Next Article in Journal
Detection of Eccentricity in Conventional Grinding Wheels Using Acoustic Emission Signals and Counts Statistics During the Dressing Operation
Previous Article in Journal
(Electro)catalytic and Sensing Properties of Redox-Active Nanoparticles with Peroxidase-like Activity
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Proceeding Paper

Virtual Operation Support Team as a Tool for Threat Mapping and Improving Scenario Modeling in the Field of Road Critical Infrastructure †

Faculty of Safety Engineering, VSB—Technical University of Ostrava, Lumirova 13, 700 30 Ostrava, Czech Republic
*
Author to whom correspondence should be addressed.
Presented at the 5th International Conference on Advances in Environmental Engineering, Ostrava, Czech Republic, 26–28 November 2025.
Eng. Proc. 2025, 116(1), 33; https://doi.org/10.3390/engproc2025116033
Published: 9 December 2025

Abstract

Road critical infrastructure, especially bridges, is vulnerable to threats such as extreme weather, traffic overload, accidents, and natural disasters, which can compromise stability or operability. Timely mapping of these threats and modeling crisis scenarios are vital for resilience. This study explores how Virtual Operations Support Teams (VOSTs) can enhance threat mapping and scenario modeling. VOSTs collect real-time data (e.g., from social media and sensors) and produce digital maps and analyses to improve situational awareness. The study focuses on the types of data VOSTs gather and the resulting changes in mapping procedures and scenario parameters. The findings indicate that integrating VOST capabilities supports more effective crisis planning and response for road infrastructure management.

1. Introduction

Reliable road transport infrastructure represents not only a key prerequisite for economic development and the provision of essential services, but also an indispensable element for ensuring specific services during crisis situations [1]. In the dynamic environment in which road critical infrastructure operates, and with the increasing likelihood of cumulative phenomena associated with global industrialization challenges, the infrastructure is exposed to a wide range of threats. The most vulnerable components are bridges, which are uniformly subjected to common impacts such as extreme weather events, continuously increasing traffic intensity, uncontrolled overloading, and the mechanical or chemical effects of the environment. Depending on the location of the bridge, these factors are further compounded by accidents related to traffic operations and by the effects of natural disasters such as floods, earthquakes, or typhoons, all of which contribute to additional material fatigue [2].
Among the significant parameters influencing the effectiveness of crisis management are, in particular, the structural condition and material characteristics of road construction elements [3,4]. These factors are crucial for the operation of infrastructure under standard loading conditions; however, when addressing non-standard and crisis situations, they become limiting [5]. Threats affecting bridge structures can generally be understood as factors that either directly endanger the stability and load-bearing capacity of the bridge or significantly restrict its operability [6]. These circumstances highlight the necessity of mapping threats with potential impacts on critical infrastructure elements, including minor adverse events, and are closely linked to the targeted strengthening of resilience [7].
A proactive approach to these threats requires timely information about potential risks, on the basis of which appropriate measures can be designed to minimize their impacts. This enables the estimation of various scenario developments and the anticipated severity of their consequences, allowing for adequate responses already in the planning and design phases of protective measures. One approach to ensuring the timely provision of information is the use of VOSTs (Virtual Operations Support Teams). Their benefits include providing better situational awareness to decision-makers, thereby increasing their level of information and enabling them to adopt more appropriate measures and decisions [8]. Among the tasks of VOSTs are digital mapping of the situation and the execution of spatial analyses [9].
Beyond immediate situational awareness, many VOST practices already fuse verified, filtered social-media inputs with Geographic Information System (GIS) displays. Building on this, we outline an extended VOST-based framework that treats verified inputs as indicators for pattern detection, scenario parameterization, and early identification of triggers or escalation factors across all phases of crisis management. In road transport, this shifts VOSTs from passive monitoring to active threat mapping and decision support tailored to vulnerable bridges and corridors and strengthening resilience.
The efficiency of these teams can be leveraged, for example, to ensure safe and effective coordination of logistics operations, particularly in situations requiring the rapid deployment of heavy equipment (e.g., fire and rescue service units, military units, or civilian evacuations). Under such conditions, information on the condition and safety of road infrastructure is crucial for the timely and coordinated deployment of necessary resources [10].
The current state of the Czech road network in certain sections indicates long-term operation at the upper limit of capacity [11]. This points to limited reserves and the potential vulnerability of the transport network in dealing with extraordinary events. Titko [12] therefore emphasizes the need for comprehensive threat identification combined with vulnerability analysis of critical parts of the infrastructure, for which sufficient geographic data are not available for crisis management purposes, also in connection with Act No. 266/2025 [13]. One of the fundamental tasks of crisis management is the protection of the population [14]. It is therefore important to continue developing this area and thereby improve the population protection system. In the Czech Republic, specific provisions concerning VOSTs have not yet been established; legislation primarily addresses the functioning and composition of crisis staffs [15]. It is therefore necessary to focus on the possibilities of applying the VOST concept within the framework of crisis management of road infrastructure.
The aim is to identify how VOSTs can improve the processes of threat mapping and scenario modeling in road critical infrastructure. The focus is placed on the types of data that VOSTs collect and process, as well as on changes in mapping procedures and scenario parameterization.

2. Background and Materials

Road critical infrastructure represents a complex set of interconnected elements of the transport network. These are physical assets, particularly roads and bridges, whose functionality is strategically significant for public services as well as for crisis management; the disruption or failure of any of them may substantially limit the operation of dependent systems, such as the integrated rescue system or logistics [16]. With regard to the strategic linkages within the Trans-European Transport Network (TEN-T), there arises a need for systematic identification of weak points and targeted strengthening of interconnections [17].
Social media have a significant impact on crisis communication and emergency management. On this basis, the concept of Virtual Operations Support Teams (VOSTs) was developed, providing systematic collection, verification, and analysis of data from publicly available sources in real time. VOSTs can enhance decision-making awareness and support more effective coordination of crisis management entities [18]; its development, application, and contributions to crisis communication are described in detail by Alexander [19]. Although the benefits of VOSTs have been demonstrated abroad, the system is currently implemented in only a limited number of countries, and it is absent in the Czech Republic. This creates limitations for scenario modeling and for planning measures based on timely, verified field data.
Under conditions of limited data support, crisis management often relies on predefined operational regimes and standards. In certain emergency and tactical situations, such as the transport of vehicles across endangered sections, it may be necessary to temporarily modify standard criteria or apply less stringent safety limits. Strategic planning in the Czech Republic sets general frameworks but does not define the key factors. Here, the use of VOSTs presents an opportunity: continuous reporting on conditions, faster updates of map layers, and targeted supplementation of information on exposed elements can support scenario modeling and strengthen the resilience of the transport system.
In this sense, a VOST expands the data-collection framework and enhances both the efficiency and the safety of crisis management itself.

3. Framework for VOST Implementation

In preparing for crisis situations and protecting critical infrastructure, the law defines the powers of state authorities and territorial self-governing bodies, as well as the rights and obligations of legal and natural persons [20]. In the event of a crisis situation, and for the coordination of rescue operations, the Central Crisis Staff serves as its executive body. The composition of the Central Crisis Staff is regulated by its Statute, which is approved by the government [20]. At the regional level, this role is fulfilled by the Regional Crisis Staff, chaired by the regional governor. At the municipal level, the Crisis Staff of a municipality with extended powers operates, chaired by the mayor of the respective municipality. Current crisis management in the Czech Republic is based on a cyclical model comprising four fundamental, interconnected phases (Figure 1). Each phase—prevention, preparedness, response, and recovery—has its own specific tasks and instruments.
The aim of prevention is to avert the occurrence of extraordinary events or at least reduce the likelihood of their emergence. This phase includes risk analysis and assessment, the implementation of protective and safety measures, the education of both professionals and the general public, and other activities aimed at ensuring safety prior to the onset of a threat.
Preparedness consists in building capacities and conditions for the effective management of events that cannot be completely averted. This includes, for example, the development of crisis plans, professional training of personnel, provision of necessary equipment and materials, organization of exercises, and the establishment of a clearly defined system of management and communication during a crisis.
Within this framework, VOSTs can be operationalized as a structured information pipeline for road critical infrastructure. Digital volunteers and partner agencies monitor social media and open sources, verify and filter reports, and fuse the verified inputs with geoinformation systems. The extended framework then treats these verified inputs as indicators for pattern detection, scenario parameterization, and early identification of triggers or escalation factors across all phases of crisis management, with a strong emphasis on prevention. Outputs include digital mapping, spatial analyses, and decision support tailored to vulnerable bridges and corridors. The approach supports managerial decision-making and acknowledges interdependencies with supplier and contractor entities that sustain transport operations and logistics.
International practice confirms feasibility. In New Hampshire, authorities monitored social media to identify reported road closures. During the 2013 Calgary floods, VOST volunteers monitored platforms to support situational awareness and mapping. In France, Volontaires Internationaux en Soutien Opérationnel Virtuel (VISOV) operates under agreements with prefectures and the Ministry of the Interior to monitor social media and map incidents. In Germany, VOSTde within the Federal Agency for Technical Relief provides visualization support during floods. The extended framework proposed in this article enables these applications to be implemented and managed systematically: redistribution of traffic to alternative routes during disruptions, analysis of evacuation routes and procedures with subsequent integration into crisis plans, analysis of the origin and character of incidents to strengthen prevention, and evidence based design of flood measures and flood plans.
The proposed contribution advances beyond collection and verification. Verified inputs are exploited by indicator based methods to analyze patterns in the data and to derive reasoned deductions for planning. This shifts the VOST from passive monitoring to active threat mapping and scenario modeling for road transport. It strengthens resilience by enabling targeted crisis plans and variant decisions for bridge and corridor management.
The response phase begins immediately after the occurrence of an extraordinary event. Its aim is to limit the direct impacts of the situation and to protect lives, health, property, and the environment. The response phase includes the deployment of the integrated rescue system, the activation of crisis staffs, the provision of evacuation and emergency accommodation, as well as the implementation of necessary safety measures.
Recovery focuses on the return to normal functioning of society after the acute phase of a crisis has passed. It includes the repair and reconstruction of affected infrastructure, psychosocial and material assistance to the affected population, the restoration of essential services, as well as the evaluation of measures taken in order to improve future procedures.
The legislative framework of crisis management is currently undergoing significant changes. Based on the amendment to the Crisis Act and the related government decree, modifications are being introduced in the composition of crisis staffs. These changes will affect both the regional level and municipalities with extended powers (ORP): the existing permanent working groups will be abolished and replaced by newly established expert working groups within the crisis staff. These will consist primarily of specialized groups responsible for ensuring crisis communication as well as for situational analysis and prediction of further developments. At the same time, a new Act on Critical Infrastructure is being prepared, through which Directive (EU) 2022/2557 of the European Parliament and of the Council [17] on the resilience of critical entities is to be transposed into the Czech legal framework. This concept, together with the planned legislative revision, reflects the need to strengthen coordination and expert support for crisis management at all levels.
The creation of expert groups for situational analysis and forecasting aligns with VOST roles and workflows. VOST-generated, GIS-linked indicators can feed these groups with timely, verified information for planning, response coordination, and iterative updates to crisis plans. This institutional anchoring clarifies responsibilities, facilitates cooperation between public authorities and volunteer initiatives, and improves the practical use of VOST outputs in management processes.

3.1. The Role of VOSTs in Crisis Management

Virtual Operations Support Teams (VOSTs) expand the ability of staffs to rapidly acquire, filter, and validate information from open sources, to communicate flexibly, and to provide decision-making inputs in a standardized format. This also includes digital mapping and spatial analyses (e.g., thematic maps of affected areas, evacuation and access routes, flood zones), as well as the coordination of volunteers. For effective integration into the staff structure, it is necessary to clearly define responsibilities, communication channels, reporting frequency, escalation procedures, and standards for data quality and protection (including, for example, Responsible, Accountable, Consulted, Informed (RACI)).
Crowdsourcing refines the situational picture but carries risks of disinformation and noise. Therefore, it is advisable to introduce standardized collection forms, multi-stage source verification, and an auditable validation chain [21]. Social media serve both for obtaining situational information and for engaging in dialogue with the population; experience from the COVID-19 pandemic demonstrated the practical contribution of VOSTs to situational awareness and actionable information for decision-makers [22]. The teams consist of trained specialists with expertise in data processing, ethical and qualification requirements, and the use of modern tools and structured workflows [18].
VOSTs should be integrated into all phases of the crisis management cycle. In the prevention phase, it identifies trends and verifies weak signals; in preparedness, it develops scenarios and risk maps and tests communication channels; during the response phase, it ensures rapid information gathering and triage, supports decision-making, and coordinates communication with the public (including counter-disinformation activities); in recovery, it conducts process analysis, lessons learned, and mapping of damages and needs for systemic changes (Table 1).

3.2. Indicators and Metrics

Following the amendment to the Crisis Act, changes will be introduced in the composition of crisis staffs at both the regional level and at municipalities with extended powers. The permanent working group will be abolished and replaced by expert working groups within the crisis staff, in particular a group responsible for crisis communication and a group for situational analysis and prediction of further developments. At the same time, it is necessary to prepare a separate Act on Critical Infrastructure in order to transpose the requirements of Directive (EU) 2022/2557 of the European Parliament and of the Council [17] into the Czech legal framework. Another current issue is that no unified methodology or standardized procedure yet exists for VOSTs, defining its tasks and mode of operation.
According to Fathi et al. [22], the activities of VOSTs include, in particular, monitoring and collecting online information, filtering and evaluating it, and transmitting relevant findings to crisis authorities. They also encompass providing and sharing useful information with the public, crisis communication on social networks, and digital mapping or spatial analyses [23]. Further tasks of VOSTs involve transforming raw data into comprehensible information, rapid and intuitive visualization, and preparing inputs for decision-making. This includes, for example, creating thematic digital maps of affected areas supplemented with key data (such as flood zones or access routes) and coordinating volunteer cooperation at both national and international levels [24]. For the effective integration of VOSTs into the work of the crisis staff, it is necessary to define its competencies and ensure its management by the staff leadership, including the establishment of standards for data quality, validation processes, and subsequent decision-making procedures. These responsibilities should also be formally anchored, for instance, through the use of a RACI matrix.
Indicators represent a widely used tool for the early detection of potential disruptions to the resilience of critical elements and for the continuous assessment of both the current situation and the actual state of the environment. Monitoring the values of selected indicators over time makes it possible to estimate future developments and to adjust established measures in a timely manner. This group also includes the indicators described in the work of Řehák et al. [25]. In connection with the Critical Infrastructure Resilience Failure Indicators (CIRFI) framework, the indication of disruptions is carried out in several successive steps:
  • The assessed critical infrastructure element is selected and described in detail.
  • The element is classified into the appropriate category (group) of infrastructure elements.
  • The environment and domain for which the indicators will be defined are determined.
  • Specific indicators of the resilience disruption of the given element are identified.
  • For each indicator, a corresponding parameter is established to enable the measurement and evaluation of changes [26,27].
For better orientation in the technical domain of element resilience, the diagram of resilience area factors by Řehák et al. [25] can be used, providing an overview of the main technical factors influencing resilience (Figure 2).

3.3. Threats Affecting Bridge Structures

Threats affecting bridge structures can generally be defined as factors that either directly endanger the stability and load-bearing capacity of a bridge or limit its operability. In risk analysis and crisis management, it is essential to distinguish between disruption and failure. Disruption represents a temporary limitation of the functionality or operation of a given element, whereas failure denotes its complete removal from service [28]. An example of disruption may be the short-term flooding of access roads, while failure would correspond to extensive damage to the load-bearing structure requiring full restoration of the entire element.
Titko [12] emphasizes the need to conduct a comprehensive identification of threats in combination with a vulnerability analysis of critical parts of the structure. Such an approach ensures timely information about potential risks and makes it possible to propose appropriate measures to minimize their impacts, which helps to estimate possible scenarios, the anticipated severity of impacts, and to respond adequately already in the design phase. The analysis of identified threats then results in scenarios requiring specific structural and operational measures. The recorded threats affecting bridges can be divided into two basic categories (Figure 3).
Figure 3 schematically illustrates these two categories of threats. The first category includes threats affecting the load-bearing capacity of structural elements of the bridge; the second comprises threats that do not directly damage the load-bearing structures but limit the usability of the bridge (for example, by restricting access).
The first group consists of threats that generate extraordinary loading of the load-bearing parts of a bridge, thereby directly affecting the load capacity of structural elements. These include, for example, the effects of explosions, which can damage piers and the superstructure, initiating the formation of cracks or displacements of key elements from their positions [29]. Similar effects are caused by impacts of heavy vehicles or vessels, or by sudden landslides, where short-term but extreme forces act on a small area of the structure, inducing extraordinary stress at a localized point. Equally significant are natural phenomena such as extremely increased water flows, which undermine piers, cause erosion of abutments, or induce changes in foundation conditions [30]. In such situations, a radical reduction in the structural safety margin may occur, which in extreme cases can lead to a chain collapse [31]. The robustness of exposed parts of the bridge therefore directly influences the overall resilience of the bridge structure.
The second category consists of threats that do not directly damage the load-bearing structures but significantly limit the usability of the bridge. A typical example is flooding, when water submerges access roads or ramps and practically prevents passage across the bridge. A similar problem arises when it is necessary to transport oversized or over-dimensional loads exceeding the design parameters of the bridge. The bridge structure may be fully functional under normal conditions, yet in a crisis situation, when it is necessary to deploy specialized equipment, restrictions in clearance or insufficient load-bearing capacity can severely limit the usability of the bridge [24]. Precisely in moments of crisis events, the inoperability of key elements of road critical infrastructure may thus become a major obstacle in terms of the functionality and effectiveness of crisis management [32,33].
Structural and technical factors may, in specific situations, represent a major limitation to the usability of bridge structures, particularly when non-standard loading is required during crisis transport (e.g., the movement of heavy or oversized equipment). This corresponds with findings on increasing loads beyond standard design assumptions [34,35]. Insufficient robustness of certain bridge elements can significantly threaten the functionality of the entire infrastructure and prevent the effective management of specific crisis situations [36,37]. Conversely, transport infrastructure with sufficient reserves in design parameters can maintain key functions even under adverse conditions, thereby supporting the operational management of emerging events [33,38].

3.4. Vost Communication Protocols with the Crisis Staff

The Virtual Operations Support Team (VOST) provides added value to crisis management in the form of rapid information acquisition and distribution, flexible communication, and coordinated cooperation across the involved entities. The VOST strengthens system resilience through targeted data collection, verification, and transformation into comprehensible inputs for the decision-making of the crisis staff. For the effective use of a VOST, it is necessary to establish clear communication protocols that define responsibilities, communication channels, the format and frequency of reporting, escalation and approval procedures, as well as standards for data quality and protection.
Crowdsourcing expands the database with inputs from both experts and the general public, enabling faster and more detailed representation of situations in dynamically evolving events. Alongside these benefits, however, crowdsourcing also brings risks associated with disinformation and inaccurate data on social networks. It is therefore necessary to introduce standardized tools for information collection, multi-level source verification, a transparent validation process, and continuous monitoring of information quality. This minimizes the impact of erroneous or unverified data on the decision-making process.
Social media play a key role in crisis communication—they enable operational management, direct dialogue with the population, and rapid collection of inputs for situational reports [18]. In the literature, a VOST is described as a new form of organized information gathering for emergencies, which proved effective during the COVID-19 pandemic [22]. VOSTs are composed of trained specialists capable of working with data and preparing comprehensible outputs for decision-makers. Team members meet defined qualification and ethical requirements and use modern communication technologies as well as structured workflows [21]. Table 2 summarizes the advantages and limitations of traditional communication methods, social media, and VOSTs in crisis communication.
As part of the content analysis of communication outputs, conducted on the basis of the search parameter traffic accident, dominant thematic areas were identified (Figure 4). The majority of records concerned transport and logistics (12,522 records), followed by construction (7508 records) and information technology and communication (5347 records). Considerably fewer records in the dataset related to sports (4529 records), health and healthcare (2824 records), and culture and education (1925 records), with by far the lowest number recorded in the field of agriculture (1493 records).
Figure 5 shows the distribution of outputs by type of communication channel. The results of the analysis indicate that the majority of information was obtained from internet sources (68.0%, i.e., 32,281 records), while the shares of other communication channels were considerably lower—social media (11.6%, 5530 records), print (8.6%, 4067 records), radio (7.6%, 3613 records), and television (4.2%, 1997 records).

3.5. Network Metrics

Network metrics translate infrastructure topology and operations into measurable indicators and help to identify critical links, nodes, and corridors within the system; their outputs can be used by management to prioritize interventions, plan redundancy, and conduct operational traffic management. These metrics can be applied to the assessment of communication processes and data flows, monitoring, for example, network availability, density, and latency, or identifying key nodes of the information network. The insights gained are subsequently reflected in capacity management, resource prioritization, and the adjustment of communication protocols.
For the systematic assessment of road bridge resilience, multi-criteria analytical methods can also be employed. Shen et al. [44], for example, propose a framework using the fuzzy Analytic Hierarchy Process (fuzzy AHP) on an exponential scale. First, the structure of the assessed bridge is described in detail, with attention to its specific structural characteristics. The complex problem is then decomposed into hierarchical levels, and the relationships between criteria are quantified, on the basis of which the weights of individual factors are determined. This procedure creates a transparent foundation for multi-criteria decision-making and prioritization, both in maintenance and in crisis scenarios.
The need for new assessment methods also arises from the current development of standards in transport infrastructure. An analysis of the revision of Directive RiL 805 for the recalculation and assessment of railway bridges in Germany [45] demonstrates the legislative reasons for changing approaches—it is necessary to take into account safety as well as the impact of load combination factors. These findings support the introduction of approaches capable of integrating uncertainties, multi-component data, and dynamic operational conditions into a robust resilience assessment.
Table 3 below provides an overview of selected methods with potential for practical application in planning and operational management of crisis situations. The spectrum includes both standardized tools already implemented in practice (e.g., the Hazus methodology developed by federal emergency management agency (FEMA) for disaster loss estimation) and advanced analytical approaches from recent research. These include, for instance, travel time reliability analysis and the Planning Time Index (PTI) for detecting traffic anomalies, geoinformation approaches to identifying critical segments in the transport network, or methods for determining hydrologically sensitive road sections prone to flash floods. Further examples involve the use of Unmanned Aerial Vehicle (UAV) imaging and the calculation of the Pavement Condition Index (PCI) for accurate surface damage mapping, as well as multi-criteria pavement condition assessments for maintenance prioritization. The set also encompasses methods for detecting extraordinary events from city-wide Global Positioning System (GPS) data and corridor mobility analysis, which can provide real-time alerts on reduced throughput or emerging congestion.

4. Conclusions

Virtual Operations Support Teams (VOSTs) represent a significant contribution to the crisis management of road critical infrastructure, particularly bridge structures. VOSTs provide crisis managers with added value in the form of rapid information acquisition and distribution, flexible communication, and coordinated cooperation across the involved entities. Owing to these capabilities, decision-makers can gain a more comprehensive situational overview and adopt better-informed measures in a shorter time.
The results indicate that VOSTs play an indispensable role in all phases of the crisis cycle—from prevention through preparedness and response to recovery. In the prevention phase, such teams help to identify emerging threats in a timely manner and to verify “weak signals” of future risks; during preparedness, they contribute to scenario development, digital risk mapping, and the testing of communication channels; in the response phase, they ensure rapid collection, triage, and verification of information, actively support the decision-making of the crisis staff, and assist in coordinated communication with the public; and in the recovery phase, they contribute to event analysis (lessons learned) as well as to the mapping of damages and needs for strategic changes. These activities demonstrably enhance the situational awareness of all stakeholders and enable more effective management of extraordinary events.
The study further emphasized the benefits of using digital tools, mapping, and indicators for assessing infrastructure resilience. VOSTs routinely employ digital mapping and spatial analyses to visualize threatened areas, which facilitates the identification of critical points in the transport network. At the same time, key indicators were identified, the monitoring of which over time enables early detection of declining infrastructure resilience and continuous assessment of the current state of the environment. Continuous monitoring of these metrics supports the prediction of future developments and allows for real-time adjustment of established measures. The deployment of these digital tools and metrics thus enhances the overall capacity of the system to withstand disruptions and to respond swiftly to changing conditions.
In line with these findings, this article describes the possibility of extension and the capability for further data processing and use built on the currently established framework. Specifically, the extended VOST approach enables systematic implementation and management of redistribution of traffic to alternative routes during disruptions; analysis of evacuation routes and procedures with subsequent integration into crisis plans; analysis of the origin and character of incidents to strengthen prevention; and evidence-based design of flood measures and flood plans.
From the perspective of institutional anchoring, the need for legislative and methodological incorporation of the VOST concept has been identified. At present, there is no unified methodology or procedure defining the position, tasks, and mode of operation of VOSTs within the crisis management system. Likewise, the current legislation (e.g., the Crisis Act) does not explicitly mention these teams, focusing instead on traditional crisis staffs. Based on the findings, it is therefore necessary to develop official methodological guidelines and, if needed, legislative amendments that clearly define the competencies of VOSTs, standards for their data outputs, and mechanisms for their integration into crisis management structures. Such formal anchoring would ensure a unified framework for VOST activities across regions and organizations, increase the effectiveness of their deployment, and enable their full potential to be utilized in practice.

Author Contributions

Conceptualization, O.R.; methodology, O.R.; formal analysis, O.R.; investigation, O.R.; writing—original draft preparation, O.R.; writing—review and editing, P.G.; funding acquisition, P.G. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by VSB—Technical University of Ostrava, grant number SP2025/088.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on reasonable request from the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Patrman, D.; Splichalova, A.; Rehak, D.; Onderkova, V. Factors Influencing the Performance of Critical Land Transport Infrastructure Elements. Transp. Res. Procedia 2019, 40, 1518–1524. [Google Scholar] [CrossRef]
  2. Vlcek, P. Odvodnění Mostních Objektů: Pro Studijní Účely Vysoké Školy Báňské–Technické Univerzity Ostrava, Fakulta Stavební, Katedra Městského Inženýrství; Vysoká Škola Báňská–Technická Univerzita: Ostrava, Czech Republic, 2005; ISBN 80-248-0875-7. [Google Scholar]
  3. Loveček, T.; Straková, L.; Kampová, K. Modeling and Simulation as Tools to Increase the Protection of Critical Infrastructure and the Sustainability of the Provision of Essential Needs of Citizens. Sustainability 2021, 13, 5898. [Google Scholar] [CrossRef]
  4. Soman, R.K.; Molina-Solana, M.; Whyte, J.K. Linked-Data based Constraint-Checking (LDCC) to support look-ahead planning in construction. Autom. Constr. 2020, 120, 103369. [Google Scholar] [CrossRef]
  5. Pavlicek, J. Mosty: Stavba, Údržba, Rekonstrukce; Academia: Praha, Czech Republic, 2001. [Google Scholar]
  6. Ryska, O.; Janeckova, H. Impact of Parameters of Critical Road Infrastructure on Crisis Management. In Proceedings of the TRANSBALTICA XV: Transportation Science and Technology, Vilnius, Lithuania, 19–20 September 2024; pp. 579–588. [Google Scholar] [CrossRef]
  7. Rehak, D.; Splichalova, A.; Janeckova, H.; Ryska, O.; Oulehlova, A.; Michalcova, L.; Hromada, M.; Kontogeorgos, M.; Ristvej, J. Critical entities resilience strengthening tools to small-scale disasters. Int. J. Crit. Infrastruct. Prot. 2025, 49, 100766. [Google Scholar] [CrossRef]
  8. Fathi, R.; Fiedrich, F. Social Media Analytics by Virtual Operations Support Teams in Disaster Management: Situational Awareness and Actionable Information for Decision-Makers. Front. Earth Sci. 2022, 10, 941803. [Google Scholar] [CrossRef]
  9. Fathi, R.; Thom, D.; Koch, S.; Ertl, T.; Fiedrich, F. VOST: A case study in voluntary digital participation for collaborative emergency management. Inf. Process. Manag. 2020, 57, 102174. [Google Scholar] [CrossRef]
  10. Chen, H.; Cullinane, K.; Liu, N. Developing a model for measuring the resilience of a port-hinterland container transportation network. Transp. Res. Part E Logist. Transp. Rev. 2017, 97, 282–301. [Google Scholar] [CrossRef]
  11. Mendoza-Lugo, M.A.; Nogal, M.; Morales-Nápoles, O. Estimating bridge criticality due to extreme traffic loads in highway networks. Eng. Struct. 2023, 300, 117172. [Google Scholar] [CrossRef]
  12. Maris, L.; Zvakova, Z.; Kampova, K.; Lovecek, T. The Influence of Threat Development on the Failure of the System’s Symmetry. Systems 2021, 9, 74. [Google Scholar] [CrossRef]
  13. Parliament of the Czech Republic. Act No. 266/2025 Coll., on the Resilience of Critical Infrastructure Entities and Amendments to Related Acts (Critical Infrastructure Act); Collection of Laws of the Czech Republic: Prague, Czech Republic, 2025.
  14. Parliament of the Czech Republic. Act No. 239/2000 Coll., on the Integrated Rescue System and Amendments to Certain Acts; Collection of Laws of the Czech Republic: Prague, Czech Republic, 2000.
  15. Government of the Czech Republic. Government Regulation No. 462/2000 Coll., on the Participation Rules for Crisis Management Authorities; Collection of Laws of the Czech Republic: Prague, Czech Republic, 2000.
  16. Rehak, D.; Senovsky, P.; Slivkova, S. Resilience of Critical Infrastructure Elements and Its Main Factors. Systems 2018, 6, 21. [Google Scholar] [CrossRef]
  17. European Parliament. Regulation (EU) 2024/2557 on the Resilience of Critical Entities; Official Journal of the European Union: Brussels, Belgium, 2024. [Google Scholar]
  18. Roth, F.; Prior, T. Utility of Virtual Operation Support Teams: An International Survey. Aust. J. Emerg. Manag. 2019, 34, 53–59. [Google Scholar] [CrossRef]
  19. Alexander, D.E. Social Media in Disaster Risk Reduction and Crisis Management. Sci. Eng. Ethics 2013, 20, 717–733. [Google Scholar] [CrossRef]
  20. Parliament of the Czech Republic. Act No. 240/2000 Coll., on Crisis Management and Amendments to Certain Acts; Collection of Laws of the Czech Republic: Prague, Czech Republic, 2000.
  21. Veglis, A.; Panagiotou, N. Verifying Social Media Content in Crisis Reporting. In Proceedings of the EJTA Teachers Conference 2018, Thessaloniki, Greece, 18–19 October 2018. [Google Scholar]
  22. Paulus, D.; Fathi, R.; Fiedrich, F.; de Walle, B.V.; Comes, T. On the Interplay of Data and Cognitive Bias in Crisis Information Management. Inf. Syst. Front. 2024, 26, 391–415. [Google Scholar] [CrossRef]
  23. Fathi, R.; Schulte, Y.; Schütte, P.M.; Tondorf, V.; Fiedrich, F. Lageinformationen aus den sozialen Netzwerken: Virtual Operations Support Teams (VOST) international im Einsatz. Notfallvorsorge 2018, 49, 4–12. [Google Scholar]
  24. Müller, F.; Frings, N.; Kubitza, M.; Wielgosch, T.; Tomczyk, S.; Tutt, L.; Bach, S.; Fiedrich, F. VOST-Methodenhandbuch [Electronic Handbook]. In #Sosmap—Systematische Analyse der Kommunikation in Sozialen Medien zur Anfertigung Psychosozialer Lagebilder in Krisen und Katastrophen; Bundesamt für Bevölkerungsschutz und Katastrophenhilfe: Bonn, Germany, 2024; Available online: https://wiki.uni-wuppertal.de/!sosmap/ (accessed on 10 November 2025).
  25. Rehak, D.; Splichalova, A.; Hromada, M.; Lovecek, T.; Hlavaty, R. Využití Indikátorů v Ochraně Kritické Infrastruktury, 1st ed.; Sdružení Požárního a Bezpečnostního Inženýrství: Ostrava, Czech Republic, 2022; ISBN 978-80-7385-259-7. [Google Scholar]
  26. Rehak, D.; Hromada, M.; Ristvej, J. Indication of Critical Infrastructure Resilience Failure. In Proceedings of the Safety and Reliability—Theory and Applications: Proceedings of the 27th European Safety and Reliability Conference (ESREL 2017), Portorož, Slovenia, 18–22 June 2017; Čepin, M., Briš, R., Eds.; CRC Press/Balkema: Leiden, The Netherlands, 2017; pp. 963–970. [Google Scholar] [CrossRef]
  27. Rehak, D.; Splichalova, A. Application of Composite Indicator in Evaluation of Resilience in Critical Infrastructure System. In Proceedings of the 2022 IEEE International Carnahan Conference on Security Technology (ICCST), Valeč u Hrotovic, Czech Republic, 7–9 September 2022; pp. 1–6. [Google Scholar] [CrossRef]
  28. Rehak, D.; Patrman, D.; Foltin, P.; Dvořák, Z.; Skrickij, V. Negative Impacts from Disruption of Road Infrastructure Element Performance on Dependent Subsystems: Methodological Framework. Transport 2021, 36, 510–524. [Google Scholar] [CrossRef]
  29. Wardhana, K.; Hadipriono, F.C. Analysis of Recent Bridge Failures in the United States. J. Perform. Constr. Facil. 2003, 17, 144–150. [Google Scholar] [CrossRef]
  30. Yang, Z.; Barroca, B.; Bony-Dandrieux, A.; Dolidon, H. Resilience Indicator of Urban Transport Infrastructure: A Review on Current Approaches. Infrastructures 2022, 7, 33. [Google Scholar] [CrossRef]
  31. Mansour, D.M.M.; Moustafa, I.M.; Khalil, A.H.; Mahdi, H.A. An Assessment Model for Identifying Maintenance Priorities Strategy for Bridges. Ain Shams Eng. J. 2019, 10, 695–704. [Google Scholar] [CrossRef]
  32. Dvorak, Z.; Leitner, B.; Rehak, D. Critical Infrastructure Protection Specifications in the Transport Sector. MEST J. 2019, 7, 31–40. [Google Scholar] [CrossRef]
  33. Rehak, D.; Hromada, M.; Novotny, P. European Critical Infrastructure Risk and Safety Management: Directive Implementation in Practice. Chem. Eng. Trans. 2016, 48, 943–948. [Google Scholar] [CrossRef]
  34. Maňas, P.; Rotter, T. Vyhodnocení zatížitelnosti mostního provizória TMS podle norem NATO. In Krizové Stavy a Doprava; Institut Jana Pernera, o.p.s.: Lázně Bohdaneč, Czech Republic, 2006; ISBN 80-86530-27-2. [Google Scholar]
  35. Doming, L.C.P.; Vinaykumar, C.H. Comparison of Load Classification System across the World for Interoperability between Different Countries. Int. J. Eng. Res. Technol. 2021, 10, 610–613. [Google Scholar]
  36. Bruneau, M.; Chang, S.E.; Eguchi, R.T.; Lee, G.C.; O’Rourke, T.D.; Reinhorn, A.M.; Shinozuka, M.; Tierney, K.; Wallace, W.A.; von Winterfeldt, D. A Framework to Quantitatively Assess and Enhance the Seismic Resilience of Communities. Earthq. Spectra 2003, 19, 733–752. [Google Scholar] [CrossRef]
  37. Labaka, L.; Hernantes, J.; Sarriegi, J.M. A Holistic Framework for Building Critical Infrastructure Resilience. Technol. Forecast. Soc. Change 2016, 103, 21–33. [Google Scholar] [CrossRef]
  38. Besinovic, N.; Ferrari Nassar, R.; Szymula, C. Resilience Assessment of Railway Networks: Combining Infrastructure Restoration and Transport Management. Reliab. Eng. Syst. Saf. 2022, 224, 108538. [Google Scholar] [CrossRef]
  39. Janeckova, H.; Ryska, O. Smart City Resilience. Chem. Eng. Trans. 2024, 111, 139–144. [Google Scholar] [CrossRef]
  40. Hudson, P.; Hagedoorn, L.; Bubeck, P. Potential Linkages Between Social Capital, Flood Risk Perceptions, and Self-Efficacy. Int. J. Disaster Risk Sci. 2020, 11, 251–262. [Google Scholar] [CrossRef]
  41. Bier, M.; Fathi, R.; Stephan, C.; Kahl, A.; Fiedrich, F.; Fekete, A. Spontaneous Volunteers and the Flood Disaster 2021 in Germany: Development of Social Innovations in Flood Risk Management. J. Flood Risk Manag. 2025, 18, e12933. [Google Scholar] [CrossRef]
  42. Ali, A.S.; Afifi, S.; El Khateeb, S.; El Fayoumi, M.A.; ElHusseiny, O.M. Virtual Reality Simulation in Urban Design Processes: Comparative Workflow Assessment and Implementation Outcomes. Ain Shams Eng. J. 2025, 16, 103671. [Google Scholar] [CrossRef]
  43. Titko, M.; Havko, J.; Studena, J. Modelling Resilience of the Transport Critical Infrastructure Using Influence Diagrams. Communications 2020, 22, 102–118. [Google Scholar] [CrossRef]
  44. Nan, C.; Sansavini, G. A Quantitative Method for Assessing Resilience of Interdependent Infrastructures. Reliab. Eng. Syst. Saf. 2017, 157, 35–53. [Google Scholar] [CrossRef]
  45. Giudici, H.; Pérez-Fortes, A.P. How Recent Developments in Smart Road Technologies and Construction Materials Can Contribute to the Sustainability of Road Infrastructure. J. Infrastruct. Syst. 2022, 28, 02522002. [Google Scholar] [CrossRef]
  46. Gong, L.; Fan, W.D. Applying Travel-Time Reliability Measures in Identifying and Ranking Recurrent Freeway Bottlenecks at the Network Level. J. Transp. Eng. 2017, 143, 04017001. [Google Scholar] [CrossRef]
  47. Yuan, J.; Wang, H.; Fang, Y. Identification of Critical Links in Urban Road Network Based on GIS. Sustainability 2023, 15, 14841. [Google Scholar] [CrossRef]
  48. Jato-Espino, D.; Pathak, S. Geographic Location System for Identifying Urban Road Sections Sensitive to Runoff Accumulation. Hydrology 2021, 8, 72. [Google Scholar] [CrossRef]
  49. Elvik, R.; Sagberg, F.; Langeland, P.A. An Analysis of Factors Influencing Accidents on Road Bridges in Norway. Accid. Anal. Prev. 2019, 129, 1–6. [Google Scholar] [CrossRef]
  50. Budzynski, M.; Kustra, W.; Okraszewska, R.; Pyrchla, J. The Use of GIS Tools for Road Infrastructure Safety Management. E3S Web Conf. 2018, 26, 00009. [Google Scholar] [CrossRef]
  51. Toma, M.G.; Ungureanu, R.D.; Dicu, M. GIS, a Tool for Improving the Road Network Management. IOP Conf. Ser. Earth Environ. Sci. 2021, 664, 012103. [Google Scholar] [CrossRef]
  52. Rizky, A.M.; Zahra, A.A.; Astor, Y.; Fauzi, C. Road Maintenance Management Based on Geographic Information System (GIS). Int. J. Adv. Sci. Eng. Inf. Technol. 2023, 13, 2418–2426. [Google Scholar] [CrossRef]
  53. Donovan, B.; Work, D.B. Empirically Quantifying City-Scale Transportation System Resilience to Extreme Events. Transp. Res. Part C Emerg. Technol. 2017, 79, 333–346. [Google Scholar] [CrossRef]
  54. Banik, S.; Bullock, D.M.; Vanajakshi, L. Corridor Level Mobility Analysis Using GPS Data. Int. J. Intell. Transp. Syst. Res. 2019, 18, 204–218. [Google Scholar] [CrossRef]
  55. Almeida, M.C.; Telhado, M.J.; Morais, M.; Barreiro, J.; Lopes, R. Urban Resilience to Flooding: Triangulation of Methods for Hazard Identification in Urban Areas. Sustainability 2020, 12, 2227. [Google Scholar] [CrossRef]
Figure 1. Phases of Crisis Management.
Figure 1. Phases of Crisis Management.
Engproc 116 00033 g001
Figure 2. Factors determining the resilience of critical infrastructure elements.
Figure 2. Factors determining the resilience of critical infrastructure elements.
Engproc 116 00033 g002
Figure 3. Main threat areas determining the usability of bridge structures during emergencies.
Figure 3. Main threat areas determining the usability of bridge structures during emergencies.
Engproc 116 00033 g003
Figure 4. Overview of thematic areas of content analysis outputs and their frequency.
Figure 4. Overview of thematic areas of content analysis outputs and their frequency.
Engproc 116 00033 g004
Figure 5. Share of individual communication channels in the total number of content analysis outputs.
Figure 5. Share of individual communication channels in the total number of content analysis outputs.
Engproc 116 00033 g005
Table 1. Overview of Key Factors and Specific Roles of VOSTs in the Individual Phases of Crisis Management.
Table 1. Overview of Key Factors and Specific Roles of VOSTs in the Individual Phases of Crisis Management.
PhaseKey FactorsRoles of the Virtual Operations Support Team
PreventionAnticipation, detection, risk management, security measures, innovation processes, and educational and development processes.Timely identification of trends, verification of signals, and inputs for information campaigns and plan adjustments.
PreparednessCrisis preparedness, robustness, redundancy, material resources, financial resources, human resources, and recovery processes.Scenario development, digital risk maps, testing of communication channels, and training of both the public and crisis staffs.
ResponseResponsiveness, detection, security measures, human resources, material resources, and redundancy.Rapid collection and sorting of information, triage, support for staff decision-making, and coordinated communication with the public, including countering disinformation.
RecoveryRenewability, recovery processes, adaptability, financial resources, and innovation processes.Process analysis, evaluation of experiences (lessons learned), mapping of damages and needs, and proposals for systemic changes.
Table 2. Communication tools in crisis management.
Table 2. Communication tools in crisis management.
ToolAdvantagesDisadvantagesReference
Traditional methods (telephone, radio)Reliable, clear, and direct communicationLimited reach, slow response time[18,19,39]
Social media (Twitter, Facebook)Fast information, wide reach, real-time updatesRisk of disinformation, need for continuous monitoring[8,18,19,39,40]
VOSTs (virtual operations support teams)Effective coordination, real-time dataDependence on technologies, required sufficient digital literacy[22,41,42,43]
Table 3. Overview of selected methods for disruption indication and localization of vulnerable points in transport infrastructure.
Table 3. Overview of selected methods for disruption indication and localization of vulnerable points in transport infrastructure.
Title and AuthorObserved VariablesData InterpretationCharacteristics/Limitations
Hazus–FEMA’s methodology for estimating potential losses from disastersFlood depth/hazard intensity; object exposure; building typologyEstimation of physical and economic impacts, risk mapping, and prioritization of interventionsStandardized GIS framework for earthquake/flood/cyclone scenarios; output quality strongly depends on the quality of input data
Travel-time reliability & PTI [46]Speed; traffic flow; frequency of congestion; Planning Time Index (PTI)Identification of bottlenecks and anomalies in time and space on the transport networkRequires detailed operational data; indicates consequences of disruption, not the cause
Resilience-based identification of critical roads [45]Traffic flow; speed; density; network topology OpenStreetMap (OSM)/GISSimulation of outages and localization of segments with the highest impact on the networkThe network is often simplified due to computational demands; calibration to local operating conditions is necessary
GIS identification of critical links [47]Road density; accessibility; buffer zones; points of interest (POI)Identification of critical links in the road network based on spatial structureStatic view without real-time data; suitable for preliminary identification of weak points
Runoff-sensitive road sections [48]Total precipitation; surface runoff; digital terrain model; drainage capacityLocalization of segments sensitive to water accumulation during flash rainfallRequires high-quality elevation data and hydrological calibration; suitable for flash flood scenarios
Bridge accident factors [49]Accident data; bridge parameters; traffic intensityIdentification of bridges with above-average accident rates and risk characteristicsContext-specific method (developed for Norway); requires robust and consistent accident records
GIS safety management–roadway geometry [50]Road curvature; sequence of curves; GPS/ real-time kinematic (RTK) data; speedIdentification of segments with higher risk based on geometric parametersField data collection (e.g., using cameras and RTK) is demanding; however, it significantly improves the accuracy of risk assessment for segments
Multi-criteria pavement condition assessment [51]C1 flatness; C2 roughness; C3 bearing capacity; C4 surface degradationPrioritization of maintenance and indication of the most degraded road sectionsWorks as part of multi-criteria analysis ELimination Et Choix Traduisant la REalité (ELECTRE), does not provide a complete picture on its own; requires high-quality inventory data
UAV imagery + PCI for pavement management [52]Pavement Condition Index (PCI); heavy vehicle loading; CBRLocalization of pavement surface damage and proposal of repair prioritiesRequires the deployment of drones and favorable conditions for imaging; high data resolution significantly increases the accuracy of defect identification
City-scale resilience & event detection from GPS data [53]Travel times; speeds; deviations from expected valuesDetection of extraordinary events and evaluation of their impact on mobility at the city-wide scaleRequires a large volume of GPS data; risk of false alarms due to noise deviations
Corridor mobility analysis from GPS [54]Segmentation of the transport corridor; temporal profiles of travel timeIdentification of critical periods of mobility decline and detection of sections with significant delaysDependent on the availability and quality of GPS data; method suitable for operational traffic monitoring
Triangulation of flood risk methods [55]Hydrological data; topographic data; object exposure; infrastructureCombined flood risk indicators and identification of sensitive network sectionsIntegration-intensive method; its advantage is the synthesis of multiple data sources for a more robust identification of endangered sites
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Ryska, O.; Gamonova, P. Virtual Operation Support Team as a Tool for Threat Mapping and Improving Scenario Modeling in the Field of Road Critical Infrastructure. Eng. Proc. 2025, 116, 33. https://doi.org/10.3390/engproc2025116033

AMA Style

Ryska O, Gamonova P. Virtual Operation Support Team as a Tool for Threat Mapping and Improving Scenario Modeling in the Field of Road Critical Infrastructure. Engineering Proceedings. 2025; 116(1):33. https://doi.org/10.3390/engproc2025116033

Chicago/Turabian Style

Ryska, Ondrej, and Patricie Gamonova. 2025. "Virtual Operation Support Team as a Tool for Threat Mapping and Improving Scenario Modeling in the Field of Road Critical Infrastructure" Engineering Proceedings 116, no. 1: 33. https://doi.org/10.3390/engproc2025116033

APA Style

Ryska, O., & Gamonova, P. (2025). Virtual Operation Support Team as a Tool for Threat Mapping and Improving Scenario Modeling in the Field of Road Critical Infrastructure. Engineering Proceedings, 116(1), 33. https://doi.org/10.3390/engproc2025116033

Article Metrics

Back to TopTop