Disclosure of Invention
The present invention aims to solve the related technical problems.
Therefore, the invention provides a respiratory tract infectious disease transmission risk assessment system of a multi-person dynamic scene, which can make up for the defect of consideration of dynamic behaviors of a plurality of persons in an actual scene at the same time or successively, improve the accuracy of risk assessment and better ensure public safety.
The invention relates to a respiratory tract infectious disease transmission risk assessment method based on a multi-person dynamic scene, which specifically and sequentially comprises the following steps:
Setting up a model of a risk assessment object and a research area, setting analysis parameters according to the characteristics of an infectious agent, setting crowd movement parameters, spreading numerical simulation aiming at the diffusion of infectious agents, calculating the exposure level of personnel, and comprehensively assessing the risk of infectious diseases.
Specifically, building a model of a risk assessment object and a research area, wherein the model is used for building a calculation area of a multi-person dynamic scene where respiratory tract infectious diseases occur, and performing calculation grid division on the area to build a calculation model;
setting analysis parameters according to the characteristics of the infectious agents, considering the release characteristics of the infectious agents from different areas of the respiratory system of a patient, setting different types of the infectious agents and exhalation characteristics according to different scenes, further simulating the process of exhaling the infectious agents and aerodynamic characteristics thereof, and constructing a result with universality as an input module;
And setting analysis parameters according to the characteristics of the infectious agents, wherein the analysis parameters are the characteristics of the infectious agents according to the pathological characteristics of the infectious agents to be analyzed, setting corresponding release positions and particle size distribution of the infectious agents, selecting a proper model to simulate the process of exhaling the infectious agents by the patients, and quantifying the aerodynamic characteristics of the infectious agents, and the model is a discrete phase model or a component transportation model.
The analysis parameters are set according to the characteristics of the infection source, and the release characteristics comprise a release part, a release concentration, particle size distribution and release time.
The analysis parameters are specifically set according to the characteristics of the infection sources:
For the characteristics of the infectious agents, two methods of a component transport model (STM) and a Discrete Phase Model (DPM) are respectively used for simulating the transmission of virus liquid drops.
The trace gas is selected in STM to represent the virus and the mass fraction in the patient's exhaled air flow is set.
In DPM, droplets of different particle diameters are released from the surface of a patient's mouth, and the droplet density, the frequency of release of the droplets, and the number of single releases are set, and the droplet trajectory is tracked using a lagrangian model, and the turbulent diffusion characteristics of the droplets are simulated using a discrete random walk model (DRW). Calculated by newton's second law:
Where mp is the drop mass and up,i is the velocity of the drop in the i direction. Fg,i is gravity, Fd,i is drag, Fb,i is Brownian force, and Fs,i is Safmann lift. ρi and ρ are the densities of the droplets and air, respectively. fD is a Stokes resistance correction function of the Reynolds number. τp is the characteristic response time.
The trace gas is CO2.
Setting crowd motion parameters, and realizing multi-person motion simulation of different scenes by writing user-defined functions (UDF) through a dynamic grid technology in Computational Fluid Dynamics (CFD), thereby realizing reliable simulation of multi-person motion and influence rules of the multi-person motion on an airflow field and an infectious agent diffusion process.
The set crowd movement parameters comprise the number of people in movement, the speed of people, the distance between people and the relative position distribution of people.
The specific steps of setting the crowd motion parameters are as follows:
the motion of an object is simulated by using a moving grid model, in particular to a moving grid simulation by using a fairing method (Smoothing) and a grid reconstruction method (REMESHING) in the moving grid model.
The springs in the ANSYS Fluent system used are approximately smooth (Spring-based). By considering the nodes as ideal springs, the node positions are updated by calculating the balance of the spring forces. Spring forceThe calculation formula of (2) is as follows:
Wherein the method comprises the steps ofAndIs the displacement of node i and neighboring node j, ni is the number of connected nodes of node i, kij is the spring rate, defined as:
Where kfac is a settable Spring Constant Factor parameter. When the node is in an equilibrium state, the spring force acting on the node should be 0, from which an iterative relation of the position calculation is derived. The spring fairing method has three parameters to be set in calculation, namely a spring stiffness coefficient (Spring Constant Factor), convergence accuracy (Convergence Tolerance) and iteration number (Number of Iterations), and the spring stiffness coefficient (Spring Constant Factor) has a value range of 0-1.
The dynamic mesh reconstruction is achieved by using a reconstruction internal mesh unit (Local Cell) in combination with a reconstruction of the triangle Face mesh (Local Face) on the deformation boundary.
For a scalar phi in the control volume of motion V, the integral form of the dynamic grid conservation equation is:
wherein ρ is the fluid density,As a vector of the flow velocity,For the grid speed of the moving grid, Γ is the diffusion coefficient and Sφ is the source term of phi. Here, theFor representing the boundary of the control volume V. In the numerical calculation process, a user-defined function (UDF) is written, and a DEFINE_CG_MOTION macro used for defining rigid body MOTION in an ANSYS Fluent system is called, so that the personnel interaction MOTION process with different speeds and different directions is realized. Because the complex surface structure of the human body easily generates a negative volume grid when simulating the movement of a person, ANSYS ICEM is used for generating a tetrahedron grid with stronger adaptability during pretreatment, the grid around the human body is encrypted, and a prismatic layer is added at the boundary. In the calculation process, boundary layer grids on the surface of the human body are fixed, so that the partial grids are not updated in the process of personnel interaction movement, the reduction of grid quality in the movement process is reduced, and the calculation accuracy is improved.
Aiming at the diffusion spreading numerical simulation of the infectious agents, corresponding boundary conditions are set according to the constructed actual situation, and the diffusion transport process of the infectious agents in the multi-person dynamic scene is analyzed to output the analysis result of the diffusion transport of the infectious agents.
The specific steps of spreading numerical simulations for the spread of infectious agents are:
The method is characterized by carrying out numerical simulation, researching the influence of factors of the number of interaction sports, the movement speed, the personnel position distribution, the droplet size and ventilation on the diffusion and concentration distribution of droplets exhaled by a plurality of persons and patients in detail, carrying out regional dynamic risk assessment, and providing scientific basis and technical support for the establishment of respiratory tract infectious disease prevention and control strategies in a person-intensive place. And calculating an indoor flow field of the multi-person interactive motion scene by using the RNG k-epsilon turbulence model and a SIMPLE algorithm, and adopting a second-order windward format. The buoyancy effect was simulated using a Boussinesq model. The air density and ambient relative humidity are set. And designing a plurality of groups of numerical simulation working conditions, and further researching the influence of relevant factors such as the number of sportsmen, the speed, the personnel position distribution, ventilation and the particle size of liquid drops. In addition, a plurality of monitoring points are provided to record transient airflow rates.
And calculating the exposure level of the susceptible people, and acquiring the space-time distribution evolution rule of the concentration of the infectious agents according to the diffusion analysis result of the corresponding infectious agents, so as to obtain the space-time evolution characteristic of the exposure level of the susceptible people.
The level of susceptible human exposure includes instantaneous exposure doses and cumulative exposure doses.
The specific steps of the susceptible person exposure level calculation are as follows:
And acquiring the space-time distribution evolution rule of the concentration of the infectious agents according to the corresponding diffusion analysis result of the infectious agents, and further acquiring the exposure level space-time evolution characteristic of susceptible people. In the embodiment, by setting a plurality of real-time monitoring points, the space-time distribution evolution rule of respiratory tract infectious agents in a multi-person dynamic scene is obtained. Specifically, for personal risk assessment, the probability of infection P for a susceptible person depends on the number of inhaled infection quanta Nquanta according to the Wells-Riley model:
Assuming a uniform distribution of virus in the patient's exhaled breath, the relative concentration Cr and the infection quantum yield QIP can be used to calculate the infection probability for a susceptible person:
Where Ca is the mass fraction of CO2 in the gas exhaled by the patient (4%) and C is the mass fraction of CO2 in the inhaled gas by the susceptible person. The inhalation ratio IF is:
Here Min can typically be set at 30L/min (susceptible), Mex can typically be set at 10L/min (patient), after exposure time T:
the infection probability P of the susceptible person is:
for regional risk assessment, consider that different height planes represent the respiratory height planes of standing and sitting persons, respectively. Dividing the plane into areas with corresponding areas, calculating the average concentration of infectious agents in each area, substituting C in the equivalent individual risk assessment method into the formula, and calculating the exposure and risk of each area.
The comprehensive risk assessment of infectious diseases is used for assessing dynamic risk distribution characteristics in a space according to a flow field evolution mode, an infectious material diffusion process and result and an exposure level of susceptible people, quantifying a high risk area evolution rule and outputting risk distribution data.
The invention constructs an indoor non-uniform risk assessment algorithm, which can be used for individual infection risk assessment and regional risk assessment respectively. The method combines the significant differences of the concentration distribution of the infectious agents in different areas in the actual multi-person dynamic scene, and provides a feasible method for accurately carrying out indoor risk assessment and correcting in a non-uniform environment by combining CFD simulation results.
According to the respiratory infectious disease propagation risk assessment method based on the multi-person dynamic scene, dynamic exposure risk assessment of susceptible people is carried out through the spatial characteristics of the scene, typical motion parameters such as the number of motion people, the relative position distribution, the motion speed and the like of a plurality of motion people, and key environment parameters such as temperature, humidity and ventilation conditions, so that the respiratory infectious disease area risk dynamic evolution rules of typical personnel-intensive places of different scenes (such as hospitals, waiting rooms, subway stations, terminal buildings or schools) are assessed, the requirement for accurately predicting the personnel infection risk of the corresponding scene is met, scientific basis is provided for formulating prevention and control strategies of personnel-intensive places, technical support is provided for risk assessment and emergency management of sudden public health events, and public safety is ensured.
The tool constructed based on the invention can be used for infectious disease risk assessment in typical personnel-intensive places, is helpful for guiding measures such as comprehensive design zoned ventilation, filtration, air curtain and the like, and reduces the respiratory infectious disease transmission risk. Aiming at the transportation hub, a reasonable scheduling scheme is designed, the exposure time of passengers is reduced, and the risk of cross infection is reduced.
In summary, the embodiment of the invention is based on the CFD technology, combines a three-dimensional numerical human model, utilizes a numerical simulation method of multi-person exercise, can develop detailed researches on the number of exercise persons, the position distribution of the personnel, the speed of the personnel, the particle size of infectious agent droplets and potential influencing factors of ventilation of a multi-person dynamic scene, analyzes the airflow characteristics of the multi-person exercise and the influence of the multi-person exercise on the transmission of respiratory infectious diseases, develops regional dynamic risk assessment, finally establishes a non-uniform risk assessment method in the multi-person dynamic scene, and provides scientific basis and technical support for the establishment of infectious disease prevention and control strategies in a person-intensive place.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
The risk assessment method disclosed by the invention can be used for optimizing the existing respiratory infectious disease transmission risk assessment technology, improving the risk assessment precision and reliability, supplementing and replacing high-cost field experiments by using the CFD technology, and can be used for respiratory infectious disease transmission risk assessment in hospitals, waiting rooms, subways, terminal buildings, schools and other personnel-intensive places and guiding the formulation of prevention and control strategies.
Detailed Description
Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative and intended to explain the present application and should not be construed as limiting the application.
The following describes a multi-person dynamic scenario respiratory infectious disease risk assessment method according to an embodiment of the present invention with reference to fig. 1 to 5, and first describes a respiratory infectious disease risk assessment system according to an embodiment of the present invention with reference to the accompanying drawings.
FIG. 1 is a flow chart of a method for risk assessment of respiratory infectious disease in a multi-person dynamic scenario of the present invention.
The model building of the risk assessment object and the research area (specifically, the model building of the risk assessment object and the research area of the respiratory tract infectious disease transmission risk research area of the multi-person dynamic scene) is used for building a calculation area of a multi-person dynamic space where the respiratory tract infectious disease occurs, and the calculation area is subjected to grid division to build a calculation model.
The analysis parameters are set according to the characteristics of the infectious agents, mainly according to the pathological characteristics of the infectious agents to be analyzed, the corresponding release positions and particle size distribution of the infectious agents are set, and proper models (discrete phase models, component transport models and the like) are selected to simulate the process of exhaling the infectious agent droplets and aerosols by the patients, so that the aerodynamic characteristics of the infectious agents are quantified.
The crowd motion parameters are set, mainly according to scene environment conditions, a Computational Fluid Dynamics (CFD) dynamic grid method of multi-person motion is set, and a multi-person dynamic scene is realized.
And carrying out numerical simulation on the diffusion spreading numerical simulation of the pollutants, setting a contextual model according to the current conditions, and carrying out numerical simulation on the flow propagation process by taking the contextual model as an input condition so as to output an analysis result of diffusion transport of the infectious agents.
The personnel exposure level is calculated for the spatial and temporal distribution of the concentration of the infectious agent according to the analysis result of the diffusion transport of the infectious agent and the exposure level of the susceptible population is obtained.
The comprehensive infectious disease infection risk assessment is used for outputting an infectious agent diffusion and transportation analysis result, an exposure level of susceptible people and risk distribution in an assessment space according to an airflow movement mode, a process of exhaling an infectious agent and aerodynamic characteristics of the process, and outputting a risk distribution result.
The evaluation system provided by the embodiment of the invention can solve the requirement of accurate prediction of the personnel infection level in the multi-person dynamic scene infectious disease transmission risk evaluation, can be applied to the design of respiratory tract infectious disease protection schemes and emergency plans of susceptible people, improves the accuracy of risk evaluation, and better ensures public safety.
Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative and intended to explain the present application and should not be construed as limiting the application.
The following describes a respiratory infectious disease risk assessment method according to an embodiment of the present invention in a multi-person dynamic scenario, and first describes a respiratory infectious disease risk assessment system according to an embodiment of the present invention with reference to the accompanying drawings.
Fig. 1 is a schematic flow chart of a respiratory infectious disease risk assessment system according to an embodiment of the present invention, and as shown in fig. 1, the respiratory infectious disease risk assessment system includes a model building of a risk assessment object and a research area, setting analysis parameters according to infection source characteristics, spreading numerical simulation for infectious agents, a quantitative calculation module, and an infectious disease risk assessment module.
A detailed description of one embodiment is provided below with reference to the accompanying drawings.
In the embodiment of the invention, as shown in fig. 1, the system of the embodiment of the invention comprises a risk assessment object, a risk assessment object of a research area, a model building of the research area, an infection source characteristic module, an environment condition control module, a multi-person interaction motion numerical simulation module, a susceptibility population exposure level quantitative calculation module, a multi-person dynamic scene respiratory infectious disease transmission risk assessment module and a multi-person dynamic scene respiratory infectious disease transmission risk assessment module, wherein the infection source characteristic module considers factors such as the generation and release positions, the concentration, the particle size distribution, the release time and the like of infectious agents, the environment condition control module considers factors such as ventilation, temperature and humidity, the position of the infectious agents and the like, the multi-person interaction motion numerical simulation module considers factors such as the number of people in motion, the speed, the distance, the relative position distribution and the like, the susceptibility population exposure level quantitative calculation module obtains characteristics such as instantaneous exposure dose and accumulated exposure dose of the susceptibility population, and the multi-person dynamic scene respiratory infectious disease transmission risk assessment module is used for carrying out quantitative assessment of the multi-person dynamic scene respiratory infectious disease transmission risk.
Model construction of a risk assessment object and a research area of a respiratory tract infectious disease transmission risk research area of a multi-person dynamic scene:
As shown in fig. 2, a 10m×10m×3m (length×width×height) multi-person indoor scene is constructed in consideration of the scene's typical nature, similar to the scale of a small train station waiting room, a subway station, a small and medium-sized hospital visit area. Different air inlets correspond to ventilation modes, namely Displacement Ventilation (DV), natural Ventilation (NV) and Mixed Ventilation (MV). The areas of the air inlet and the air outlet are 1m2. 7 persons are arranged in the room, and a static standing patient (red) and six sports persons M01-M06 (blue) are arranged in the room. The face of the patient is parallel to the sportsman, the width of the human body is 0.58m, and the interval is set to be 1.0m. According to the relative positions of the moving personnel and the patient, three scenes are established, and the influence of the relative position distribution of the personnel on the airflow result of the multi-person interactive movement is compared. These position distributions are named "triangle distribution" (scene 1), "ladder distribution" (scene 2), and "side-by-side distribution" (scene 3), respectively. Generating unstructured tetrahedral grids in ANSYS ICEM software, encrypting the grids around the human body, and adding prismatic layer boundaries.
An infection source characteristic module:
For the characteristics of the infectious agents, two methods, namely a component transport model (STM) and a Discrete Phase Model (DPM), are respectively used for simulating the transmission of virus droplets. CO2 was chosen as the tracer gas in STM to represent the virus, with the mass fraction in the patient's exhaled air stream set to 4%. In DPM, droplets having particle diameters of 1, 5,10, 20, 50, 100 μm, respectively, were released from the surface of the patient's mouth, and the density was set at 1100kg/m3. The particles were released 412 at 0.2 s/time, a total of 1500 times, the trajectory was tracked using a lagrangian model, and the turbulent diffusion characteristics of the droplets were simulated using a discrete random walk model (DRW). Calculated by newton's second law:
Where mp is the drop mass and up,i is the velocity of the drop in the i direction. Fg,i is gravity, Fd,i is drag, Fb,i is Brownian force, and Fs,i is Safmann lift. ρi and ρ are the densities of the droplets and air, respectively. fD is a Stokes resistance correction function of the Reynolds number. τp is the characteristic response time.
The multi-person interaction motion numerical simulation module comprises:
Further, in the numerical simulation of human interactive movements, simulating human movements and their effects on the air flow is a technical difficulty. The dynamic grid Model (DYNAMIC MESH Model) in the CFD simulates the movement of an object by adopting a mode of defining the movement of a boundary or grid nodes, can be used for simulating the flow of the change of the domain shape along with the time due to the calculation of the movement of the boundary of the domain, has been widely verified by experiments, and has better adaptability. The core technology of the dynamic mesh method is a mode of handling mesh movement caused by object movement, namely a mesh updating method. The grid updating methods commonly used in the dynamic grid method mainly include a Smoothing method (Smoothing), a grid reconstruction method (REMESHING) and a dynamic Layering method (Layering). The three-dimensional numerical human model constructed by the embodiment has abundant surface details, and the generated grid structure is complex, so that the grid simulation is performed by comprehensively adopting a fairing method and a grid reconstruction method. The fairing method is a basic dynamic grid method and is mainly suitable for scenes in which small deformation is caused and the topological relation of grid nodes is not changed in the deformation process. Three methods of fairing are provided in the ANSYS Fluent system used, spring-approximate-fairing (Spring-based), diffuse-fairing (Diffusion), linear elastic solids (LINEARLY ELASTIC Solid). The invention selects a spring approximate fairing method, and the basic idea of the method is to consider the nodes as ideal springs, and update the positions of the nodes by calculating the balance of spring forces. Spring forceThe calculation formula of (2) is as follows:
Wherein the method comprises the steps ofAndIs the displacement of node i and neighboring node j, ni is the number of connected nodes of node i, kij is the spring rate, defined as:
Where kfac is a settable Spring Constant Factor parameter. When the node is in an equilibrium state, the spring force acting on the node should be 0, from which an iterative relation of the position calculation is derived. The spring fairing method has three main parameters to be set in calculation, namely, the spring stiffness coefficient (Spring Constant Factor), the value range is 0-1, the larger the value is, the wider the influence range is, the convergence accuracy (Convergence Tolerance) is set to be 0.7 in the embodiment, the convergence accuracy (Convergence Tolerance) is set to be 0.001 in the embodiment, the iteration times (Number of Iterations) are set, namely, the iteration times for solving an iteration equation are set, the initial value is set to be 20 in the embodiment, and the initial value is adjusted according to the convergence condition in the calculation process.
The grid reconstruction method is a dynamic grid method capable of solving any motion, and the basic principle is that the quality of grids is continuously monitored in the calculation process, and grids with the quality lower than the required quality are marked and repartitioned. In practical applications, the mesh reconstruction method is mainly used for unstructured meshes and is often used together with the fairing method. In the ANSYS Fluent system, there are 5 mesh reconstruction methods in total, reconstructing an internal mesh Cell (Local Cell), reconstructing a triangle Face mesh on a deformation boundary (Local Face), reconstructing a Face mesh adjacent to a motion boundary (Region Face), reconstructing a mesh Cell of the entire Region and a Face mesh (CutCell Zone), and reconstructing a prism layer Cell in a 3D Region (2.5D). In this embodiment, the Local Cell and Local Face methods are used in combination to implement the dynamic mesh reconstruction.
For a scalar phi in the control volume of motion V, the integral form of the dynamic grid conservation equation is:
wherein ρ is the fluid density,As a vector of the flow velocity,For the grid speed of the moving grid, Γ is the diffusion coefficient and Sφ is the source term of phi. Here, theFor representing the boundary of the control volume V. In the numerical calculation process, a user-defined function (UDF) is written, and a DEFINE_CG_MOTION macro used for defining rigid body MOTION in an ANSYS Fluent system is called, so that the personnel interaction MOTION process with different speeds and different directions is realized. Because the complex surface structure of the human body easily generates a negative volume grid when simulating the movement of a person, ANSYS ICEM is used for generating a tetrahedron grid with stronger adaptability during pretreatment, the grid around the human body is encrypted, and 6 prism layers are added at the boundary. In the calculation process, boundary layer grids on the surface of the human body are fixed, so that the partial grids are not updated in the process of personnel interaction movement, the reduction of grid quality in the movement process is reduced, and the calculation accuracy is improved.
Numerical simulations were developed for the spread of infectious agents:
The method is characterized by carrying out numerical simulation, researching the influence of factors of the number of interaction sports, the movement speed, the personnel position distribution, the droplet size and ventilation on the diffusion and concentration distribution of droplets exhaled by a plurality of persons and patients in detail, carrying out regional dynamic risk assessment, and providing scientific basis and technical support for the establishment of respiratory tract infectious disease prevention and control strategies in a person-intensive place. And calculating an indoor flow field of the multi-person interactive motion scene by using the RNG k-epsilon turbulence model and a SIMPLE algorithm, and adopting a second-order windward format. The buoyancy effect was simulated using a Boussinesq model. The air density was set at 1.18kg/m3. The ambient relative humidity was set to 50%. And designing a plurality of groups of numerical simulation working conditions, and further researching the influence of relevant factors such as the number of sportsmen, the speed, the personnel position distribution, ventilation and the particle size of liquid drops. In addition, a plurality of monitoring points are provided to record transient airflow rates.
Personnel exposure level calculation:
And acquiring the space-time distribution evolution rule of the concentration of the infectious agents according to the corresponding diffusion analysis result of the infectious agents, and further acquiring the exposure level space-time evolution characteristic of susceptible people. In the embodiment, by setting a plurality of real-time monitoring points, the space-time distribution evolution rule of respiratory tract infectious agents in a multi-person dynamic scene is obtained. Specifically, for personal risk assessment, the probability of infection P for a susceptible person depends on the number of inhaled infection quanta Nqua:
Assuming a uniform distribution of virus in the patient's exhaled breath, the relative concentration Cr and the infection quantum yield QIP can be used to calculate the infection probability for a susceptible person:
Where Ca is the mass fraction of CO2 in the gas exhaled by the patient (4%) and C is the mass fraction of CO2 in the inhaled gas by the susceptible person. The inhalation ratio IF is:
Here Min can typically be set at 30L/min (susceptible), Mex can typically be set at 10L/min (patient), after exposure time T:
the infection probability P of the susceptible person is:
As shown in FIG. 3, for regional risk assessment, consider that 1.55m and 1.25m height planes represent the respiratory height planes of standing and sitting personnel, respectively. Dividing the plane into 1m multiplied by 1m areas, calculating the average concentration of infectious agents in each area, and substituting C in the equivalent individual risk assessment method into the formula to calculate the exposure and risk of each area.
Infectious disease risk assessment module:
in combination with the basic data of the analysis parameters 300 set according to the characteristics of the infectious agents, as shown in fig. 5, an area where the risk of infection of a susceptible person is higher than 5% at 30min (typical waiting time of a waiting room at a railway station) is taken as a high risk area. The virus release rate of COVID-19 patients can reach 725-2345 quata/h, and when the highest infection source intensity, namely 2345quanta/h is considered, the C corresponding to the high risk area is deduced to be more than or equal to 1.75e-6. Comparing the 6-person simultaneous interactive motion scene with the time change rule of the high risk area of the 1.55m height plane in the no-motion scene, the high risk area is concentrated at the right front of the patient before the multi-person interactive motion, and the high risk area at the left front and the rear of the patient is also obviously enlarged in 3min after the multi-person motion, which is likely to be related to strong indoor convection caused by the multi-person motion, and is also related to the following of the virus aerosol exhaled by the patient to the wake of the left-side motion personnel. It can thus be seen that the movement of multiple persons simultaneously increases the range of high risk areas of the respiratory zone of standing and sitting persons. For a standing person breathing zone z=1.55m plane, in an unmanned motion scene, the area of a high risk area (C is more than or equal to 1.75e-6) gradually increases to about 20m2 and tends to be stable during 120 s-300 s. The area of the high risk area is rapidly enlarged within about 50s after the occurrence of the multi-person exercise, namely the area of the high risk area at the moment t=120s is about 3.85m2, the area reaches 19.24m2 by the moment t=170s, the area of the high risk area is enlarged to 34.53m2 by the moment t=300s (which is 8.97 times that of the moment t=120s), and the trend of continuing the enlargement is still that the area is 67.9 percent higher than that of the area of the high risk area at the moment t=120s, which is 20.57m2 of the scene without the interactive exercise.
In summary, the embodiment calculates the mixing characteristics of infectious agents in a multi-person dynamic scene, reveals the airflow characteristics of multi-person movement under different personnel position distribution, and the personnel position distribution can influence the airflow form and the propagation rule of the infectious agents, wherein the stepped distribution and the side-by-side distribution are beneficial to the transverse diffusion of the infectious agents. The change condition of the high-risk area can be quantified through the area dynamic risk assessment. Features are disclosed that the movement of multiple persons significantly promotes remote airborne transmission of respiratory infections and enlarges high risk areas. Considering that many people's movements frequently occur in densely populated places, a large error may result if the regional risk is still assessed with the virus concentration profile of the static scenario. Based on the invention, dynamic risk assessment can be carried out in an environment with a large number of active personnel. And measures such as regional ventilation, filtration, air curtain and the like are comprehensively designed, so that the transmission risk of respiratory infectious diseases is reduced. And a reasonable scheduling scheme is designed for the transportation hub, so that the exposure time of passengers is reduced, and the risk of cross infection is reduced.
It should be noted that the explanation of the embodiment of the respiratory infectious disease transmission risk assessment system in the multi-person dynamic scenario is also applicable to the risk assessment method in the embodiment, and is not repeated here.
According to the multi-person dynamic scene respiratory tract infectious disease risk assessment method provided by the embodiment of the invention, the exposure risk assessment of susceptible people is carried out through the measurement parameters such as the spatial features, the personnel movement features, the environmental features and the like, so that the risk level of infectious disease occurrence under different scene couplings is assessed, the requirement of accurate prediction of the personnel infection level in the infectious disease transmission risk assessment is solved, theoretical basis is provided for formulating respiratory tract infectious disease prevention and control scheme and emergency rescue, decision support is provided for emergency management of sudden public health events, the accuracy of risk assessment is improved, and public safety is better ensured.
In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the device or element being referred to must have a specific orientation, be configured and operated in a specific orientation, and therefore should not be construed as limiting the present invention.
In the description of the present invention, the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present invention, the meaning of "plurality" means at least two, for example, two, three, etc., unless specifically defined otherwise.
The specific meaning of the terms in the present invention can be understood by those of ordinary skill in the art according to the specific circumstances.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention.
In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.
While embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the invention, and that variations, modifications, alternatives and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the invention.