Respiratory infectious disease control effect evaluation system and method based on feature analysis

Abstract

The invention discloses a respiratory infectious disease control effect evaluation system and method based on feature analysis, and relates to the technical field of control effect evaluation, and the method comprises the steps: evaluating the respiratory infectious disease transmission change condition according to historical respiratory infectious disease transmission data and current respiratory infectious disease transmission data, evaluating the human traffic change condition according to the historical human traffic data and the current human traffic data, and evaluating the change condition of the respiratory tract infection latency period according to the probability of the historical respiratory tract infection latency period and the probability of the current respiratory tract infection latency period; predicting the infection condition of the respiratory infectious diseases before control according to the transmission change condition of the respiratory infectious diseases, the human flow rate change condition and the change condition of the respiratory infection incubation period, and evaluating the control effect of the respiratory infectious diseases according to the actual infection condition of the respiratory infectious diseases after control and the predicted infection condition of the respiratory infectious diseases before control. And the accuracy of respiratory infectious disease control effect evaluation is improved.

Description

Technical Field

[0001] The present application relates to the field of control effect evaluation technology, and in particular to a system and method for evaluating the control effect of respiratory infectious diseases based on feature analysis. Background Technology

[0002] Respiratory infectious diseases refer to infectious diseases caused by pathogens invading the human body's nasal cavity, throat, trachea and bronchus. Since respiratory infectious diseases are relatively hidden in their spread, the evaluation of the control effect of respiratory infectious diseases is relatively complicated; The evaluation of the control effect of respiratory infectious diseases in related technologies is mostly to compare the number of cases and transmission rate before and after the implementation of intervention measures, and analyze the relationship between intervention measures and case reduction, but lacks consideration of the probability of respiratory infection under the influence of environmental pollution and one's own physical condition, so it is impossible to comprehensively evaluate the control effect by combining changes in infectious diseases, changes in human flow and changes in the probability of respiratory infection, thereby reducing the accuracy of the evaluation of the control effect of respiratory infectious diseases.

[0003] In order to solve the above problems, this application provides a respiratory infectious disease control effect evaluation system and method based on feature analysis. SUMMARY OF THE INVENTION

[0004] The main purpose of this application is to provide a system and method for evaluating the control effect of respiratory infectious diseases based on feature analysis, aiming to solve the technical problem of low accuracy in evaluating the control effect of respiratory infectious diseases in the existing technology.

[0005] To achieve the above purpose, the present application proposes a method for evaluating the control effect of respiratory infectious diseases based on feature analysis, and the method for evaluating the control effect of respiratory infectious diseases based on feature analysis includes: S1. Evaluate the changes in the spread of respiratory infectious diseases based on historical and current data on the spread of respiratory infectious diseases; S2. Evaluate the change of passenger flow based on historical passenger flow data and current passenger flow data; S3. Obtain the historical probability of being in the latent period of respiratory infection and the current probability of being in the latent period of respiratory infection, and evaluate the change of the latent period of respiratory infection based on the historical probability of being in the latent period of respiratory infection and the current probability of being in the latent period of respiratory infection; S4. Comprehensively predict the transmission of respiratory infectious diseases before control based on changes in the spread of respiratory infectious diseases, changes in human traffic and changes in the incubation period of respiratory infections; S5. Evaluate the control effect of respiratory infectious diseases based on the actual infection situation of respiratory infectious diseases after control and the predicted infection situation of respiratory infectious diseases before control.

[0006] Specifically, S1 includes the following specific steps:​ S101, obtaining historical respiratory infectious disease transmission data and current respiratory infectious disease transmission data, wherein the historical respiratory infectious disease transmission data includes historical transmission rate, historical incubation period and historical aerosol stability, and the current respiratory infectious disease transmission data includes current transmission rate, current incubation period and current aerosol stability; S102. Obtain historical respiratory infectious disease transmission anomalies based on historical transmission rate, historical incubation period and historical aerosol stability; S103. Obtain the current abnormal value of respiratory infectious disease transmission based on the current transmission rate, current incubation period and current aerosol stability; S104, subtract the current respiratory infectious disease transmission abnormal value from the historical respiratory infectious disease transmission abnormal value to obtain the respiratory infectious disease transmission abnormal difference value, and then divide the respiratory infectious disease transmission abnormal difference value by the historical respiratory infectious disease transmission abnormal value to obtain the respiratory infectious disease transmission change rate.

[0007] Specifically, S2 includes the following specific steps: S201, obtaining historical human flow data and current human flow data, wherein the historical human flow data includes historical human flow and historical crowd density, and the current human flow data includes current human flow and current crowd density; S202, obtaining historical human flow abnormality values ​​according to historical human flow and historical crowd density; S203, obtaining the current abnormal value of human flow according to the current human flow and the current crowd density; S204, subtract the current abnormal flow value from the historical abnormal flow value to obtain the abnormal flow difference, and then divide the abnormal flow difference by the historical abnormal flow value to obtain the change rate of the flow.

[0008] Specifically, S3 includes the following specific steps: S301, obtaining the historical probability of being in the latent period of respiratory tract infection and the current probability of being in the latent period of respiratory tract infection; S302, subtract the current probability of being in the latent period of respiratory infection from the historical probability of being in the latent period of respiratory infection to obtain the difference of the probability of the latent period of infection, and then divide the difference of the probability of the latent period of infection by the historical probability of being in the latent period of respiratory infection to obtain the change rate of the latent period of respiratory infection.

[0009] Specifically, the S301 includes the following specific steps: a. Obtain individual basic data, which includes age and basic medical history, and obtain individual health abnormal values ​​based on age and basic medical history; b. Obtain air pollution data, which includes PM2.5 concentration; c. Obtain the number of respiratory infectious diseases infected in the group within the set range; d. Obtain the probability of an individual being in the latent period of respiratory infection based on individual health abnormalities, PM2.5 concentration and group respiratory infectious disease infection data; e. Obtain the average value of the probability that an individual is in the latent period of respiratory infection in history as the probability of being in the latent period of respiratory infection in history, and obtain the average value of the probability that an individual is in the latent period of respiratory infection in the current period as the probability of being in the latent period of respiratory infection in the current period.

[0010] Specifically, the S4 includes the following specific steps: The transmission rate of respiratory infectious diseases before control is predicted by combining the change rate of respiratory infectious diseases transmission, the change rate of human flow and the change rate of the latent period of respiratory infections.

[0011] Specifically, S5 includes the following specific steps: S501, obtain the actual infection rate of respiratory infectious diseases after control, subtract the predicted infection rate of respiratory infectious diseases before control from the actual infection rate of respiratory infectious diseases after control to obtain the difference in infection rate of infectious diseases, and then divide the difference in infection rate of infectious diseases by the predicted infection rate of respiratory infectious diseases before control to obtain the infectious disease control rate; S502, obtain the comparison result of the infectious disease control rate and the preset expected infectious disease control rate. If the infectious disease control rate is greater than or equal to the preset expected infectious disease control rate, it is judged that the control of respiratory infectious diseases has achieved the expected effect. If the infectious disease control rate is less than the preset expected infectious disease control rate, it is judged that the control of respiratory infectious diseases has not achieved the expected effect.

[0012] In addition, to achieve the above purpose, the present application also proposes a respiratory infectious disease control effect evaluation system based on feature analysis, and the respiratory infectious disease control effect evaluation system based on feature analysis includes: Infectious disease transmission change assessment module, used to assess the change rate of respiratory infectious disease transmission based on historical respiratory infectious disease transmission data and current respiratory infectious disease transmission data; The crowd flow change evaluation module is used to evaluate the crowd flow change rate based on historical crowd flow data and current crowd flow data; Infection incubation period change assessment module, used to assess the change rate of the respiratory infection incubation period based on the historical probability of being in the respiratory infection incubation period and the current probability of being in the respiratory infection incubation period; The infection rate prediction module before control is used to predict the infection rate of respiratory infectious diseases before control by comprehensively considering the change rate of respiratory infectious disease transmission, the change rate of human flow and the change rate of the incubation period of respiratory infection; The control effect evaluation module is used to evaluate the control effect of respiratory infectious diseases based on the actual infection rate of respiratory infectious diseases after control and the predicted infection rate of respiratory infectious diseases before control.​

[0013] In addition, to achieve the above purpose, the present application also proposes an electronic device, the device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the respiratory infectious disease control effect evaluation method based on feature analysis as described above.

[0014] In addition, to achieve the above purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and stores a computer program on the storage medium. When the computer program is executed by the processor, the steps of the respiratory infectious disease control effect evaluation method based on feature analysis as described above are implemented.

[0015] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the respiratory infectious disease control effect evaluation method based on feature analysis as described above are implemented.

[0016] Compared with the prior art, this application evaluates the changes in the spread of respiratory infectious diseases based on historical respiratory infectious disease spread data and current respiratory infectious disease spread data, evaluates the changes in human flow based on historical human flow data and current human flow data, evaluates the changes in the latent period of respiratory infection based on the historical probability of being in the latent period of respiratory infection and the current probability of being in the latent period of respiratory infection, predicts the infection of respiratory infectious diseases before control based on the changes in the spread of respiratory infectious diseases, changes in human flow and changes in the latent period of respiratory infection, evaluates the control effect of respiratory infectious diseases based on the actual infection of respiratory infectious diseases after control and the predicted infection of respiratory infectious diseases before control, and analyzes the combined impact of changes in infectious disease spread, changes in human flow and changes in the latent period when evaluating the control effect of respiratory infectious diseases, and considers the probability of respiratory infection under the influence of environmental pollution and one's own physical condition, thereby improving the accuracy of the evaluation of the control effect of respiratory infectious diseases. Brief Description of the Figures

[0017] The accompanying drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present application, and together with the description are used to explain the principles of the present application.

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor.

[0019] Figure 1Schematic diagram of the evaluation method for the control effect of respiratory infectious diseases in this application; Figure 2 Schematic diagram of the S1 process of the evaluation method for the control effect of respiratory infectious diseases in this application; Figure 3 Schematic diagram of the S2 process of the evaluation method for the control effect of respiratory infectious diseases in this application; Figure 4 Schematic diagram of the S301 process of the evaluation method for the control effect of respiratory infectious diseases in this application; Figure 5 Schematic diagram of the structure of the evaluation system for the control effect of respiratory infectious diseases in this application. Specific implementation manners

[0020] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of this application and are not used to limit this application.

[0021] For a better understanding of the technical solutions of this application, the following will be described in detail in combination with the accompanying drawings of the specification and specific implementation manners.

[0022] Based on this, the embodiments of this application provide an evaluation method for the control effect of respiratory infectious diseases based on feature analysis. Refer to Figure 1 , the evaluation method for the control effect of respiratory infectious diseases based on feature analysis includes the following specific steps: S1. Evaluate the change in the transmission of respiratory infectious diseases based on historical respiratory infectious disease transmission data and current respiratory infectious disease transmission data; Refer to Figure 2 , in this embodiment, S1 includes the following specific steps: S101. Obtain historical respiratory infectious disease transmission data and current respiratory infectious disease transmission data. The historical respiratory infectious disease transmission data includes historical transmission rate, historical incubation period, and historical aerosol stability. The current respiratory infectious disease transmission data includes current transmission rate, current incubation period, and current aerosol stability. In specific implementation, the transmission rate can be obtained by multiplying the contact rate by the infection rate, or by using the SEIR model to fit the actual data using methods such as maximum likelihood estimation and Bayesian estimation to calculate the transmission rate. The incubation period is obtained by fitting the distribution of the incubation period to the exposure time and onset time data using statistical methods such as gamma distribution and log-normal distribution, and extracting the average value of the incubation period. The aerosol stability is obtained by collecting air samples in the natural environment, detecting the concentration change of pathogens, and calculating the half-life and survival conditions of pathogens in the aerosol; S102. Obtain the historical respiratory infectious disease transmission outliers based on the historical transmission rate, historical incubation period, and historical aerosol stability. In specific implementation, the respiratory infectious disease transmission outliers can be obtained by the following formula: , where, is the propagation rate obtained, is the standard transmission rate after the spread of respiratory infectious diseases is controlled, is the incubation period for acquisition, is the standard incubation period after the spread of respiratory infectious diseases is controlled, To obtain the aerosol stability, is the standard aerosol stability after the spread of respiratory infectious diseases is controlled. In the above formula, the abnormal degree of respiratory infectious disease transmission is proportional to the transmission rate and aerosol stability, and inversely proportional to the incubation period. The standard transmission rate, standard incubation period and standard aerosol stability can be obtained through several experimental scenarios. When the transmission of respiratory infectious diseases in the experimental scenarios is maintained within the set controlled range, the measured transmission rate, incubation period and aerosol stability are averaged as the standard transmission rate, standard incubation period and standard aerosol stability; S103. Obtain the current abnormal value of respiratory infectious disease transmission based on the current transmission rate, current incubation period and current aerosol stability; S104, subtract the current respiratory infectious disease transmission abnormal value from the historical respiratory infectious disease transmission abnormal value to obtain the respiratory infectious disease transmission abnormal difference value, and then divide the respiratory infectious disease transmission abnormal difference value by the historical respiratory infectious disease transmission abnormal value to obtain the respiratory infectious disease transmission change rate.

[0023] S2. Evaluate the change of passenger flow based on historical passenger flow data and current passenger flow data; Reference Figure 3 , in this embodiment, S2 includes the following specific steps: S201, obtaining historical and current human flow data, the historical human flow data including historical human flow and historical crowd density, the current human flow data including current human flow and current crowd density. In specific implementation, human flow can be monitored by installing sensors or counters at the entrance, and crowd density is obtained by dividing the monitoring area into several small areas, calculating the crowd density of each small area and taking the average value; S202, according to the historical flow of people and the historical crowd density, the abnormal value of the historical flow of people is obtained. In the specific implementation, the abnormal value of the flow of people can be obtained by the following formula: , where To obtain the flow of people, is the standard flow of people, is the obtained crowd density, is the standard crowd density corresponding to the standard crowd flow. In the above formula, the abnormal degree of crowd flow is proportional to the crowd flow and crowd density. The standard crowd flow is obtained by the number of people accommodated under standard conditions of the venue, and the standard crowd density is obtained by dividing the standard crowd flow by the venue area; S203, obtaining the current abnormal value of human flow according to the current human flow and the current crowd density; S204, subtract the current abnormal flow value from the historical abnormal flow value to obtain the abnormal flow difference, and then divide the abnormal flow difference by the historical abnormal flow value to obtain the change rate of the flow.

[0024] S3. Obtain the historical probability of being in the latent period of respiratory infection and the current probability of being in the latent period of respiratory infection, and evaluate the change of the latent period of respiratory infection based on the historical probability of being in the latent period of respiratory infection and the current probability of being in the latent period of respiratory infection; In this embodiment, S3 includes the following specific steps: S301, obtaining the historical probability of being in the latent period of respiratory tract infection and the current probability of being in the latent period of respiratory tract infection; S302, subtract the current probability of being in the latent period of respiratory infection from the historical probability of being in the latent period of respiratory infection to obtain the difference of the probability of the latent period of infection, and then divide the difference of the probability of the latent period of infection by the historical probability of being in the latent period of respiratory infection to obtain the change rate of the latent period of respiratory infection.

[0025] Reference Figure 4 , in this embodiment, S301 includes the following specific steps: a. Obtain individual basic data, including age and basic medical history. Obtain individual health abnormal values ​​based on age and basic medical history. In specific implementation, collect individual age and basic medical history, divide them into youth, middle-aged and elderly according to age, and divide them into mild, moderate and severe according to the severity of basic medical history. Respiratory disease experts assign points to each dimension and make weight judgments on age and basic medical history. The weighted total score obtained by multiplying the score of each dimension by the corresponding weight is the individual health abnormal value; b. Obtain air pollution data, including PM2.5 concentration; c. Obtain the number of respiratory infectious diseases infected in the group within the set range; d. According to individual health abnormalities, PM2.5 concentration and group respiratory infectious disease infection data, the probability of an individual being in the latent period of respiratory infection can be obtained. In specific implementation, the probability of an individual being in the latent period of respiratory infection can be obtained by the following formula: , where is the individual health abnormal value, is the PM2.5 concentration, is the standard PM2.5 concentration, where the standard PM2.5 concentration is set at 75μg / m³, is the propagation rate, is the respiratory rate, which is obtained based on the average of the individual's historically measured respiratory rates. is the degree of virus filtration, monitoring whether the individual is wearing a mask, if not, judging , if worn, then , is the ventilation rate. The ventilation rate can be measured by using an anemometer at a set measurement point. The measured wind speed is multiplied by the cross-sectional area of ​​the air duct to obtain the ventilation volume per unit time. is the number of respiratory infectious diseases infected in the group, is the total number of groups, is an exponential function with e as base; e. Obtain the average value of the probability that an individual is in the latent period of respiratory infection in history as the probability of being in the latent period of respiratory infection in history, and obtain the average value of the probability that an individual is in the latent period of respiratory infection in the current period as the probability of being in the latent period of respiratory infection in the current period.

[0026] S4. Comprehensively predict the transmission of respiratory infectious diseases before control based on changes in the spread of respiratory infectious diseases, changes in human traffic and changes in the incubation period of respiratory infections; In this embodiment, S4 includes the following specific steps: The transmission rate of respiratory infectious diseases before control is predicted by combining the change rate of respiratory infectious diseases, the change rate of human flow and the change rate of the latent period of respiratory infections. In specific implementation, the infection rate of respiratory infectious diseases before control can be obtained by the following formula: , where is the initial respiratory infectious disease infection rate, is the change rate of transmission of respiratory infectious diseases, Change rate of human traffic, is the change rate in the incubation period of respiratory infection, is the propagation change weight, The weight of human traffic change, is the weight of the change in the incubation period. The distribution of the weight of the change in transmission, the weight of the change in human flow and the weight of the change in the incubation period is made by experts in respiratory diseases based on historical relevant respiratory infection data and then they analyze the impact of transmission, human flow and incubation period respectively.

[0027] S5. Evaluate the control effect of respiratory infectious diseases based on the actual infection situation of respiratory infectious diseases after control and the predicted infection situation of respiratory infectious diseases before control.

[0028] In this embodiment, S5 includes the following specific steps: S501, obtain the actual infection rate of respiratory infectious diseases after control, subtract the predicted infection rate of respiratory infectious diseases before control from the actual infection rate of respiratory infectious diseases after control to obtain the difference in infection rate of infectious diseases, and then divide the difference in infection rate of infectious diseases by the predicted infection rate of respiratory infectious diseases before control to obtain the infectious disease control rate; S502, obtain the comparison result of the infectious disease control rate and the preset expected infectious disease control rate. If the infectious disease control rate is greater than or equal to the preset expected infectious disease control rate, it is judged that the control of respiratory infectious diseases has achieved the expected effect. If the infectious disease control rate is less than the preset expected infectious disease control rate, it is judged that the control of respiratory infectious diseases has not achieved the expected effect.

[0029] It should be noted that the above examples are only used to understand this application and do not constitute a limitation on the respiratory infectious disease control effect evaluation method based on feature analysis of this application. More simple transformations based on this technical concept are all within the scope of protection of this application.

[0030] This application also provides a respiratory infectious disease control effect evaluation system based on feature analysis, see Figure 5 , the respiratory infectious disease control effect evaluation system based on feature analysis includes: Infectious disease transmission change assessment module, used to assess the change rate of respiratory infectious disease transmission based on historical respiratory infectious disease transmission data and current respiratory infectious disease transmission data; The crowd flow change evaluation module is used to evaluate the crowd flow change rate based on historical crowd flow data and current crowd flow data; Infection incubation period change assessment module, used to assess the change rate of the respiratory infection incubation period based on the historical probability of being in the respiratory infection incubation period and the current probability of being in the respiratory infection incubation period; The infection rate prediction module before control is used to predict the infection rate of respiratory infectious diseases before control by comprehensively considering the change rate of respiratory infectious disease transmission, the change rate of human flow and the change rate of the incubation period of respiratory infection; The control effect evaluation module is used to evaluate the control effect of respiratory infectious diseases based on the actual infection rate of respiratory infectious diseases after control and the predicted infection rate of respiratory infectious diseases before control.

[0031] The respiratory infectious disease control effect evaluation system based on feature analysis provided in the present application adopts the respiratory infectious disease control effect evaluation method based on feature analysis in the above-mentioned embodiment, which can solve the technical problem. Compared with the prior art, the beneficial effects of the respiratory infectious disease control effect evaluation system based on feature analysis provided in the present application are the same as the beneficial effects of the respiratory infectious disease control effect evaluation method based on feature analysis provided in the above-mentioned embodiment, and other technical features in the respiratory infectious disease control effect evaluation system based on feature analysis are the same as the features disclosed in the above-mentioned embodiment method, which will not be repeated here.​

[0032] The present application provides an electronic device, which includes: at least one processor; and a memory connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor, so that the at least one processor can execute the respiratory infectious disease control effect evaluation method based on feature analysis in the above-mentioned embodiment 1.

[0033] The electronic device provided by this application adopts the respiratory infectious disease control effect evaluation method based on feature analysis in the above embodiment, which can solve the technical problem. Compared with the prior art, the beneficial effect of the electronic device provided by this application is the same as the beneficial effect of the respiratory infectious disease control effect evaluation method based on feature analysis provided in the above embodiment, and the other technical features in the electronic device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0034] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0035] The above are only specific implementation methods of this application, but the protection scope of this application is not limited to this. Any technician familiar with this technical field can easily think of changes or substitutions within the technical scope disclosed in this application, which should be covered by the protection scope of this application.

[0036] Therefore, the protection scope of this application shall be based on the protection scope of the claims.

[0037] The present application provides a computer-readable storage medium having computer-readable program instructions stored thereon, and the computer-readable program instructions are used to execute the respiratory infectious disease control effect evaluation method based on feature analysis in the above-mentioned embodiment.

[0038] The computer-readable storage medium provided by this application stores computer-readable program instructions for executing the above-mentioned method for evaluating the control effect of respiratory infectious diseases based on feature analysis, which can solve technical problems. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by this application are the same as the beneficial effects of the method for evaluating the control effect of respiratory infectious diseases based on feature analysis provided by the above-mentioned embodiment, and will not be repeated here.

[0039] The present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the above-mentioned method for evaluating the control effect of respiratory infectious diseases based on feature analysis.

[0040] The computer program product provided in this application can solve technical problems. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as the beneficial effects of the respiratory infectious disease control effect evaluation method based on feature analysis provided in the above embodiment, and will not be described in detail here.

[0041] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems and methods according to various embodiments of the present application. Each box in the flowchart or block diagram may represent a module, a program segment, or a part of the code, which contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the boxes may also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession may actually be executed substantially in parallel, and they may sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart may be implemented by a dedicated hardware-based system that performs the specified functions or operations, or may be implemented by a combination of dedicated hardware and computer instructions.

[0042] The above are only some embodiments of the present application, and do not limit the patent scope of the present application. All equivalent structural changes made by using the contents of the present application specification and drawings under the technical concept of the present application, or directly / indirectly applied in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A method for evaluating the control effect of respiratory infectious diseases based on feature analysis, characterized in that: The specific steps include: S1. Evaluate changes in the spread of respiratory infectious diseases based on historical and current data on the spread of respiratory infectious diseases; S2. Evaluate the change of passenger flow based on historical passenger flow data and current passenger flow data; S3. Obtain the historical probability of being in the latent period of respiratory infection and the current probability of being in the latent period of respiratory infection, and evaluate the change of the latent period of respiratory infection according to the historical probability of being in the latent period of respiratory infection and the current probability of being in the latent period of respiratory infection; S4. Comprehensively predict the transmission of respiratory infectious diseases before control based on changes in the spread of respiratory infectious diseases, changes in human traffic, and changes in the incubation period of respiratory infections; S5. Evaluate the control effect of respiratory infectious diseases based on the actual infection situation of respiratory infectious diseases after control and the predicted infection situation of respiratory infectious diseases before control.

2. The method for evaluating the control effect of respiratory infectious diseases based on feature analysis according to claim 1, characterized in that: The S1 comprises the following specific steps: S101. Acquire historical respiratory infectious disease transmission data and current respiratory infectious disease transmission data, wherein the historical respiratory infectious disease transmission data includes historical transmission rate, historical incubation period and historical aerosol stability, and the current respiratory infectious disease transmission data includes current transmission rate, current incubation period and current aerosol stability; S102. Obtain historical respiratory infectious disease transmission anomalies based on historical transmission rates, historical incubation periods, and historical aerosol stability; S103, obtaining the current respiratory infectious disease transmission abnormality value according to the current transmission rate, the current incubation period and the current aerosol stability; S104. Subtract the historical abnormal value of respiratory infectious disease transmission from the current abnormal value of respiratory infectious disease transmission to obtain the abnormal difference of respiratory infectious disease transmission, and then divide the abnormal difference of respiratory infectious disease transmission by the historical abnormal value of respiratory infectious disease transmission to obtain the change rate of respiratory infectious disease transmission.

3. The method for evaluating the control effect of respiratory infectious diseases based on feature analysis according to claim 2, characterized in that: The S2 comprises the following specific steps: S201, obtaining historical human flow data and current human flow data, wherein the historical human flow data includes historical human flow and historical crowd density, and the current human flow data includes current human flow and current crowd density; S202, obtaining historical human flow abnormality values ​​according to historical human flow and historical crowd density; S203, obtaining a current abnormal value of human flow according to the current human flow and the current crowd density; S204: Subtract the current abnormal human flow value from the historical abnormal human flow value to obtain the abnormal human flow difference, and then divide the abnormal human flow difference by the historical abnormal human flow value to obtain the human flow change rate.

4. The method for evaluating the control effect of respiratory infectious diseases based on feature analysis according to claim 3, characterized in that: The S3 comprises the following specific steps: S301, obtaining the historical probability of being in the latent period of respiratory tract infection and the current probability of being in the latent period of respiratory tract infection; S302, subtract the current probability of being in the latent period of respiratory infection from the historical probability of being in the latent period of respiratory infection to obtain the difference of the probability of infection latent period, and then divide the difference of the probability of infection latent period by the historical probability of being in the latent period of respiratory infection to obtain the change rate of the latent period of respiratory infection.

5. The method for evaluating the control effect of respiratory infectious diseases based on feature analysis according to claim 4, characterized in that: The S301 includes the following specific steps: a. Obtain individual basic data, including age and basic medical history, and obtain individual health abnormality values ​​based on age and basic medical history; b. Obtaining air pollution data, wherein the air pollution data includes PM2.5 concentration; c. Obtain the number of respiratory infectious diseases infected in a group within a set range; d. Obtain the probability that an individual is in the latent period of respiratory infection based on individual health abnormalities, PM2.5 concentration and group respiratory infectious disease infection data; e. Obtain the average value of the historical probabilities that individuals are in the latent period of respiratory infection as the historical probability of being in the latent period of respiratory infection, and obtain the average value of the current probability that individuals are in the latent period of respiratory infection as the current probability of being in the latent period of respiratory infection.

6. The method for evaluating the control effect of respiratory infectious diseases based on feature analysis according to claim 5, characterized in that: The S4 comprises the following specific steps: The infection rate of respiratory infectious diseases before control is predicted by combining the change rate of respiratory infectious disease transmission, the change rate of human flow and the change rate of the incubation period of respiratory infection.

7. The method for evaluating the control effect of respiratory infectious diseases based on feature analysis according to claim 6, characterized in that: The S5 comprises the following specific steps: S501, obtaining the actual infection rate of the respiratory infectious disease after control, subtracting the predicted infection rate of the respiratory infectious disease before control from the actual infection rate of the respiratory infectious disease after control to obtain the difference in infection rate of the infectious disease, and then dividing the difference in infection rate of the infectious disease by the predicted infection rate of the respiratory infectious disease before control to obtain the infectious disease control rate; S502. Obtain the comparison result between the infectious disease control rate and the preset expected infectious disease control rate. If the infectious disease control rate is greater than or equal to the preset expected infectious disease control rate, it is judged that the control of respiratory infectious diseases has achieved the expected effect. If the infectious disease control rate is less than the preset expected infectious disease control rate, it is judged that the control of respiratory infectious diseases has not achieved the expected effect.

8. A respiratory infectious disease control effect evaluation system based on feature analysis, used to implement the respiratory infectious disease control effect evaluation method based on feature analysis as claimed in any one of claims 1 to 7, characterized in that: include: An infectious disease transmission change assessment module is used to assess the change rate of respiratory infectious disease transmission based on historical respiratory infectious disease transmission data and current respiratory infectious disease transmission data; A crowd flow change evaluation module is used to evaluate the crowd flow change rate based on historical crowd flow data and current crowd flow data; An infection latent period change assessment module is used to assess the change rate of the respiratory infection latent period based on the historical probability of being in the respiratory infection latent period and the current probability of being in the respiratory infection latent period; The infection rate prediction module before control is used to predict the infection rate of respiratory infectious diseases before control by comprehensively considering the change rate of respiratory infectious disease transmission, the change rate of human flow and the change rate of the incubation period of respiratory infection; The control effect evaluation module is used to evaluate the control effect of respiratory infectious diseases based on the actual infection rate of respiratory infectious diseases after control and the predicted infection rate of respiratory infectious diseases before control.

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