Human-computer interaction public place biological terrorism event risk analysis system and method

Abstract

The invention discloses a human-computer interaction public place bioterrorism event risk analysis system and method, and the method comprises the steps: S1, building a risk evolution simulation model which comprises a continuous space representing a public place; defining a proxy library of behaviors and attributes of the subject; the random distribution mode setting module is used for simulating the position distribution of the main body in the continuous space; constructing a distance-based network generation module; initializing a simulation module; s2, defining classification of key subjects and classification of non-key subjects in the risk evolution simulation model; and S3, inputting different parameters and conditions into the risk evolution simulation model by using a graphical user interface, further simulating different bioterrorism event scene simulation, collecting process and result data of a bioterrorism event in the simulation process, and analyzing and evaluating the process and result data. According to the method, the computer analog simulation technology is utilized, and the behaviors of different public places and different crowds in bioterrorism events can be quickly obtained through analog simulation.

Description

Technical Field

[0001] The present invention belongs to the technical field of bioterrorism risk analysis, and in particular relates to a human-computer interactive public place bioterrorism event risk analysis system and method. Background Art

[0002] In today's world, bioterrorism has become a worrying security threat. This type of attack involves the use of potent biological factors that are highly lethal or pathogenic to humans, commonly known as biological warfare agents. The use of these pathogens or toxins is intended to cause harm to humans through various means.

[0003] There are many ways to carry out biological terrorist attacks, including but not limited to contaminating food and water sources, carrying pathogens through mail, releasing pathogens through air conditioning systems, and releasing them in large public places such as stations, subways, and shopping malls where there are large crowds of people. In some cases, terrorists may even use airplanes to spread pathogens to achieve a wider spread effect. These attack methods are extremely concealed, making detection and prevention extremely difficult.

[0004] The characteristics of biological terrorist attacks are their concealment and delay, which makes them more difficult to be discovered and dealt with in a timely manner compared with other types of terrorist attacks. Such attacks not only lead to high morbidity and mortality, but also cause social chaos and panic among the people. Obviously, public bioterrorism incidents are an illegal act of spreading bioterrorism incidents in public places, which is extremely harmful to human society.

[0005] Due to the limited research methods for the spread of bioterrorist incidents in public places, there is an urgent need to design and develop a human-computer interactive public place bioterrorist incident risk analysis system and method. This system will use computer simulation technology to quickly simulate the behavior of different public places and different groups of people in bioterrorist incidents. Such systems and methods are extremely important because they can help humans better understand and predict the potential risks of bioterrorist attacks, so as to take effective prevention and response measures and reduce the harm of bioterrorist attacks to society and the public. In this way, the safety of public places can be improved to a certain extent, and the safety of people's lives and social stability can be guaranteed. Summary of the invention

[0006] The purpose of the present invention is to meet practical needs and provide a human-computer interactive public place bioterrorism incident risk analysis system and method, which uses computer simulation technology to quickly simulate the behaviors of different public places and different groups of people in bioterrorism incidents.

[0007] To achieve the above-mentioned invention object, the first object of the present invention is to provide a human-computer interactive method for risk analysis of bioterrorism incidents in public places, comprising the following steps:

[0008] S1. Building a risk evolution simulation model, the risk evolution simulation model includes:

[0009] a continuous space representing a public place;

[0010] An agent library that defines the behavior and properties of the subject;

[0011] A module for setting random distribution patterns to simulate the position distribution of the subject in continuous space;

[0012] Construct a distance-based network generation module;

[0013] Initialize the simulation module;

[0014] S2. defining the classification of key subjects and the classification of non-key subjects in the risk evolution simulation model;

[0015] S3. Use the graphical user interface to input different parameters and conditions into the risk evolution simulation model, and then simulate different bioterrorism incident scenarios. During the simulation process, collect the process and result data of the bioterrorism incident, and analyze and evaluate the process and result data of the bioterrorism incident.

[0016] Furthermore, the continuous space is a two-dimensional or three-dimensional structure.

[0017] Furthermore, the behavior and attributes of the subject include the subject's location distribution, state transition, and interaction rules.

[0018] Furthermore, the working process of the random distribution mode setting module is: firstly, the initial position of the subject in the continuous space is set, and then the random distribution algorithm is used to simulate the natural distribution of the crowd.

[0019] Furthermore, the working process of the network generation module is as follows: first, a connection rule between nodes is defined, and when the distance between two entities is less than a threshold, a connection is established between the two entities.

[0020] Furthermore, the classification of the key subjects includes normal activities, initial susceptible persons, initial infected persons, evacuated persons, isolated persons, exposed persons, final susceptible persons, final infected persons, and confirmed persons.

[0021] Furthermore, the classification of the non-critical subjects includes terrorist attackers, site managers, site staff, and health treatment personnel.

[0022] The second object of the present invention is to provide a human-computer interactive public place bioterrorism risk analysis system, comprising:

[0023] A risk evolution simulation model, wherein the risk evolution simulation model comprises:

[0024] a continuous space representing a public place;

[0025] An agent library that defines the behavior and properties of the subject;

[0026] A module for setting random distribution patterns to simulate the position distribution of the subject in continuous space;

[0027] Construct a distance-based network generation module;

[0028] Initialize the simulation module;

[0029] A crowd subject classification module, used to define the classification of key subjects and the classification of non-key subjects in the risk evolution simulation model;

[0030] The human-computer interaction module uses a graphical user interface to input different parameters and conditions into the risk evolution simulation model, thereby simulating different bioterrorism incident scenarios. During the simulation, the process and result data of bioterrorism incidents are collected, and the process and result data of bioterrorism incidents are analyzed and evaluated.

[0031] A third object of the present invention is to provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-mentioned human-computer interactive public place bioterrorism incident risk analysis method.

[0032] A fourth object of the present invention is to provide a computer program product, comprising a computer program, which, when executed by a processor, implements the above-mentioned human-computer interactive public place bioterrorism incident risk analysis method.

[0033] The advantages and positive effects of this application are:

[0034] The present invention uses computer simulation technology and human-computer interaction to quickly perform simulations, thereby obtaining behavioral responses when biological terrorist incidents occur in different public places and facing different groups of people. Specifically:

[0035] First, the present invention can achieve scientific risk management. Through the simulation of bioterrorism incidents in public places, the risk evolution process of bioterrorism incidents in public places can be scientifically analyzed and predicted, thereby improving the foresight and pertinence of risk management. This enables decision makers to more accurately assess potential risks and formulate more effective preventive measures.

[0036] Secondly, the present invention can optimize the response strategy. Through simulation experiments, different response strategies can be tested to help decision makers choose the most effective emergency response plan. In this way, when a bioterrorism incident occurs, the most appropriate measures can be taken quickly, thereby improving the efficiency and effectiveness of responding to bioterrorism incidents.

[0037] Thirdly, the present invention can improve the speed of emergency response. Through the simulation model, the emergency response process can be pre-set, and once a bioterrorism incident occurs, the emergency plan can be quickly activated to reduce decision-making delays. This enables the emergency response team to respond in the shortest possible time and minimize the losses caused by the incident.

[0038] In addition, the present invention can reduce actual losses. By simulating and optimizing the emergency response process in advance, casualties and property losses can be reduced when a real bioterrorism incident occurs. This not only protects the lives and safety of the public, but also reduces the loss of social resources.

[0039] Finally, the present invention can enhance the resilience of the system. Through continuous simulation and improvement, the resilience and adaptability of the public place management system in the face of bioterrorism events can be enhanced. This enables the public place management system to better respond to various emergencies and improve the overall safety level.

[0040] In conclusion, the present invention can not only improve the ability to respond to bioterrorism incidents by providing a simulation platform based on human-computer interaction, but also promote the development of social security and public health management on a broader level. Through this technical means, the public's safety can be better protected, the overall response capability of society can be improved, and strong support can be provided for building a safer and more harmonious social environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0042] Figure 1 A flow chart provided by a preferred embodiment of the present invention is shown;

[0043] Figure 2 It shows a passenger subject behavior state transition rule diagram in a preferred embodiment of the present invention;

[0044] Figure 3 The behavior state change of the passenger subject in the preferred embodiment of the present invention is shown;

[0045] Figure 4The human-computer interaction interface of the risk evolution simulation model in the preferred embodiment of the present invention is shown;

[0046] Figure 5 The figure shows the three-stage risk evolution result diagram in the preferred embodiment of the present invention. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] See also Figures 1 to 5 ;

[0049] The present invention provides a human-computer interactive public place bioterrorism incident risk analysis method, which is carried out according to the idea of ​​theoretical analysis of event risk evolution process, risk subject identification, and risk evolution simulation, and includes the following steps:

[0050] The first step is to study the risk evolution of bioterrorism incidents in public places in depth, so as to clearly identify the key stages of bioterrorism incidents, such as risk origin, risk outbreak, risk spread and risk handling. This process involves a comprehensive analysis of the incident from the initial stage to the final resolution, ensuring that the development path of bioterrorism incidents in public places can be understood and predicted.

[0051] In the second step, by identifying the key risk subjects in bioterrorism incidents in public places, the main risk subjects involved can be determined, including terrorist attackers, venue managers, venue staff, health treatment personnel, and the general population. A detailed analysis of the behavioral characteristics, response patterns, and interaction relationships of each type of subject will help to build a more realistic and accurate simulation model. Such a model can truly reflect the role and influence of each subject in a bioterrorism incident, thereby providing a scientific basis for formulating effective response strategies.

[0052] The third step is to build a multi-agent simulation model of the risk evolution of bioterrorism incidents in public places. In this step, AnyLogic simulation software will be used to create a simulation environment that includes the above risk subjects. This includes the construction of a microscopic public place simulation environment, the distribution pattern of subjects in space, the programming of subject behavior rules, etc. Finally, the incident warning and response mechanisms will be integrated to simulate the entire process from risk origin to risk treatment, ensuring that the various risks brought about by bioterrorism incidents can be comprehensively assessed and addressed.

[0053] 1.1 Analysis of the evolution of bioterrorism risk in public places

[0054] When a bioterrorism incident occurs in a public place, the risk evolution process usually includes the following stages:

[0055] Phase 1: Triggering an alarm. This phase is the starting point of the emergency response to a bioterrorism incident. It usually involves the identification and reporting of suspicious events, such as the discovery of unexplained physical discomfort symptoms, abnormal behavior activities, or the detection of potential biological threat factors. At this point, relevant departments and professionals need to quickly assess the situation, confirm whether it is a bioterrorism incident, and initiate emergency response plans.

[0056] Phase 2: Preliminary Disposal. After a bioterrorism incident is confirmed, the preliminary disposal phase is immediately entered. The key to this phase is to quickly control the scope of the incident and prevent the further spread of the pathogen. This may include blocking the site, isolating the affected area, launching a monitoring and tracking system, and screening and isolating people who may have been exposed to the pathogen.

[0057] Phase 3: Triage and rescue. This phase focuses on triage and treatment of victims. The health rescue team will triage the victims, give priority to critically ill patients, and provide necessary medical assistance, such as vaccinations and drug treatments.

[0058] 1.2 Identification of risk subjects of bioterrorism incidents in public places

[0059] Through the expert questionnaire survey, the risk stakeholders in the evolution of bioterrorism risk in public places can be identified. When a bioterrorism incident occurs in a certain micro-public place, the risk stakeholders mainly include the following categories:

[0060] (1) Terrorist attackers: The main responsibility of this type of subject is to create terrorist attacks, thereby triggering the entire risk evolution process. They may use various means, such as releasing biological agents, to achieve their terrorist purposes.

[0061] (2) Venue managers: As decision-makers in public places, venue managers are responsible for making key decisions in emergency situations and directing venue staff to take action. They need to quickly assess the situation, develop response measures, and ensure timely delivery of information.

[0062] (3) Site staff: Responsible for the effective evacuation and isolation of the general population in an emergency to reduce harm and control the spread of risks. They need to receive professional training so that they can guide the evacuation of the crowd quickly and orderly when a crisis occurs.

[0063] (4) Medical personnel: After a bioterrorism incident, medical personnel are responsible for providing timely medical assistance to the affected general population. They need to have professional medical knowledge and skills to provide effective treatment and support to victims.

[0064] Through the above steps and analysis, we can better understand and respond to the risks posed by bioterrorism incidents in public places, thereby providing stronger protection for public safety.

[0065] The first embodiment is a human-computer interactive method for risk analysis of bioterrorism incidents in public places, which mainly includes:

[0066] S1. Building a risk evolution simulation model, the risk evolution simulation model includes:

[0067] a continuous space representing a public place;

[0068] An agent library that defines the behavior and properties of the subject;

[0069] A module for setting random distribution patterns to simulate the position distribution of the subject in continuous space;

[0070] Construct a distance-based network generation module;

[0071] Initialize the simulation module;

[0072] In this example, AnyLogic software was used to build an Agent-Based Modeling (ABM) simulation model for the risk evolution of bioterrorism incidents in public places. AnyLogic software provided a comprehensive modeling and simulation development environment for the simulation construction of this example, enabling this example to effectively define and implement the risk evolution simulation model environment.

[0073] First, this example defines a risk evolution simulation model environment. In the AnyLogic simulation model environment, this example creates a microscopic public place simulation environment, which is designed to simulate people's daily activities and interactions in public places. In this simulation environment, the subjects of this example are the general population in public places, such as passengers in the subway, spectators in the stadium, and visitors to other public places. In order to more accurately simulate the natural gathering and dispersion of people in the real world, this example determines the position of these subjects in the continuous space through a random distribution pattern.

[0074] In order to more realistically reflect the distribution and interaction of people in public places, this embodiment uses a distance-based network to simulate the connection between people. In this network, each subject can be regarded as a node, and the connection between nodes is determined based on the distance between them. When the distance between two nodes is less than a preset threshold, the two nodes will be connected to each other to form a network. This distance-based network construction method can effectively simulate the interaction and connection between people.

[0075] Specifically, in AnyLogic software, this embodiment implements this environment definition through the following steps:

[0076] (1) Creating a continuous space: This embodiment uses the AnyLogic space library to create a two-dimensional or three-dimensional continuous space to represent a public place. This continuous space provides a basic physical environment for the simulation model of this embodiment.

[0077] (2) Define the subject: This example uses AnyLogic’s agent library to define the behavior and properties of the subject. These properties include their location distribution, state transitions, interaction rules, etc. By defining these properties in detail, this example can more accurately simulate the behavior of the subject in public places.

[0078] (3) Random distribution mode: This embodiment sets the initial position of the subject in the continuous space and uses a random distribution algorithm to simulate the natural distribution of the crowd. This random distribution algorithm can help this embodiment more realistically reproduce the gathering and dispersion of the crowd in public places.

[0079] (4) Constructing a distance-based network: This embodiment defines the connection rules between nodes. When the distance between two entities is less than a certain threshold, a connection is established between them. This distance-based network construction method can effectively simulate the interaction and connection between people.

[0080] (5) Initialize simulation: Before the simulation starts, this embodiment initializes the subject's location and network connection according to the defined rules. Through this initialization process, this embodiment ensures that the simulation model can reflect a real crowd distribution and interaction state at the beginning.

[0081] Through these steps, this embodiment successfully built a simulation model that can simulate crowd behavior and interaction in public places. This model provides a solid foundation for this embodiment to further study the risk evolution of bioterrorism incidents, allowing this embodiment to better understand and predict crowd behavior and risk evolution trends when similar incidents occur.

[0082] S2. Define the classification of key subjects and non-key subjects in the risk evolution simulation model; specifically:

[0083] In studying the risk evolution of bioterrorist attacks in public places, we found that the general population in the place is the most affected key subject. Therefore, in the present invention, an agent-based model (ABM) is first constructed, in which the key subject is the individual general population, that is, the node in the distance-based network. These general population individuals influence each other through social interaction and message transmission with other risk stakeholders to adapt to changes in the environment. Other risk stakeholder subjects influence the crowd through message transmission, with their social interaction as the background. These general public subjects also interact with each other to adapt to changes in the environment.

[0084] The SEIJR model is developed based on the classic SEIR model. It takes into account the confirmed cases and subdivides the population into five types: susceptible (S), latent (E), infected (I), confirmed (J) and recovered (R). Susceptible (S) refers to those who have not been infected but lack immunity and are easily infected after contact with infected people; infected (I) refers to those who have been infected and are contagious but may not have been diagnosed; confirmed (J) refers to those who have been infected and diagnosed with the disease and will not infect others due to forced isolation.

[0085] From the perspective of emergency management, this paper draws on the classification of people in the SEIJR model during disease transmission, and defines 10 states of the general population in a bioterrorism attack in a public place: normal activity, susceptible (initial), infected (initial), evacuated, isolated, exposed, susceptible (final), infected (final), and confirmed. The specific states are defined as follows:

[0086] (1) During the normal operating hours of public places, the general public is in a normal activity state. They are in a "normal activity" state in public places, such as walking, shopping, or watching performances, which is also their initial state.

[0087] (2) When terrorists enter public places and release bioterrorism threat factors, the source of infection of bioterrorism threat appears in public places. At this time, most of the general population in public places are exposed to the environment that may be infected, becoming the main body of the "susceptible (initial)" state, and a certain proportion of people are directly infected due to direct contact with the source of infection personnel / agents, becoming "infected (initial)".

[0088] (3) Passengers in the "Infected (Initial)" state come into contact with other passengers in the "Susceptible (Initial)" state who are connected to them in a network at a certain rate. The susceptible passengers they come into contact with are infected with a certain probability and become passengers in the "Susceptible (Initial)" state.

[0089] (4) After the site operator identifies the occurrence of a bioterrorism attack, it will take measures to control the further expansion of the situation. Due to the infectiousness of bioterrorism threats, site managers usually conduct classified control on the general population. After the site manager makes a key decision and issues an evacuation or quarantine order to the site staff, the site manager begins to take action to quarantine the high-risk population that has been infected / is very likely to be infected to prevent the further expansion of the source of infection; evacuate the low-risk population that is less likely to be infected to block the transmission path between the source of infection and the susceptible population. Therefore, at this time, the general population is in two possible states: "evacuated" or "quarantined."

[0090] Health care workers triage the evacuated / isolated general population, and the general population has two possible health states: infected and uninfected. Therefore, after the implementation of control measures and triage, the general population will eventually be in four possible states: uninfected & evacuated, infected & evacuated, uninfected & isolated, infected & isolated. Since the accuracy of control / evacuation may not always reach 100%, there may be infected people among the evacuated population, and there may be uninfected people among the isolated population. Therefore, the uninfected people in the evacuated population are in the "susceptible" state, and the infected people can infect these susceptible people and are in the "infected" state; the isolated infected people are in the "confirmed" state under control, and the isolated uninfected people may contact them and are in the "exposed" state. As shown in Table 1 below. .

[0091] Table 1 shows the classification of the general population

[0092] Not infected Infect Evacuated Susceptible Infected Isolation Exposed Confirmed

[0093] In the process of building a risk evolution simulation model, it is necessary to define other risk subjects in the model in detail and set specific behavioral rules for each subject. Such a setting can ensure that our simulation model can fully and accurately simulate the complexity of the risk evolution process when a bioterrorism incident occurs in a public place. In addition to the main subject of the general population, it is also necessary to pay attention to several other key risk subjects, namely terrorist attackers, site managers, site staff, and health treatment personnel. Next, the behavioral rules of these four types of personnel will be elaborated in detail:

[0094] (1) Terrorists: The main responsibility of this type of subject is to create terrorist attacks, thereby triggering the start of the entire risk evolution process. In the initial stage of the simulation model, terrorists are in a "waiting" state. They will hide in a corner of a public place and patiently wait for the best time to launch an attack. When the hidden countdown ends, the terrorists will carry out their attacks, thus triggering a series of risk evolution events.

[0095] (2) Venue managers: As decision-makers in public places, venue managers play a vital role in the simulation model. They are responsible for making key decisions in emergency situations and guiding venue staff to take appropriate actions. Venue managers are initially in an "idle" state. They will monitor the routine operations of public places to ensure that everything is going smoothly. Once they receive news that terrorists have launched an attack, managers will immediately enter the "decision-making" state. They will quickly assess the current situation and develop appropriate response strategies. After the decision is made, managers will issue advance disposal instructions such as evacuation and isolation to venue staff in order to minimize the damage caused by the terrorist attack.

[0096] (3) Site staff: In the simulation model, site staff are responsible for effectively evacuating and isolating the general population in an emergency to reduce harm and control the spread of risk. Site staff are initially in an "idle" state, and they are always ready to respond to emergencies. After receiving instructions from the site manager, site staff will enter the "action" state, and they will quickly prepare to perform evacuation and isolation tasks. When starting to guide the crowd, site staff will issue clear guidance instructions to the crowd to ensure that the crowd can be evacuated or isolated safely and orderly, thereby effectively reducing risks.

[0097] (4) Medical personnel: After a bioterrorism incident, medical personnel play a vital role in the simulation model. They are responsible for providing timely medical assistance to the affected general population to reduce the damage caused by the terrorist attack. Medical personnel are initially in an "idle" state, and they will be on standby to respond to emergency medical needs. After receiving a call for help from the venue, medical personnel will quickly assess the situation and rush to the scene as soon as possible. After arriving at the public place, medical personnel will immediately triage the general population in the venue and provide appropriate treatment according to the severity of the injury, in order to save lives and reduce injuries to the greatest extent possible.

[0098] Table 2 shows the impact of other risk stakeholders on key entities

[0099]

[0100] Through the above detailed definitions and setting of behavioral rules, the risk evolution simulation model of the present application can more comprehensively and accurately simulate the complexity of the risk evolution process when a bioterrorism incident occurs in a public place, thereby providing decision makers with a more scientific and effective response strategy.

[0101] S3. When performing human-computer interaction operations on the risk evolution simulation model, users can interact with the model through a graphical user interface (GUI). Through this interface, users can input various parameters and conditions to simulate various bioterrorism incident scenarios. The design of this simulation model allows users to flexibly control and adjust the simulation environment to adapt to various needs and scenarios.

[0102] During the simulation, the system automatically collects detailed process and outcome data about the bioterrorism incident. This data includes the development process of the incident, the scope of impact, the number of people affected, and other relevant statistical information. By analyzing and evaluating this data, the system can provide in-depth insights to help users understand the impact of different decisions and actions on the evolution of the incident.

[0103] In addition, the simulation model can also provide detailed analysis results and evaluation reports, which include not only the statistical data of the event, but also the qualitative analysis of the impact of the event. Through these analyses and evaluations, users can better understand the risk factors and potential threats of bioterrorism events, and thus develop more effective response strategies.

[0104] Ultimately, the simulation model in this application is intended to help users improve their risk response strategies for bioterrorism incidents in public places. By simulating different bioterrorism incident scenarios and conducting detailed analysis and evaluation of these scenarios, users can better prepare and respond to similar incidents that may occur in the future. This simulation model not only improves users' awareness of the risks of bioterrorism incidents, but also provides a scientific basis for formulating effective response measures.

[0105] The second embodiment is a human-computer interactive public place bioterrorism incident risk analysis system, which is used to implement the method of the first embodiment, including:

[0106] A risk evolution simulation model, wherein the risk evolution simulation model comprises:

[0107] a continuous space representing a public place;

[0108] An agent library that defines the behavior and properties of the subject;

[0109] A module for setting random distribution patterns to simulate the position distribution of the subject in continuous space;

[0110] Construct a distance-based network generation module;

[0111] Initialize the simulation module;

[0112] A crowd subject classification module, used to define the classification of key subjects and the classification of non-key subjects in the risk evolution simulation model;

[0113] The human-computer interaction module uses a graphical user interface to input different parameters and conditions into the risk evolution simulation model, thereby simulating different bioterrorism incident scenarios. During the simulation, the process and result data of bioterrorism incidents are collected, and the process and result data of bioterrorism incidents are analyzed and evaluated.

[0114] A third embodiment is a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-mentioned human-computer interactive method for analyzing the risk of bioterrorism incidents in public places.

[0115] A fourth embodiment is a computer program product, comprising a computer program, which, when executed by a processor, implements the above-mentioned human-computer interactive method for analyzing the risk of bioterrorism incidents in public places.

[0116] Implementation case: In modern society, subways, as an important part of urban public transportation, carry the daily travel needs of a large number of passengers. However, due to its high density of people and closed environment, subway stations have also become potential targets for bioterrorist attacks. In order to cope with this threat, subway station operators and managers must establish a complete emergency response mechanism to ensure that measures can be taken quickly and effectively in the event of a bioterrorist incident to minimize losses and impacts.

[0117] First, the starting point of a bioterrorism incident must be identified. This usually involves the identification and reporting of suspicious events, such as the discovery of unexplained physical discomfort symptoms in passengers, the observation of abnormal passenger behavior, or the detection of potential biological threat factors. In this case, subway station operators and managers need to quickly assess the situation, confirm whether it is a bioterrorism incident, and immediately initiate emergency response plans.

[0118] Once a bioterrorism incident is confirmed, the subway station will quickly enter the preliminary disposal phase. The core task of this phase is to quickly control the scope of the incident and prevent the further spread of pathogens. This may include blocking the subway station site, isolating the affected area in the station, activating the monitoring and tracking system, and evacuating and isolating passengers and station staff who may have been exposed to the pathogen.

[0119] During the triage and rescue phase, the health rescue team will focus on triage and treatment of the victims. They will classify the victims according to their injuries, give priority to the seriously ill patients, and provide necessary medical assistance, such as vaccinations and drug treatments.

[0120] In order to better understand and respond to the risks of bioterrorism incidents in subway stations, this case identified the relevant subjects in the risk evolution through an expert questionnaire survey. When a bioterrorism incident occurs in a subway station, the risk stakeholders mainly include the following categories:

[0121] 1. Terrorist attackers: The main responsibility of this type of entity is to create terrorist attacks, thereby triggering the entire risk evolution process.

[0122] 2. Metro Station Operator Leader: As the decision-maker of the metro station, the metro station operator leader is responsible for making key decisions in emergency situations and guiding metro station staff to take actions.

[0123] 3. Subway station staff: responsible for the effective evacuation and isolation of passengers in emergency situations to reduce injuries and control the spread of risks.

[0124] 4. Medical treatment personnel: After a bioterrorism incident occurs, medical treatment personnel are responsible for providing timely medical assistance to affected passengers.

[0125] In order to simulate and analyze the risk evolution of a bioterrorism incident in a subway station, we built an ABM (Agent-Based Modeling) simulation model using AnyLogic software. The software provides a complete modeling and simulation development environment for agent-based simulation construction.

[0126] In the simulation model environment definition stage, this case first created a two-dimensional continuous space of 500 meters × 500 meters to represent the actual environment of the subway station. Then, 500 passenger subjects were defined, and the positions of these passengers in the two-dimensional continuous space were determined by random distribution patterns to simulate the natural gathering and dispersion of people in real subway stations. In addition, this case constructed a distance-based network to simulate the connection between passengers. Each subject is regarded as a node, and the connection between nodes is based on the distance between them. This case also defines the connection rules between passenger subject nodes, that is, when the distance between two subjects is less than 1.5 meters, a connection will be established between them. Finally, before the simulation starts, this case initializes the position and network connection of the subject according to the defined rules.

[0127] In the key subject definition stage of the risk evolution simulation model, 10 states of passenger subjects in the subway station bioterrorism attack event are defined: normal activity, susceptible (initial), infected (initial), evacuated, isolated, exposed, susceptible (final), infected (final), and confirmed. The specific state definitions are as follows:

[0128] 1. During the normal operation period of the subway station, the general public is in a normal activity state. They are in a "normal activity" state in the subway station, such as walking, shopping or watching performances, which is also their initial state.

[0129] 2. When terrorists enter the subway station and release bioterrorism threat factors, the source of infection of bioterrorism threat appears in the subway station. At this time, 99% of the general population in the subway station are exposed to the environment that may be infected, becoming the main body of the "susceptible (initial)" state, and 1% of the people are directly infected due to direct contact with the source of infection personnel / agents, becoming "infected (initial)".

[0130] 3. Passengers in the "Infected (Initial)" state come into contact with other passengers in the "Susceptible (Initial)" state who are connected to the network at a rate of 10 people per minute. The susceptible passengers who are contacted have a 90% probability of being infected and becoming passengers in the "Susceptible (Initial)" state.

[0131] 4. After the subway station operator identifies the occurrence of a bioterrorism attack, it will take measures to control the further expansion of the situation. Due to the infectiousness of bioterrorism threats, subway station managers usually conduct classified control for the general population. After the subway station manager makes a key decision and issues an evacuation or isolation order to the subway station staff, the subway station manager begins to act to isolate the high-risk population that has been infected / is very likely to be infected to prevent the further expansion of the source of infection; evacuate the low-risk population that is less likely to be infected to block the transmission path between the source of infection and the susceptible population. Therefore, at this time, the general population is in two possible states: "evacuated" or "isolated."

[0132] 5. Health care workers triage the evacuated / isolated general population, who have two possible health states: infected and uninfected. Therefore, after the implementation of control measures and triage, the general population will eventually be in four possible states: uninfected & evacuated, infected & evacuated, uninfected & isolated, infected & isolated, corresponding to "susceptible (final)", "infected (final)", "exposed", and "confirmed" respectively.

[0133] Table 3 shows the classification of the general population

[0134] Not infected Infected Evacuated Susceptible (final) Infected (final) Isolation Exposed Confirmed

[0135] As attached Figure 2 As shown in the figure, the state transition triggering conditions of the passenger subject in the biological terrorist attack incident at the subway station are defined as follows:

[0136] Table 4 is the definition of the state transition triggering conditions of the passenger subject in the subway station biological terrorist attack event

[0137]

[0138] Definition of other risk entities in the risk evolution simulation model

[0139] In the simulation model of the risk evolution of biological terrorist incidents in subway stations, in addition to the passenger subject, there are four other major risk subjects involved. These subjects are terrorist attackers, subway station operating unit leaders, subway station staff, and health treatment personnel. Next, we will elaborate on the behavioral rules of these four types of personnel to ensure accurate simulation of the risk evolution process.

[0140] (1) Terrorists: The main responsibility of this subject is to create a terrorist attack, thereby triggering the entire risk evolution process. In the initial stage of the simulation model, the terrorists are in a "waiting" state. They hide in the subway station and look for the best time to launch an attack. When the 5-minute hidden countdown ends, the terrorist subject will send an "attack" message to all other subjects to simulate the execution of the attack.

[0141] (2) Metro station operating unit leaders: As decision-makers at the metro station, metro station operating unit leaders play a vital role in emergency situations. They are responsible for making key decisions and guiding metro station staff to take appropriate actions. Metro station operating unit leaders are initially in an "idle" state, monitoring the routine operation of the metro station; once they receive an "attack" message from a terrorist attacker, the manager will enter the "decision-making" state, using 3 minutes of decision-making time to assess the situation and develop a response strategy; after the decision is made, the manager will send an "I decided!" message to the main metro station staff to simulate the issuance of advance disposal instructions such as evacuation and isolation.

[0142] (3) Subway station staff: In an emergency, subway station staff are responsible for the effective evacuation and isolation of the general population to reduce harm and control the spread of risks. Initially, they are in an "idle" state, ready to respond to emergencies at any time; after receiving advance disposal instructions from subway station managers, subway station staff will enter the "action" state, ready to perform evacuation and isolation tasks; after 5 minutes, subway station staff begin to guide the crowd and issue clear guidance instructions to the crowd to ensure that the crowd is evacuated or isolated safely and orderly.

[0143] (4) Medical personnel: After a bioterrorism incident occurs, medical personnel are responsible for providing timely medical assistance to the affected passengers. Initially, medical personnel are in an "idle" state, on standby to respond to emergency medical needs; after receiving a distress message from the subway station manager, medical personnel will rush to the scene as soon as possible; 30 minutes later, medical personnel arrive at the subway station and send an "I decided!" message to the passengers to simulate the triage of passengers.

[0144] Human-computer interaction operation of risk evolution simulation model

[0145] The simulation model allows users to interact with the model through a graphical user interface (GUI). Users can simulate different bioterrorism incident scenarios by inputting different parameters and conditions, and control and adjust the simulation environment. Figure 5 shown.

[0146] After setting the input parameters and variables, the evolution of the risk of bioterrorism incidents in subway stations can be simulated. As time goes by, the changes in the behavior states of passengers represent the evolution of the risk of incidents, and the results are intuitively displayed on the experimental platform (screenshot at the 45th minute is attached). Figure 3 shown).

[0147] Furthermore, during the simulation, the system can collect detailed process and result data and provide detailed result analysis and evaluation to help users understand the impact of different decisions and operations on the evolution of events, and thus obtain improved response strategies for the risk of bioterrorism events in subway stations. The data collection results of the risk evolution simulation model are shown in the attached figure. Figure 5 shown.

[0148] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When the use is implemented in whole or in part in the form of a computer program product, the computer program product includes one or more computer instructions. When the computer program instructions are loaded or executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL) or wireless (e.g., infrared, wireless, microwave, etc.) mode) to another website site, computer, server or data center. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk SolidState Disk (SSD)), etc.

[0149] The above is only a preferred embodiment of the present invention. It should be pointed out that, for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A human-computer interactive method for risk analysis of bioterrorism incidents in public places, characterized in that: include: S1. Building a risk evolution simulation model, the risk evolution simulation model includes: a continuous space representing a public place; An agent library that defines the behavior and properties of the subject; A module for setting random distribution patterns to simulate the position distribution of the subject in continuous space; Construct a distance-based network generation module; Initialize the simulation module; S2. defining the classification of key subjects and the classification of non-key subjects in the risk evolution simulation model; S3. Use the graphical user interface to input different parameters and conditions into the risk evolution simulation model, and then simulate different bioterrorism incident scenarios. During the simulation process, collect the process and result data of the bioterrorism incident, and analyze and evaluate the process and result data of the bioterrorism incident.

2. The method for risk analysis of bioterrorism incidents in public places with human-computer interaction according to claim 1, characterized in that: The continuous space is a two-dimensional or three-dimensional structure.

3. The method for risk analysis of bioterrorism incidents in public places with human-computer interaction according to claim 1, characterized in that: The behavior and attributes of the subject include the subject's location distribution, state transition, and interaction rules.

4. The method for risk analysis of bioterrorism incidents in public places with human-computer interaction according to claim 1, characterized in that: The working process of the random distribution mode setting module is: firstly, the initial position of the subject in the continuous space is set, and then the random distribution algorithm is used to simulate the natural distribution of the crowd.

5. The method for risk analysis of bioterrorism incidents in public places with human-computer interaction according to claim 4 is characterized in that: The working process of the network generation module is as follows: first, the connection rules between nodes are defined, and when the distance between two entities is less than a threshold, a connection is established between the two entities.

6. The method for risk analysis of bioterrorism incidents in public places with human-computer interaction according to claim 1, characterized in that: The classification of the key subjects includes normal activities, initial susceptible persons, initial infected persons, evacuated persons, isolated persons, exposed persons, final susceptible persons, final infected persons, and confirmed persons.

7. The method for risk analysis of bioterrorism incidents in public places with human-computer interaction according to claim 1, characterized in that: The classification of non-critical subjects includes terrorist attackers, site managers, site staff, and health treatment personnel.

8. A human-computer interactive public place bioterrorism risk analysis system, characterized in that: include: A risk evolution simulation model, wherein the risk evolution simulation model comprises: a continuous space representing a public place; An agent library that defines the behavior and properties of the subject; A module for setting random distribution patterns to simulate the position distribution of the subject in continuous space; Construct a distance-based network generation module; Initialize the simulation module; A crowd subject classification module, used to define the classification of key subjects and the classification of non-key subjects in the risk evolution simulation model; The human-computer interaction module uses a graphical user interface to input different parameters and conditions into the risk evolution simulation model, thereby simulating different bioterrorism incident scenarios. During the simulation, the process and result data of bioterrorism incidents are collected, and the process and result data of bioterrorism incidents are analyzed and evaluated.

9. A computer-readable storage medium storing a computer program, which, when executed by a processor, implements the human-computer interactive public place bioterrorism incident risk analysis method according to any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the human-computer interactive method for analyzing the risk of bioterrorism incidents in public places described in any one of claims 1 to 7 is implemented.

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