A method for assessing the spread of infectious diseases

Abstract

The present invention relates to the field of data analysis, and in particular to a method for evaluating the spread of infectious diseases. The present invention constructs a moving path for each infectious disease infection body in a city virtual map, and uploads the moving path and the symptom text data of the infectious disease infection body to an epidemic survey database; obtains the moving path of each infectious disease infection body to mark a number of overlapping activity nodes in the city virtual map, determines the distribution characteristics of the overlapping activity nodes, and calculates discrete distribution characterization coefficients based on the distribution characteristics to divide regional flow categories; calls data in the epidemic survey database, and adaptively analyzes and evaluates the spread of infectious diseases according to regional flow categories. The present invention can identify potential spread nodes of infectious diseases and estimate the severity of the spread of infectious diseases in each spread area.

Description

Technical Field

[0001] The present invention relates to the field of data analysis, and in particular to a method for evaluating the spread of infectious diseases. Background Art

[0002] The public health field needs effective assessment methods to deal with infectious diseases. In order to control them in a timely manner, it is necessary to accurately assess the spread of infectious diseases, including the speed of spread, the scope of spread, the characteristics of the infected population, and many other aspects.

[0003] Chinese patent application publication number: CN111739653A, discloses an evaluation method, device, computer equipment and storage medium for infectious disease transmission, the method comprising: obtaining target trajectory data corresponding to each evaluation object in a preset area in a first time slice, the preset area comprising multiple sub-areas; determining a matching sub-area matched by each evaluation object in the first time slice based on the target trajectory data, the matching sub-area being one of the multiple sub-areas; taking at least one of the multiple sub-areas as a target sub-area, and evaluating the evaluation objects in the target sub-area based on an infectious disease model to determine the transmission trend of the infectious disease in the evaluation objects in the preset area in the first time slice; taking the next time slice as the first time slice, and re-executing the above steps until the end of the target time period, to determine the transmission trend of the infectious disease in the evaluation objects in the preset area within the target time period.

[0004] However, there are still the following problems in the prior art:

[0005] In the early stages of an infectious disease, the data available are not analyzed in advance and in a timely manner to predict the potential spread of the infectious disease, which reduces the timeliness and efficiency of infectious disease assessments and causes a lag in subsequent prevention and control measures. Summary of the invention

[0006] To this end, the present invention provides a method for evaluating the spread of an infectious disease, so as to overcome the problem in the prior art that, in the early stages of an infectious disease, the acquired data cannot be preliminarily analyzed in advance and in a timely manner to predict the potential spread of the infectious disease, thereby reducing the timeliness and efficiency of infectious disease assessment and resulting in a lag in subsequent prevention and control measures.

[0007] To achieve the above object, the present invention provides a method for evaluating the spread of infectious diseases, comprising:

[0008] Constructing movement paths for each infectious agent in a virtual city map, and uploading the movement paths and symptom text data of the infectious agent to an epidemic investigation database;

[0009] Obtaining the movement paths of the infectious bodies of each of the infectious diseases, marking a number of overlapping activity nodes in the virtual city map, determining the distribution characteristics of the overlapping activity nodes, and calculating the discrete distribution characterization coefficient based on the distribution characteristics to divide the regional flow categories;

[0010] Calling the data in the epidemiological investigation database, analyzing and evaluating the spread of infectious diseases according to the regional flow categories, including:

[0011] Determine the flow characteristics of each infectious body at each overlapping activity node, identify potential diffusion nodes, screen the potential diffusion nodes according to the historical traffic flow characteristics corresponding to the potential diffusion nodes to obtain effective diffusion nodes, predict the diffusion area based on each effective diffusion node, obtain the propagation characteristics of each diffusion area within a predetermined time period to determine the propagation diffusion characterization coefficient, and evaluate the diffusion level of the corresponding diffusion area;

[0012] Or, determining peripheral overlapping active nodes, determining an expansion ratio based on the node categories of the peripheral overlapping active nodes, and constructing a diffusion area based on the expansion ratio;

[0013] Among them, the distribution characteristics include the number of overlapping activity nodes and the average distance between each overlapping activity node, and the transmission characteristics include the number of new infections and the symptom emergence rate.

[0014] Furthermore, the process of calculating the discrete distribution characterization coefficient based on the distribution characteristics includes:

[0015] The ratio of the quantity threshold to the quantity of overlapping active nodes is used as a first distribution feature;

[0016] The ratio of the average distance between each overlapping activity node to the distance threshold is used as the second distribution feature;

[0017] The first distribution feature and the second distribution feature are weightedly summed to determine a discrete distribution characterization coefficient.

[0018] Furthermore, the geographical mobility categories include:

[0019] If the discrete distribution characterization coefficient is greater than or equal to the discrete distribution characterization coefficient threshold, classifying the overlapping activity nodes into a geographical flow dispersion category;

[0020] If the discrete distribution characterization coefficient is less than the discrete distribution characterization coefficient threshold, the overlapping activity nodes are classified into a regional flow aggregation category.

[0021] Furthermore, the spread of infectious diseases is analyzed and evaluated, including:

[0022] If the overlapping activity nodes are of the regional flow dispersion category, the flow characteristics of each infectious body in each overlapping activity node are determined, potential diffusion nodes are identified, and potential diffusion nodes are screened according to the historical traffic flow characteristics corresponding to the potential diffusion nodes to obtain effective diffusion nodes, and the diffusion area is predicted based on each effective diffusion node. The propagation characteristics of each diffusion area within a predetermined time period are obtained to determine the propagation diffusion characterization coefficient, and the diffusion level of the corresponding diffusion area is evaluated;

[0023] If the overlapping activity nodes are of the regional flow aggregation category, the peripheral overlapping activity nodes are determined, the expansion ratio is determined based on the node category of the peripheral overlapping activity nodes, and the diffusion area is constructed based on the expansion ratio.

[0024] Furthermore, the process of determining potential diffusion nodes includes,

[0025] Obtain the flow vector of each infectious body at each overlapping activity node;

[0026] The overlapping activity nodes that meet the diffusion benchmark conditions are identified as potential diffusion nodes;

[0027] The diffusion benchmark condition is that the number of corresponding flow vectors in any direction in the overlapping activity nodes is greater than or equal to a flow vector number threshold.

[0028] Furthermore, the process of screening potential diffusion nodes to determine effective diffusion nodes includes:

[0029] If there is any potential diffusion node whose historical traffic flow characteristics are greater than or equal to the traffic flow characteristic threshold, the potential diffusion node is determined as a valid diffusion node.

[0030] Furthermore, the process of predicting the diffusion area based on each effective diffusion node includes:

[0031] Expand the boundary line of the effective diffusion node outward by a reference distance;

[0032] The closed range area formed after the expansion is determined as the diffusion area.

[0033] Furthermore, the process of obtaining the propagation characteristics of each diffusion area within a predetermined time period to determine the propagation diffusion characterization coefficient includes:

[0034] The ratio of the number of new infections to the threshold number of new infections is used as the first diffusion feature;

[0035] The ratio of the symptom highlighting rate to the symptom highlighting rate threshold is used as the second diffusion feature;

[0036] The sum of the first diffusion characteristic and the second diffusion characteristic is determined as the propagation diffusion characterization coefficient.

[0037] Further, the process of evaluating the diffusion level corresponding to the diffusion area includes,

[0038] Presetting the corresponding relationship between the diffusion level and the propagation diffusion characterization coefficient interval;

[0039] Determine the propagation diffusion characterization coefficient interval to which the propagation diffusion characterization coefficient corresponding to the diffusion area belongs;

[0040] Among them, the diffusion level corresponds to the propagation diffusion characterization coefficient interval one by one.

[0041] Further, the enlargement ratio is determined based on the node category of the peripheral overlapping active nodes, including:

[0042] The enlargement ratio corresponds one-to-one with the node categories of the peripheral overlapping activity nodes;

[0043] The node categories include living areas, commercial areas and industrial areas.

[0044] Compared with the prior art, the present invention constructs a movement path for each infectious disease infected body in the city virtual map, and uploads the movement path and the symptom text data of the infectious disease infected body to the epidemic investigation database; obtains the movement path of each infectious disease infected body to mark a number of overlapping activity nodes in the city virtual map, determines the distribution characteristics of the overlapping activity nodes, and calculates the discrete distribution characterization coefficient based on the distribution characteristics to divide the regional flow categories; calls the data in the epidemic investigation database, and adaptively analyzes and evaluates the spread of infectious diseases according to the regional flow categories. The present invention can identify potential spread nodes of infectious diseases and estimate the severity of the spread of infectious diseases in each spread area.

[0045] In particular, the present invention calculates the discrete distribution characterization coefficient based on the distribution characteristics of overlapping activity nodes. By marking the overlapping activity nodes in the city virtual map, it can clearly present the place nodes where several infectious disease infections frequently appear together. Such place nodes may often become key areas with higher risks of infectious disease transmission, thereby improving the efficiency of identifying potential transmission place nodes. Then, according to the distribution characteristics of overlapping activity nodes with potential transmission characteristics, that is, the number of overlapping activity nodes in the city virtual map and the average distance between each overlapping activity node, it can further reflect the degree of transmission and transmission mode of infectious diseases within the spatial scope of the urban area. Therefore, the present invention uses the discrete distribution characterization coefficient to characterize the distribution degree of infectious disease transmission, or presents a relatively discrete distribution, or presents an overly dense concentrated distribution, so as to provide objective data support for the subsequent division of regional flow categories, so as to adaptively analyze and evaluate the spread of infectious diseases, and ensure the accuracy of infectious disease transmission analysis.

[0046] In particular, the present invention determines the potential diffusion nodes that may become the further concentrated spread of infectious diseases in the future according to the movement paths corresponding to the infectious disease infected bodies contained in each overlapping activity node. At the same time, according to the historical traffic flow data of the potential diffusion nodes, it can characterize the personnel flow coverage and the severity of the infectious disease spread caused by the potential diffusion nodes, so as to determine the effective diffusion nodes, and identify the potential diffusion nodes with more serious potential impact as effective diffusion nodes for targeted analysis. Since the area involved in the effective diffusion nodes is relatively small, and the spread of infectious diseases is dynamic, therefore, when analyzing the spread degree, the area range of the effective diffusion nodes is appropriately expanded to characterize the flow degree of the dynamic infectious disease infected bodies and the flow coverage area to analyze the spread degree. Therefore, the effective diffusion nodes are expanded, and a larger area with data analysis value is planned. Monitoring the number of new infections and the symptom emergence rate in the area within a certain period of time can characterize and present the real-time and dynamic spread speed and spread intensity of infectious diseases in the area to a certain extent. The impact of the above characteristics is quantified according to the spread and diffusion characterization coefficient, and the development trend of the spread and diffusion of infectious diseases is accurately grasped. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 A schematic diagram of the steps of the infectious disease transmission assessment method according to an embodiment of the invention;

[0048] Figure 2 A logical decision diagram for classifying regional mobility categories for embodiments of the invention;

[0049] Figure 3 A logical decision diagram for analyzing and evaluating the spread of infectious diseases according to an embodiment of the invention;

[0050] Figure 4 A logical decision diagram for determining potential diffusion nodes for an embodiment of the invention. DETAILED DESCRIPTION

[0051] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0052] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0053] It should be noted that in the description of the present invention, terms such as "upper" and "outer" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is only for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0054] See also Figure 1 , which is a schematic diagram of the steps of the infectious disease transmission assessment method according to an embodiment of the present invention. The infectious disease transmission assessment method according to an embodiment of the present invention comprises:

[0055] Step S1, constructing a movement path for each infectious body in a virtual city map, and uploading the movement path and the symptom text data of the infectious body to an epidemic investigation database;

[0056] Step S2, obtaining the movement path of each infectious body to mark a number of overlapping activity nodes in the city virtual map, determining the distribution characteristics of the overlapping activity nodes, and calculating the discrete distribution characterization coefficient based on the distribution characteristics to divide the regional flow categories;

[0057] Step S3, calling the data in the epidemiological investigation database, and analyzing and evaluating the spread of infectious diseases according to the regional flow categories, including:

[0058] Determine the flow characteristics of each infectious body at each overlapping activity node, identify potential diffusion nodes, screen the potential diffusion nodes according to the historical traffic flow characteristics corresponding to the potential diffusion nodes to obtain effective diffusion nodes, predict the diffusion area based on each effective diffusion node, obtain the propagation characteristics of each diffusion area within a predetermined time period to determine the propagation diffusion characterization coefficient, and evaluate the diffusion level of the corresponding diffusion area;

[0059] Or, determining peripheral overlapping active nodes, determining an expansion ratio based on the node categories of the peripheral overlapping active nodes, and constructing a diffusion area based on the expansion ratio;

[0060] Among them, the distribution characteristics include the number of overlapping activity nodes and the average distance between each overlapping activity node, and the transmission characteristics include the number of new infections and the symptom emergence rate.

[0061] It can be understood that the city virtual map is a digital form of geographic information representation, which uses computer technology, geographic information system and other technologies to construct a virtual model of the city. In the assessment of the spread of infectious diseases, the activity trajectories and distribution locations of infectious disease carriers are marked on the city virtual map. The movement paths of infectious bodies can be intuitively presented through connecting lines and other methods, providing data support for the subsequent specific analysis of the spread direction of infectious diseases in the city, the coverage range and the degree of impact on the coverage range. This will not be elaborated here.

[0062] It can be understood that overlapping activity nodes refer to activity nodes where any multiple infectious disease infected bodies appear together. During implementation, they are determined based on the movement paths of the infectious disease infected bodies, including determining the activity nodes contained in the movement paths, and determining the activity nodes where at least two infectious disease infected bodies appear together as overlapping activity nodes. This will not be repeated here.

[0063] Specifically, there is no limitation on the specific structure of the epidemiological investigation database. Technical personnel in this field may obtain epidemiological investigation data in advance and construct a corresponding database, which will not be elaborated here.

[0064] In some possible implementations, the above data may be stored in a database of the analysis terminal specifically used to store relevant data, such as a CDC database;

[0065] Among them, the symptom text data of infectious disease infected bodies include relevant data such as the activity trajectory information of infectious disease infected bodies and the symptom information of infectious disease infected bodies, providing data support for subsequent analysis of related features.

[0066] Specifically, the process of calculating the discrete distribution characterization coefficient based on the distribution characteristics includes:

[0067] The ratio of the quantity threshold to the quantity of overlapping active nodes is used as a first distribution feature;

[0068] The ratio of the average distance between each overlapping activity node to the distance threshold is used as the second distribution feature;

[0069] The first distribution feature and the second distribution feature are weightedly summed to determine a discrete distribution characterization coefficient.

[0070] In implementation, when performing weighted summation, the weight of the first distribution feature is set to 0.45, and the weight of the second distribution feature is set to 0.55;

[0071] In implementation, the symptom text data of different infectious disease infected bodies during the historical occurrence of infectious diseases can be called, and the corresponding movement paths for each infectious disease infected body can be constructed in the city virtual map, and then the historical data of the number of overlapping activity nodes presented by several occurrences of infectious disease transmission and the historical data of the distance between each overlapping activity node can be determined to determine the average number of overlapping activity nodes and the average distance between each overlapping activity node;

[0072] The number threshold of overlapping active nodes is determined based on the mean number of overlapping active nodes. The purpose of setting the number threshold of overlapping active nodes in implementation is to characterize the situation where there are too many nodes covered by the movement trajectory of infectious bodies, resulting in excessive transmission impact. Therefore, in implementation, the number threshold of overlapping active nodes is determined between 1.5 and 1.8 times the number threshold of overlapping active nodes.

[0073] The distance threshold between overlapping activity nodes is determined based on the mean distance between overlapping activity nodes. Since the purpose of setting the distance threshold for overlapping activity nodes in implementation is to characterize that the range involved in the movement activities of infectious disease infected bodies is too large, which also causes excessive transmission impact, the distance threshold for overlapping activity nodes is determined between 1.25 times and 1.5 times the mean distance of overlapping activity nodes in implementation.

[0074] The embodiment of the present invention calculates the discrete distribution characterization coefficient based on the distribution characteristics of the overlapping activity nodes. By marking the overlapping activity nodes in the city virtual map, it is possible to clearly present the place nodes where several infectious disease infection bodies frequently appear together. Such place nodes may often become key areas with high risk of infectious disease transmission, thereby improving the efficiency of identifying potential transmission place nodes. Then, according to the distribution characteristics of the overlapping activity nodes with potential transmission characteristics, that is, the number of overlapping activity nodes in the city virtual map and the average distance between each overlapping activity node, it is possible to further reflect the degree of transmission and the transmission mode of the infectious disease within the spatial scope of the city area. For example, if the number of overlapping activity nodes is large and the average distance between each node is close, it can be shown to a certain extent that there is a high transmission risk in the relatively concentrated area formed by these node sets; on the contrary, if the number of overlapping activity nodes is small and the average distance between each node is far, it indicates that the transmission mode presents relatively dispersed and cross-regional characteristics. Therefore, the present invention uses the discrete distribution characterization coefficient to characterize the distribution degree of infectious disease transmission, or presents a relatively discrete distribution, or presents an overly dense concentrated distribution, to provide objective data support for the subsequent classification of regional flow categories, so as to adaptively analyze and evaluate the spread of infectious diseases and ensure the accuracy of infectious disease transmission analysis.

[0075] Specifically, see Figure 2, which is a logical decision diagram for classifying regional mobility categories in an embodiment of the present invention, and the classification of regional mobility categories includes:

[0076] If the discrete distribution characterization coefficient is greater than or equal to the discrete distribution characterization coefficient threshold, classifying the overlapping activity nodes into a geographical flow dispersion category;

[0077] If the discrete distribution characterization coefficient is less than the discrete distribution characterization coefficient threshold, the overlapping activity nodes are classified into a regional flow aggregation category.

[0078] The discrete distribution characterization coefficient threshold is selected in the interval [1.26,1.38].

[0079] Specifically, see Figure 3 , which is a logical decision diagram for analyzing and evaluating the spread of infectious diseases in an embodiment of the present invention, analyzing and evaluating the spread of infectious diseases, including:

[0080] If the overlapping activity nodes are of the regional flow dispersion category, the flow characteristics of each infectious body in each overlapping activity node are determined, potential diffusion nodes are identified, and potential diffusion nodes are screened according to the historical traffic flow characteristics corresponding to the potential diffusion nodes to obtain effective diffusion nodes, and the diffusion area is predicted based on each effective diffusion node. The propagation characteristics of each diffusion area within a predetermined time period are obtained to determine the propagation diffusion characterization coefficient, and the diffusion level of the corresponding diffusion area is evaluated;

[0081] If the overlapping activity nodes are of the regional flow aggregation category, the peripheral overlapping activity nodes are determined, the expansion ratio is determined based on the node category of the peripheral overlapping activity nodes, and the diffusion area is constructed based on the expansion ratio.

[0082] Specifically, see Figure 4 , which is a logic decision diagram for determining potential diffusion nodes in an embodiment of the invention. The process of determining potential diffusion nodes includes:

[0083] Obtain the flow vector of each infectious body at each overlapping activity node;

[0084] The overlapping activity nodes that meet the diffusion benchmark conditions are identified as potential diffusion nodes;

[0085] The diffusion benchmark condition is that the number of corresponding flow vectors in any direction in the overlapping activity nodes is greater than or equal to a flow vector number threshold.

[0086] It can be understood that any point of the boundary contour of the overlapping activity node where the infectious body is located is taken as the origin, and the flow vector is determined according to the movement direction of the infectious body after leaving the overlapping activity node, and marked in the city virtual map, which will not be repeated here.

[0087] In implementation, the mean value of the number of flow vectors is determined by calling the historical data of the number of flow vectors in each direction presented by each overlapping activity node in the virtual map of the city corresponding to the occurrence of infectious disease transmission for several times;

[0088] The threshold value of the number of flow vectors is determined based on the mean number of flow vectors. Since each overlapping activity node is determined based on the movement paths of several infectious disease infected bodies, or based on the same purpose, or based on the functional properties of the node, they appear together at a certain node, resulting in a large number of infectious disease infected bodies at the node, which may further cause the large-scale spread of infectious diseases. Therefore, the purpose of setting the threshold value of the number of flow vectors in implementation is to characterize the situation where the impact of infectious disease transmission at overlapping activity nodes is too serious and the amount of human contact caused is too large. Therefore, in implementation, the threshold value of the number of flow vectors is determined between 1.28 times and 1.34 times the mean number of flow vectors.

[0089] Specifically, the process of screening potential diffusion nodes to determine effective diffusion nodes includes:

[0090] If there is any potential diffusion node whose historical traffic flow characteristics are greater than or equal to the traffic flow characteristic threshold, the potential diffusion node is determined as a valid diffusion node.

[0091] Specifically, the process of predicting the diffusion area based on each effective diffusion node includes:

[0092] Expand the boundary line of the effective diffusion node outward by a reference distance;

[0093] The closed range area formed after the expansion is determined as the diffusion area.

[0094] It can be understood that potential diffusion nodes refer to nodes with more obvious flow characteristics, and traffic flow characteristics refer to the base number of personnel flow within any node range, that is, the number of personnel passing within the node range within a certain period of time. According to the number of infectious disease infected bodies at the node, combined with the historical traffic flow corresponding to the node, a comprehensive analysis can be conducted to determine the flow degree of the node under normal circumstances. At the same time, it can evaluate the scale of the impact of the spread of other non-infected bodies in the same node under the influence of more infectious disease infected bodies;

[0095] Therefore, in implementation, the historical traffic flow characteristics corresponding to the potential diffusion nodes are obtained to determine the mean traffic flow characteristics. The traffic flow characteristic threshold is determined based on the mean traffic flow characteristics. Since the purpose of setting the traffic flow characteristic threshold is to characterize the movement path of infectious disease infected bodies and the impact of the spread of infectious diseases, and the severity of the impact on potential diffusion nodes is too high, the traffic flow characteristic threshold is determined between 1.05 and 1.17 times the mean traffic flow characteristics in implementation.

[0096] The nodes involved in the implementation refer to areas with a smaller coverage area, such as buildings or places. Since infectious diseases spread dynamically, when analyzing the spread of infectious diseases, it is necessary to expand a certain area outward from the node as the center, that is, the diffusion area, and then conduct specific analysis to ensure that the evaluation is of practical significance.

[0097] In practice, the reference distance is predetermined.

[0098] Based on the epidemiological survey data of a single infectious disease transmission, the movement paths of each infectious disease infection body are constructed in the city virtual map to identify effective diffusion nodes, and the average distance between the effective diffusion nodes and the nodes where each new infectious disease infection body is located after the benchmark time is recorded;

[0099] Repeat the above steps to obtain the average of the average distances for each infectious disease transmission, and determine the average as the reference distance.

[0100] Specifically, the process of obtaining the propagation characteristics of each diffusion area within a predetermined time period to determine the propagation diffusion characterization coefficient includes:

[0101] The ratio of the number of new infections to the threshold number of new infections is used as the first diffusion feature;

[0102] The ratio of the symptom highlighting rate to the symptom highlighting rate threshold is used as the second diffusion feature;

[0103] The sum of the first diffusion characteristic and the second diffusion characteristic is determined as the propagation diffusion characterization coefficient.

[0104] During implementation, by obtaining relevant historical data on the spread of infectious diseases, calling the data on the number of new infections and the rate at which symptoms emerge, the average number of new infections and the average rate at which symptoms emerge are determined.

[0105] It is understandable that the premise for discovering infectious diseases is the presence of several infectious disease infections, and there are certain unspecified correlations between the infectious disease infections, such as having been to the same node location. Generally speaking, after a certain period of time, new infections will begin to show adverse physiological reactions due to the destruction of the immune system. The presence of abnormal physiological symptoms in infectious disease infections is determined as symptom emergence, and the symptom emergence rate reflects the severity of the spread of infectious diseases to a certain extent.

[0106] The threshold for the number of new infections and the threshold for the rate at which symptoms emerge are determined based on the mean number of new infections and the mean rate at which symptoms emerge, respectively. Since the purpose of setting the above two thresholds in implementation is to characterize the situation where the number of new infections is too large and the degree of infection and damage caused by infectious diseases to infected bodies is too serious, in implementation, the threshold for the number of new infections is determined between 1.02 and 1.12 times the mean number of new infections, and the threshold for the rate at which symptoms emerge is determined between 1.13 and 1.21 times the mean rate at which symptoms emerge.

[0107] Specifically, the process of evaluating the diffusion level corresponding to the diffusion area includes,

[0108] Presetting the corresponding relationship between the diffusion level and the propagation diffusion characterization coefficient interval;

[0109] Determine the propagation diffusion characterization coefficient interval to which the propagation diffusion characterization coefficient corresponding to the diffusion area belongs;

[0110] Among them, the diffusion level corresponds to the propagation diffusion characterization coefficient interval one by one.

[0111] In practice, the diffusion level of each diffusion area is determined in the following manner:

[0112] Divide the propagation diffusion characterization coefficient into three preset intervals and set three levels of diffusion levels;

[0113] If the propagation diffusion characterization coefficient corresponding to the diffusion area is within the first preset interval [4.78, +∞), the diffusion area is determined as the first diffusion level;

[0114] If the propagation diffusion characterization coefficient corresponding to the diffusion area is within the second preset interval [2.35, 4.78), the diffusion area is determined as the second diffusion level;

[0115] If the propagation diffusion characterization coefficient corresponding to the diffusion area is within a third preset interval (0, 2.35), the diffusion area is determined to be a third diffusion level;

[0116] The higher the diffusion level of the diffusion area, the higher the degree of propagation diffusion of the diffusion area.

[0117] The embodiment of the present invention determines the potential diffusion nodes that may become the further concentrated spread of infectious diseases in the future according to the movement paths corresponding to the infectious disease infected bodies contained in each overlapping activity node. At the same time, according to the historical traffic flow data of the potential diffusion nodes, it can characterize the personnel flow coverage and the severity of the infectious disease spread that may be caused by the influence of the potential diffusion nodes, so as to determine the effective diffusion nodes. For example, if the area where any infectious disease infected body flows after leaving any overlapping activity node is an area with low traffic flow, then the spread impact generated in this case will be relatively small; on the contrary, if the flow area is an area with high traffic flow, the spread impact generated will show a significant increasing trend, and the potential more seriously affected will be When the diffusion node is identified as an effective diffusion node, targeted analysis is carried out. Since the area covered by the effective diffusion node is relatively small, and the spread of infectious diseases is dynamic, the area range of the effective diffusion node is appropriately expanded when analyzing the degree of transmission to characterize the dynamic degree of flow of infectious disease infected bodies and the degree of flow coverage. Therefore, the effective diffusion node is expanded, and a larger area with data analysis value is planned. Monitoring the number of new infections and the rate of symptom emergence in the area within a certain period of time can, to a certain extent, characterize the real-time and dynamic spread speed and intensity of infectious diseases in the area. The impact of the above characteristics is quantified based on the propagation and diffusion characterization coefficient, and the development trend of the spread of infectious diseases is accurately grasped.

[0118] Specifically, the enlargement ratio is determined based on the node categories of peripheral overlapping active nodes, including,

[0119] The enlargement ratio corresponds one-to-one with the node categories of the peripheral overlapping activity nodes;

[0120] The node categories include living areas, commercial areas, and industrial areas;

[0121] It can be understood that in urban construction, the nature and functions of the buildings or places contained in each district are to meet various life needs. According to different life needs, the population flow base of each building or place is also different accordingly. Therefore, the distribution size of the population flow base of the two node categories divided in implementation is as follows: living area > commercial area > industrial area.

[0122] During implementation, the corresponding expansion ratio for living areas is 1.5 times the benchmark expansion ratio, the commercial area adopts the benchmark expansion ratio, and the industrial area adopts 0.5 times the expansion ratio.

[0123] The base expansion ratio is determined in advance, where:

[0124] Based on the epidemiological survey data of a single infectious disease transmission, the movement paths of each infectious disease infection body are constructed in the city virtual map, so as to construct the peripheral closed areas corresponding to different times based on the peripheral overlapping activity nodes, and determine the increase ratio of the peripheral closed areas after the benchmark time.

[0125] Repeat the above steps to obtain the average increase ratio for each infectious disease transmission, and determine the average increase ratio as the benchmark expansion ratio.

[0126] The process of constructing diffusion regions based on the enlargement ratio includes,

[0127] The peripheral overlapping active nodes are connected to obtain a closed area, and the closed area is enlarged by a corresponding enlargement ratio.

[0128] If the infectious disease transmission assessment method of the present invention is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention, and the aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0129] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

Claims

1. A method for evaluating the spread of infectious diseases, characterized in that: include: Constructing movement paths for each infectious agent in a virtual city map, and uploading the movement paths and symptom text data of the infectious agent to an epidemic investigation database; Obtaining the movement paths of the infectious bodies of each of the infectious diseases, marking a number of overlapping activity nodes in the virtual city map, determining the distribution characteristics of the overlapping activity nodes, and calculating the discrete distribution characterization coefficient based on the distribution characteristics to divide the regional flow categories; Calling the data in the epidemiological investigation database, analyzing and evaluating the spread of infectious diseases according to the regional flow categories, including: Determine the flow characteristics of each infectious body at each overlapping activity node, identify potential diffusion nodes, screen the potential diffusion nodes according to the historical traffic flow characteristics corresponding to the potential diffusion nodes to obtain effective diffusion nodes, predict the diffusion area based on each effective diffusion node, obtain the propagation characteristics of each diffusion area within a predetermined time period to determine the propagation diffusion characterization coefficient, and evaluate the diffusion level of the corresponding diffusion area; Or, determining peripheral overlapping active nodes, determining an expansion ratio based on the node categories of the peripheral overlapping active nodes, and constructing a diffusion area based on the expansion ratio; The distribution characteristics include the number of overlapping activity nodes and the average distance between overlapping activity nodes, and the transmission characteristics include the number of new infections and the symptom emergence rate; The process of calculating the discrete distribution characterization coefficient based on the distribution characteristics includes: The ratio of the quantity threshold to the quantity of overlapping active nodes is used as a first distribution feature; The ratio of the average distance between each overlapping activity node to the distance threshold is used as the second distribution feature; Determine a discrete distribution characterization coefficient by taking a weighted sum of the first distribution feature and the second distribution feature; Analyze and evaluate the spread of infectious diseases, including: If the overlapping activity nodes are of the regional flow dispersion category, the flow characteristics of each infectious body in each overlapping activity node are determined, potential diffusion nodes are identified, and potential diffusion nodes are screened according to the historical traffic flow characteristics corresponding to the potential diffusion nodes to obtain effective diffusion nodes, and the diffusion area is predicted based on each effective diffusion node. The propagation characteristics of each diffusion area within a predetermined time period are obtained to determine the propagation diffusion characterization coefficient, and the diffusion level of the corresponding diffusion area is evaluated; If the overlapping activity nodes are of the regional flow aggregation type, then determining the peripheral overlapping activity nodes, determining the expansion ratio based on the node types of the peripheral overlapping activity nodes, and constructing the diffusion area based on the expansion ratio; The process of obtaining the propagation characteristics of each diffusion area within a predetermined time period to determine the propagation diffusion characterization coefficient includes: The ratio of the number of new infections to the threshold number of new infections is used as the first diffusion feature; The ratio of the symptom highlighting rate to the symptom highlighting rate threshold is used as the second diffusion feature; The sum of the first diffusion characteristic and the second diffusion characteristic is determined as the propagation diffusion characterization coefficient.

2. The infectious disease transmission assessment method according to claim 1, characterized in that: The geographical mobility categories include: If the discrete distribution characterization coefficient is greater than or equal to the discrete distribution characterization coefficient threshold, classifying the overlapping activity nodes into a geographical flow dispersion category; If the discrete distribution characterization coefficient is less than the discrete distribution characterization coefficient threshold, the overlapping activity nodes are classified into a regional flow aggregation category.

3. The infectious disease transmission assessment method according to claim 1, characterized in that: The process of identifying potential diffusion nodes includes, Obtain the flow vector of each infectious body at each overlapping activity node; The overlapping activity nodes that meet the diffusion benchmark conditions are identified as potential diffusion nodes; The diffusion benchmark condition is that the number of corresponding flow vectors in any direction in the overlapping activity nodes is greater than or equal to a flow vector number threshold.

4. The infectious disease transmission assessment method according to claim 1, characterized in that: The process of screening potential diffusion nodes to determine effective diffusion nodes includes: If there is any potential diffusion node whose historical traffic flow characteristics are greater than or equal to the traffic flow characteristic threshold, the potential diffusion node is determined as a valid diffusion node.

5. The infectious disease transmission assessment method according to claim 4, characterized in that: The process of predicting the diffusion area based on each effective diffusion node includes: Expand the boundary line of the effective diffusion node outward by a reference distance; The closed range area formed after the expansion is determined as the diffusion area.

6. The infectious disease transmission assessment method according to claim 1, characterized in that: The process of assessing the diffusion level corresponding to the diffusion area includes, Presetting the corresponding relationship between the diffusion level and the propagation diffusion characterization coefficient interval; Determine the propagation diffusion characterization coefficient interval to which the propagation diffusion characterization coefficient corresponding to the diffusion area belongs; Among them, the diffusion level corresponds to the propagation diffusion characterization coefficient interval one by one.

7. The infectious disease transmission assessment method according to claim 1, characterized in that: The expansion ratio is determined based on the node category of the peripheral overlapping active nodes, including, The enlargement ratio corresponds one-to-one with the node categories of the peripheral overlapping activity nodes; The node categories include living areas, commercial areas and industrial areas.

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