefore ‘leave public transport to those who really need it’ (Bruzz, 2020). According to TEC, this has led to a stigmatization of public transport, creating frustration in the sector: “I remember a press conference during which it was explicitly stated that people should not take public transport, but to use their car instead. That is inadmissible. Public transport is stigmatized… Now, people go to clubs and cafés, but on public transport, passengers have to wear facemasks.” Similarly, Marsden and Docherty (2021) showed that messages to avoid public transport were not well-received by the sector.

STIB first used the strike scenario within their ‘SOS’ plan, meaning that fewer lines were operated. The reason for this is that, due to social distancing measures, they preferred to operate fewer lines at a higher frequency, to avoid crowding of the vehicles. In total, about 60 % of their regular offer was operated, although essential places (like hospitals) were prioritized, and the offer to those places was 80 % on average. After only a couple of weeks, they updated this plan to a ‘SOS 2’, because they realized that, due to the lockdown, the travel times of vehicles were significantly reduced. They were, in this way, able to operate more lines with the same resources than in the first ‘SOS’ plan. In a third phase, before returning to their regular offer, a holiday offer was put into place since, again, this one is more optimized, and more services can be offered with the same resources.

Overall, STIB noticed a more significant decrease in ridership during the week than during the weekend, and during peak hours when compared to off-peak hours. Important to note is that, as was also mentioned by TEC and De Lijn, changing the scheduling and the offer is a very time-consuming task. For STIB, implementing changes takes an average of 40 days: “To handle road construction or special events in the city, we review our offer every couple of weeks. That process currently takes us 40 days: three weeks of planning and three weeks to organize the different business units concerned. We’ve seen it: we can be much more reactive than that when there is a crisis.” Here, they were able to deploy an existing ‘SOS’ plan in only two days, because they were not departing from scratch in terms of offer.

Similarly, NMBS enacted their “train service of national interest” at the onset of the pandemic, between March 23, 2020, and May 4, 2020. This train service of national interest entailed a reduction of the number of trains (to 60 %), as well as a reduction of the number of seats (to 75 %). The company analyzed where its most important commuting corridors were located by looking at the demand, often linked to the workplaces of essential workers. They then chose to organize the remaining offer along structural corridors through Brussels, to ensure the highest coverage possible. After May 4, 2020, NMBS returned to its regular offer. In December 2021, the railway company even increased its offer permanently.

For TEC, the offer was put into school holiday mode since schools were closed during the spring 2020 lockdown. This led to a surplus of drivers, since the company operates a lot of lines that are only used by students, who were then asked to strengthen the lines to and from essential services. From September 2020 onwards, the regular offer was reinstated since schools were open again and needed to be reached by students. During some parts of the pandemic, TEC, as well as De Lijn, also used private coaches to strengthen their regular bus services and to facilitate social distancing measures. Throughout the different phases of the pandemic, TEC then used what they called ‘pragmatic criteria’ to adapt their offer to the evolving pandemic situation, instead of, like was done by STIB, criteria that prioritize certain lines. An example of such a criterion to deal with absent personnel is that, if children were dropped off at school in the morning, they needed to ensure there would be a bus picking them up in the evening. Another example criterion is to remove extra vehicles which usually handle peak hour travel demand.

For all operators, the levels of absent personnel, due to either COVID infections or quarantines, was one of the most important reasons to reduce the offer, and not the decrease in ridership due to the changing numbers of COVID-19 infections in the country.

4.3.3. Organization

Of course, the COVID-19 pandemic influenced the organization of the various operators. Within De Lijn, as was mentioned in section 4.2, the business continuity plans focused more on structural elements rather than on specific actions. The operator was therefore able to quickly assemble a task force of pre-identified personnel to handle the pandemic situation. However, there was a realization that this exercise, and the identification of the right stakeholders to involve, had not yet gone far enough pre-pandemic: “The list was further developed with stakeholders that initially were not included… We always keep learning.”. As a result, De Lijn expanded on this pre-COVID identification throughout the pandemic to allow them to be more reactive.

In addition, for all operators, communication with passengers was strengthened so that passengers would be aware of the ongoing measures as well as the changes in offer. All four operators, during the first months of the pandemic, also developed an occupancy meter for their vehicles. This way, passengers could be aware, before boarding, how busy vehicles were expected to be. The occupancy rate is visible in the applications or on the websites of the operators.

Two of the operators (De Lijn and NMBS) mentioned that, throughout the pandemic, they identified key operational positions, without which it was not possible to provide their offer. For each position, they quantified thresholds of personnel that needs to be present to operate normally. In case a high number of employees is absent, measures were worked out to ensure the provision of services could continue, like the cancellation of non-mandatory trainings. This allowed the operators to maintain a high level of their offer even with a high number of absent employees.

In conclusion, the range of responses throughout the COVID-19 crisis have been very broad. Initially, the offer from three operators was reduced, and strict sanitary measures were employed. Additionally, occupancy rates of vehicles were added to the operators’ applications, and a number of key positions with a minimal threshold of workers present were identified.

4.4. Recovery

Recovery is the last phase of the disaster management cycle, where there is a return to normal following the disaster. Coppola (2015) states that this phase starts after the immediate response has ended. In the case of COVID-19, there appears to be a cycle of response-recovery since the different waves of the pandemic entailed new measures and reactions each time. At the same time, operators were already able to use learnings from the previous waves, as was mentioned by TEC and De Lijn.

4.4.1. Short-term recovery

In terms of offer, all operators returned to a full offer between September 2020 and early 2021. Ridership, however, did not recover as promptly and is still (at the time of writing) below the pre-COVID baseline, as can be seen from Fig. 3. Only TEC estimates having reached 2019 occupancy rates in January 2022, but due to the low validation rates on vehicles, this is not yet reflected in their numbers. De Lijn and TEC both mentioned a significant increase in fraud since passengers were not allowed to board through the front of their vehicles. This fare evasions is also mentioned by Corazza et al. (2021), as a problem occurring mainly in Europe where it is common that the driver control passengers when they enter the vehicles. Interestingly, for NMBS the occupancy rates during the weekends in 2022 are recovering to pre-pandemic levels, although this is not yet the case for the weekdays. A similar effect can be seen in the occupancy rates of STIB. Both operators expect an increase in leisure travels using public transport in the coming years. This will be an important change from the pre-pandemic situation, where public transport was only used for leisure in 9 % of trips (see Fig. 2).

As a side effect of the pandemic, telework is expected to have an impact on ridership, but there are no plans yet within the operators to adapt their offer. STIB and De Lijn expect that there will be a decrease of 10 %–12 % in commuting trips, NMBS expects a 20 % decrease. Although currently the schedules of the operators will not be adapted, there is a close monitoring of the occupancy rates. STIB for example has noticed a slight decrease in ridership on Mondays and Fridays, and NMBS expects less pronounced differences between peak and off-peak hours. However, these differences are still too small to provide an offer that differs from other weekdays. This expected decline in peak hour commutes is similar to the findings of Marsden and Docherty (2021) in their interviews with expert policy makers. As a result of these current and expected evolutions, NMBS and TEC are already offering more flexibility in their subscriptions, while this is under discussion at De Lijn and STIB.

Interestingly, all but one (NMBS) stated that they would not be developing a contingency plan specifically for a future pandemic. Instead, they feel they can use the learnings (described below in section 4.4.3) that came out of COVID to handle a next potential crisis. As mentioned by STIB: “It would be great to have a specific scenario for every possible crisis, but the development and most importantly the update of these scenarios based on new information is too time- and resource-consuming.” Instead, the operator wishes to maintain this faster reaction time to scheduling issues that were experienced throughout the pandemic, and even decrease it to be more reactive in the future. Therefore, only NMBS are now developing a pandemic business continuity plan: “There are three key parts to the plan; first, a focus on governance and internal structure. Then, a focus and a close monitoring of absent personnel…. And then there is of course still general measures with regards to hygiene.”

It is also worth mentioning that none of the operators are revising planned infrastructural investments that were decided before the pandemic struck, which is in line with findings by Marsden and Docherty (2021). TEC even mentioned that, with funds from the EU’s recovery and resilience plan (European Commission, 2021), they planned additional infrastructure investments.

4.4.2. Long-term learnings

As stated by Coppola (2015), the recovery phase includes the learnings that have come out of the disaster. To increase resilience in the public transport sector, it is therefore important to analyse the learnings that have come out of the COVID-19 crisis. The importance of learnings and innovations has also been highlighted by the president of the WHO at the onset of the pandemic (WHO, 2020). When we asked the various operators for their main take-always, De Lijn, NMBS, and TEC all highlighted the experienced gained in identifying the right stakeholders to set up a dedicated task force. As TEC said: “We now have experience in setting up a working group, communications, etc.”. The operators stressed that this would be a considerable advantage to deal with a future crisis since less time would be lost in uncoordinated leadership. For NMBS, the only operator developing a business continuity plan specifically for pandemics, this is one of the key elements of the plan. A lack of coordinated command structures is a problem that often arises in the face of a disaster (Donahue and Tuohy, 2006), and therefore it is an important learning to include and transmit within an organization. In the face of a disaster, isolated decision-making can otherwise lead to less performance and lower efficiency levels of measures (Wankmüller, 2021). In addition to the identification of key stakeholders, De Lijn and NMBS highlighted the identification of key functions and the close follow-up of their absentee thresholds as an important learning. This also allows for more reactivity in the face of a disruption.

For STIB, the COVID-19 pandemic highlighted the importance of reliable and real-time data. From their point of view, reworking the scheduling offer in the face of a crisis and being reactive hinges on the ability to collect data much faster than is currently the case. As STIB said: “We need to gain in reactivity and be capable of reacting faster, so we do not need 100 different scenarios… If we need to rework our offer based on an external event, we need to understand what happened. We need to be able to collect more data much faster.”. More data, and data with an improved granularity is needed for better decision-making purposes, as real-time data collection can facilitate evidence-based decision making (UNDRR, & UNU-EHS, 2022). The issues with data collection and the right data formats in the case of disaster relief have similarly been pointed out by Kunz et al. (2017). Within the operator, there is now an effort ongoing to automate the collection and visualization of real-time occupancy rates in their app. STIB also stressed that COVID-19 can serve as a learning platform to increase reactivity, and that it can fast-track changes that were already underway (most notably in terms of more flexible ticketing systems).

TEC mentioned that they will be using the ‘pragmatic criteria’ experienced to deal with absent personnel throughout the COVID-19 crisis to update their contingency plan for strikes. The current strike plan, based on prioritized lines, is not practical enough, whereas the ‘pragmatic criteria’ allowed them to guarantee an offer as close to normal as possible despite the high levels of absent drivers.

Overall, all operators acknowledged that there are, and will be, other factors of uncertainties that can become the next disaster. In Belgium, although the pandemic was not yet over, important floods struck the country in July 2021, resulting in severe damage to both health and infrastructure (RTBF, 2021). However, De Lijn mentioned that the ability to put together a crisis team by knowing the right people to reach out to, allowed them to be more reactive to that natural disaster: “Because of COVID, I think we worked together better, and we used our internal structures more efficiently.”. This has also led the operator to develop a contingency plan specifically for climate change, as they expect that more disruptions caused by extreme weather events will take place in the future. During the floods, there was also a closer collaboration between operators, which De Lijn mentioned is necessary overall in a crisis situation. However, the interviewees also mentioned that this can be difficult to achieve in a crisis, since “we had no time to coordinate”. (STIB).

To conclude, recovery in terms of ridership across all operators is ongoing at the time of writing, but operators expect that the implementation of telework could have an impact on ridership. However, a shift towards an increased use of public transport for leisure can be noticed. In terms of learnings, except for NMBS, no operator expects the development of a contingency plan specifically for pandemic situations. Lastly, increased reactivity, through either the identification of stakeholders, or through better data availability, is an important learning for the future.

5. Concluding remarks

Around the world, the COVID-19 pandemic has had a severe impact on current lifestyles and disrupted all aspects of society. Public transport has not been an exception, with occupancy rates plummeting due to the measures aimed at stopping the spread of the virus. From a worldwide survey, it became apparent that the majority of cities did not have contingency plans in place for such a health crisis, leaving the sector vulnerable to the disruption caused by COVID-19 (Zhang, 2020).

The goal of our research was to analyze, through the disaster management framework, the reactions of the public transport operators in Belgium. In addition, we aimed to understand what learnings can be derived from the COVID-19 crisis in the public transport sector, in order to increase its resilience in the face of future crises. We did this by interviewing all four of the country’s public transport operators using the disaster management framework.

From our results, we see that no operator in Belgium was prepared for a pandemic before COVID-19, with no pandemic contingency plans at their disposal. However, all operators were able to use existing plans to face the effects of COVID-19 and keep operating. We saw that three out of the four operators reduced their offer through an adapted plan that prioritized some lines during the lockdown of spring 2020, and that one operator called upon pre-identified stakeholders to put together a crisis team. In terms of sanitary measures, all operators indicated having followed the ones imposed by the government, such as social distancing or the wearing of masks. In terms of response, we could see that, since COVID-19 was not a singular event, learnings from the response to a previous wave of the virus could already be implemented to face the next wave.

Overall, we see that ridership on public transport is only now, in early 2022, starting to recover for some operators, but that there are differences in how the commuter and the leisure segments are recovering. In terms of learnings, the operators highlighted the ability to quickly put together the right people when disaster strikes, as well as the importance of granular data, for indicators like absent drivers or ridership on different lines.

Although future pandemics are likely inevitable (Roche et al., 2020), it is probable that, in the future, we will experience other types of crises as well. One of the first ones that comes to mind is the climate change crisis that we are already facing, which will put the transport sector under pressure (Koetse and Rietveld, 2009). It is therefore key to develop resilience within transport and to be flexible in times of crises. This is reinforced by increasing complexity which exposes the transport systems to more disruptions (Wan et al., 2018).

When faced with disruptions, public transport systems need to be able to recover quickly, if they are to be considered an appropriate alternative to individual modes by travelers (Malandri et al., 2018). A first important aspect to increase resilience is the identification of the right people to be contacted and brought together in the case of a crisis in the stage of ‘preparedness’. As was shown by De Lijn, one of the operators interviewed, prior identification of the right stakeholders with the right competences and responsibilities enabled them to act quickly and to be reactive throughout the COVID-19 pandemic. However, the extent to which this exercise had been done was not sufficient for the scope of the pandemic, and so more work still needed to be done. This has become an important take-away from the crisis, which can be deployed in the future, as was also mentioned by NMBS and TEC.

Based on our results, we also suggest that the availability of real-time data for evidence-based decision making be incorporated into the first phases of the disaster management cycle for public transport operators. Evidence-based interventions are one of the best ways to develop transportation policies, and they require a thorough understanding of mobility patterns (Ahmad and Puppim de Oliveira, 2016).This could be done though a real-time information dashboard, showing not only the operator network, but also some key indicators for operations, like the number of workers present in crucial positions to keep operations running.

Lastly, we suggest the structural use of foresight within the management of public transport, through for example scenario planning. Although, as was mentioned by one of our interviewees, it is not possible to develop precise scenarios for all possible disruptions, a small set of robust scenarios ready to be deployed in times of crises could increase the resilience of public transport (Macharis et al., 2021).

Our research provides a broad understanding of the reactions of public transport operators in Belgium to COVID-19, as well as the learnings out of the crisis, based on semi-structured interviews with all four public transport operators. There are, however, some limitations to our work. First, it is important to mention that the profiles of the interviewees within each operator differed, which could have led to differing points of view on the crisis. Second, our research was carried out in a country where all public transport operators are public companies, which can provide a difference in the response to a crisis, since there was an obligation to continue to provide a service. Further research could replicate our analysis for other (European) countries to come to a more comprehensive view of the application of the disaster management framework within public transport operators in the context of COVID-19, to increase the resilience of the sector as a whole. Additionally, it could also be interesting to include a governmental perspective in the analysis.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Data availability statement

Restrictions apply on the availability of ridership data. They were made available by STIB-MIVB, TEC, De Lijn, and NMBS-SNCB respectively for the purpose of this paper only.

CRediT authorship contribution statement

Sara Tori: Conceptualization, Formal analysis, Writing – original draft, Writing – review & editing. Alice de Séjournet: Conceptualization, Formal analysis, Validation, Writing – original draft, Writing – review & editing. Cathy Macharis: Conceptualization, Validation, Writing – review & editing, Supervision.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

The authors wish to thank all interviewees from STIB-MIVB, TEC, De Lijn, and NMBS-SNCB for their participation in this research.

Footnotes

References

  1. Ahmad S., Puppim de Oliveira J.A. Determinants of urban mobility in India: Lessons for promoting sustainable and inclusive urban transportation in developing countries. Transp. Policy. 2016;50:106–114. doi: 10.1016/j.tranpol.2016.04.014. [DOI] [Google Scholar]
  2. Aloi A., Alonso B., Benavente J., Cordera R., Echániz E., González F., Ladisa C., Lezama-Romanelli R., López-Parra Á., Mazzei V., Perrucci L., Prieto-Quintana D., Rodríguez A., Sañudo R. Effects of the COVID-19 lockdown on urban mobility: empirical evidence from the city of Santander (Spain) Sustainability. 2020;12(9):3870. doi: 10.3390/su12093870. [DOI] [Google Scholar]
  3. Barriball K.L., While A. Collecting data using a semi-structured interview: A discussion paper. J. Adv. Nurs. 1994;19(2):328–335. doi: 10.1111/j.1365-2648.1994.tb01088.x. [DOI] [PubMed] [Google Scholar]
  4. Belgium.be. 2008a. Geographical description of Belgium | Belgium.be. https://www.belgium.be/en/about_belgium/country/geography.
  5. Belgium.be. 2008b. Public Transport | Belgium.be. https://www.belgium.be/en/mobility/public_transport.
  6. Belgium.be. 2022, March 4. Consultative Committee: Code yellow as of Monday 7 March. https://www.belgium.be/en/news/2022/consultative_committee_code_yellow_monday_7_march.
  7. Berdica K. An introduction to road vulnerability: What has been done, is done and should be done. Transp. Policy. 2002;11 [Google Scholar]
  8. Bruzz. 2020. Exitstrategie voor woon-werkverkeer: 40 kilometer extra fietspad. https://www.bruzz.be/mobiliteit/exitstrategie-voor-woon-werkverkeer-40-kilometer-extra-fietspad-2020-04-29.
  9. Camacho T., Foth M., Rakotonirainy A., Rittenbruch M., Bunker J. The role of passenger-centric innovation in the future of public transport. Public Transp. 2016;8(3):453–475. doi: 10.1007/s12469-016-0148-5. [DOI] [Google Scholar]
  10. Cole F.L. Content analysis: Process and application. Clin. Nurse Spec. 1988;2(1):53–57. doi: 10.1097/00002800-198800210-00025. [DOI] [PubMed] [Google Scholar]
  11. Coppola D.P. Third edition. Elsevier; 2015. Introduction to International Disaster Management. https://doi.org/10.1016/C2014-0-00128-1. [Google Scholar]
  12. Corazza M.V., Emberger G., Oszter V., Pejdo A., Shibayama T. COVID-19 containment measures and policies for sustainable transport: Present changes and future directions (Misure di contenimento del COVID-19 e politiche per il trasporto sostenibile: Mutazioni attuali e direzioni future) Ingegneria Ferroviaria. 2021;76(9):669–697. [Google Scholar]
  13. De Lijn. 2019. Jaarverslag 2019. https://static.delijn.be/Images/Jaarverslag%202019_tcm3-24741.pdf.
  14. de Séjournet A., Macharis C., Tori S., Vanhaverbeke L. Evolution of urban mobility behaviour in Brussels as a result of the COVID-19 pandemic. Reg. Sci. Policy Pract. 2022 doi: 10.1111/rsp3.12525. [DOI] [Google Scholar]
  15. Donahue A.K., Tuohy R.V. Lessons we Don’t learn: A study of the lessons of disasters, why we repeat them, and how we can learn them. Homeland Secur. Affairs. 2006;2(2):28. [Google Scholar]
  16. ECDC. 2020. Considerations for infection prevention and control measures on public transport in the context of COVID- 19.
  17. European Commission . European Commission; 2021. La Commission approuve le plan de la Belgique, doté d’une enveloppe de 5,9 milliards d’euros [Text]https://ec.europa.eu/commission/presscorner/detail/fr/ip_21_3147 [Google Scholar]
  18. Faulkner B. Towards a framework for tourism disaster management. Tour. Manag. 2001;22(2):135–147. doi: 10.1016/S0261-5177(00)00048-0. [DOI] [Google Scholar]
  19. Fletcher, K., Amarakoon, S., Haskell, J., Penn, P., Wilmoth, M., Matherly, D., Langdon, N. 2014. A guide for public transportation pandemic planning and response. Transp. Res. Board.
  20. FOD Mobiliteit en Vervoer. 2017. MONITOR. https://mobilit.belgium.be/nl/mobiliteit/mobiliteit_cijfers/enquetes_over_de_mobiliteit_van_de_belgen/monitor.
  21. Gkiotsalitis, K., Cats, O. 2021. Public transport planning adaption under the COVID-19 pandemic crisis: Literature review of research needs and directions. Transp. Rev., 41(3), 374–392. https://doi.org/10.1080/01441647.2020.1857886.
  22. Hao F., Xiao Q., Chon K. COVID-19 and China’s hotel industry: impacts, a disaster management framework, and post-pandemic agenda. Int. J. Hosp. Manag. 2020;90 doi: 10.1016/j.ijhm.2020.102636. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Hofinger G., Zinke R., Strohschneider S. Role-specific psychological requirements in preparing public transportation staff for disaster response. Disaster Prev. Manage. 2011;20(4):398–412. doi: 10.1108/09653561111161725. [DOI] [Google Scholar]
  24. Infrabel. 2016. Facts & Figures 2016. https://infrabel.be/sites/default/files/generated/files/report/facts_and_figures_2016_nl.pdf.
  25. Jiang F., Deng L., Zhang L., Cai Y., Cheung C.W., Xia Z. Review of the clinical characteristics of coronavirus disease 2019 (COVID-19) J. Gen. Intern. Med. 2020;35(5):1545–1549. doi: 10.1007/s11606-020-05762-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Kamga C., Eickemeyer P. Slowing the spread of COVID-19: Review of “Social distancing” interventions deployed by public transit in the United States and Canada. Transp. Policy. 2021;106:25–36. doi: 10.1016/j.tranpol.2021.03.014. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Koetse M.J., Rietveld P. The impact of climate change and weather on transport: An overview of empirical findings. Transp. Res. Part D: Transp. Environ. 2009;14(3):205–221. doi: 10.1016/j.trd.2008.12.004. [DOI] [Google Scholar]
  28. Kopsidas A., Milioti C., Kepaptsoglou K., Vlachogianni E.I. How did the COVID-19 pandemic impact traveler behavior toward public transport? The case of Athens, Greece. Transp. Lett.rs. 2021;13(5–6):344–352. doi: 10.1080/19427867.2021.1901029. [DOI] [Google Scholar]
  29. Kunz N., Van Wassenhove L.N., Besiou M., Hambye C., Kovács G. Relevance of humanitarian logistics research: Best practices and way forward. Int. J. Oper. Prod. Manag. 2017;37(11):1585–1599. doi: 10.1108/IJOPM-04-2016-0202. [DOI] [Google Scholar]
  30. Liu L., Miller H.J., Scheff J. The impacts of COVID-19 pandemic on public transit demand in the United States. PLoS One. 2020;15(11):e0242476. doi: 10.1371/journal.pone.0242476. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Macharis C., Tori S., de Séjournet A., Keseru I., Vanhaverbeke L. Can the COVID-19 crisis be a catalyst for transition to sustainable urban mobility? Assessment of the medium- and longer-term impact of the COVID-19 crisis on mobility in Brussels. Front. Sustain. 2021;2:64. doi: 10.3389/frsus.2021.725689. [DOI] [Google Scholar]
  32. Malandri C., Fonzone A., Cats O. Recovery time and propagation effects of passenger transport disruptions. Physica A. 2018;505:7–17. doi: 10.1016/j.physa.2018.03.028. [DOI] [Google Scholar]
  33. Marsden G., Docherty I. Insights on disruptions as opportunities for transport policy change. Transp. Res. A Policy Pract. 2013;51:46–55. doi: 10.1016/j.tra.2013.03.004. [DOI] [Google Scholar]
  34. Marsden G., Docherty I. Mega-disruptions and policy change: Lessons from the mobility sector in response to the Covid-19 pandemic in the UK. Transp. Policy. 2021;110:86–97. doi: 10.1016/j.tranpol.2021.05.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Qi Y., Liu J., Tao T., Zhao Q. Impacts of COVID-19 on public transit ridership. Int. J. Transp. Sci. Technol. 2021 doi: 10.1016/j.ijtst.2021.11.003. [DOI] [Google Scholar]
  36. Roche B., Garchitorena A., Guégan J., Arnal A., Roiz D., Morand S., Zambrana-Torrelio C., Suzán G., Daszak P. Was the COVID-19 pandemic avoidable? A call for a “solution-oriented” approach in pathogen evolutionary ecology to prevent future outbreaks. Ecol. Lett. 2020;23(11):1557–1560. doi: 10.1111/ele.13586. [DOI] [PubMed] [Google Scholar]
  37. RTBF . RTBF Info; 2016. Attentat à la station Maelbeek: Une vingtaine de morts, 130 blessés. https://www.rtbf.be/article/attentat-a-la-station-maelbeek-une-vingtaine-de-morts-130-blesses-9247879. [Google Scholar]
  38. RTBF . RTBF; 2021. La Belgique touchée par de fortes inondations ce 15 juillet: Le niveau de la Meuse grimpe, Namur et Liège en partie évacuées. https://www.rtbf.be/article/la-belgique-touchee-par-de-fortes-inondations-ce-15-juillet-le-niveau-de-la-meuse-grimpe-namur-et-liege-en-partie-evacuees-10804628. [Google Scholar]
  39. Sciensano. (2022). Confirmed cases by date, age, sex and province. COVID-19. https://epistat.wiv-isp.be/covid/.
  40. Statbel. (2021). Structure of the Population | Statbel. https://statbel.fgov.be/en/themes/population/structure-population#news.
  41. Stemler, S. (2000). An overview of content analysis. https://doi.org/10.7275/Z6FM-2E34.
  42. STIB. (2019). Activity report 2019. http://2019.stib-activityreports.brussels/en.
  43. TEC. (2019). Rapport d’activités 2019. http://rapportannuel.letec.be/2019/rapport/#le-tec-en-chiffres.
  44. Tirachini A., Cats O. COVID-19 and public transportation: current assessment, prospects, and research needs. J. Public Transp. 2020;22(1) doi: 10.5038/2375-0901.22.1.1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. UITP. 2020a. Management of COVID-19: Guidelines for public transport operators. https://cms.uitp.org/wp/wp-content/uploads/2020/06/Corona-Virus_EN.pdf.
  46. UITP. 2020b. Public transport authorities and COVID-19: Impact and response to a pandemic. https://www.lek.com/sites/default/files/PDFs/COVID19-public-transport-impacts.pdf.
  47. UNDRR, & UNU-EHS . UNDRR, UNU-EHS; 2022. Understanding and Managing Cascading and Systemic Risks-Lessons from COVID-19. https://www.undrr.org/publication/understanding-and-managing-cascading-and-systemic-risks-lessons-covid-19. [Google Scholar]
  48. Wan C., Yang Z., Zhang D., Yan X., Fan S. Resilience in transportation systems: A systematic review and future directions. Transp. Rev. 2018;38(4):479–498. doi: 10.1080/01441647.2017.1383532. [DOI] [Google Scholar]
  49. Wankmüller C. European disaster management in response to the COVID-19 pandemic. Mind Soc. 2021;20(1):165–170. doi: 10.1007/s11299-020-00252-2. [DOI] [Google Scholar]
  50. Weber, R. 1990. Basic Content analysis. SAGE Publications, Inc. https://doi.org/10.4135/9781412983488.
  51. WHO. 2020. WHO Director-General’s opening remarks at the media briefing on COVID-19. https://www.who.int/director-general/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19---11-march-2020.
  52. WHO. n.d.-a. Coronavirus disease (COVID-19) pandemic. Retrieved 28 April 2022, from https://www.euro.who.int/en/health-topics/health-emergencies/coronavirus-covid-19/novel-coronavirus-2019-ncov.
  53. WHO. n.d.-b. Swine flu I WHO emergency situation overview. Retrieved 19 April 2022, from https://www.who.int/emergencies/situations/influenza-a-(h1n1)-outbreak.
  54. Zhang J. Transport policymaking that accounts for COVID-19 and future public health threats: A PASS approach. Transp. Policy. 2020;99:405–418. doi: 10.1016/j.tranpol.2020.09.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Zhang J., Hayashi Y., Frank L.D. COVID-19 and transport: Findings from a world-wide expert survey. Transp. Policy. 2021;103:68–85. doi: 10.1016/j.tranpol.2021.01.011. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Restrictions apply on the availability of ridership data. They were made available by STIB-MIVB, TEC, De Lijn, and NMBS-SNCB respectively for the purpose of this paper only.

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