Infectious disease data inspection method, system and device and storable medium

Abstract

The invention discloses an infectious disease data inspection method, system and device and a storable medium, and relates to the technical field of infectious disease prevention and control, and the method comprises the following specific steps: building a dynamic risk index system: comprehensively considering morbidity, propagation speed and crowd susceptibility indexes, building the dynamic risk index system, along with the development of infectious diseases and the appearance of new data, indexes are continuously adjusted and optimized, and the weights of the indexes are dynamically adjusted, so that the current infectious disease risk level is reflected more accurately; through mutual cooperation of the dynamic risk index system and the dynamic inspection strategy, the inspection strategy is flexibly adjusted according to factors such as epidemic seasons and crowd flow conditions of infectious diseases so as to adapt to different situations and prevention and control requirements of the infectious diseases, so that the system can more effectively cope with various infectious diseases, and the safety of the infectious diseases is improved. And the pertinence and effectiveness of prevention and control measures are improved, so that the public health is better guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of infectious disease prevention and control, and specifically to an infectious disease data inspection method, system, equipment and storable medium. Background Art

[0002] Infectious disease prevention and control is an important task in the field of public health. It plays a vital role in protecting public health and maintaining social stability. With the acceleration of globalization and urbanization, population mobility is becoming more frequent, and the speed and scope of the spread of infectious diseases are also expanding, bringing unprecedented challenges to infectious disease prevention and control. In order to effectively respond to this challenge, it is necessary to use advanced technical means and methods to improve the efficiency and accuracy of infectious disease data inspections, timely discover potential risks and take effective prevention and control measures.

[0003] There are obvious limitations in traditional infectious disease data inspection methods. On the one hand, these methods often rely on static inspection processes and fixed indicators, and cannot be flexibly adjusted according to the actual development of infectious diseases and emerging data, which leads to low inspection efficiency and difficulty in fully and accurately grasping the dynamics of infectious diseases. On the other hand, traditional methods lack a dynamic risk assessment mechanism and cannot dynamically adjust inspection strategies according to factors such as the epidemic season of infectious diseases and population mobility, thereby delaying the best time to implement prevention and control measures. In addition, traditional methods also have shortcomings in processing large-scale data and realizing real-time monitoring and early warning, and it is difficult to meet the current needs of infectious disease prevention and control work.

[0004] In response to the above problems, it is necessary to optimize the current infectious disease data inspection methods, systems, equipment and storable media, and build a dynamic risk indicator system by comprehensively considering multi-dimensional indicators such as incidence rate, transmission speed, and population susceptibility. Indicators should be continuously adjusted and optimized according to the development of infectious diseases and the emergence of new data to achieve more accurate infectious disease risk assessment and early warning. Therefore, it is of great significance to develop an infectious disease data inspection method, system, equipment and storable medium that can comprehensively realize the above characteristics. Summary of the invention

[0005] The purpose of the present invention is to make up for the shortcomings of the prior art and to provide an infectious disease data inspection method, system, equipment and storable medium. It can build a dynamic risk indicator system by comprehensively considering multi-dimensional indicators such as incidence rate, transmission speed, and population susceptibility, and continuously adjust and optimize indicators according to the development of infectious diseases and the emergence of new data, dynamically adjust the weight of each indicator, and at the same time, implement a dynamic inspection strategy, dynamically adjust the frequency and focus of inspections according to factors such as the epidemic season of infectious diseases and population flow, and adopt an adaptive inspection algorithm to automatically adjust inspection parameters when data changes, thereby increasing the inspection intensity of related data.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: In the first aspect, a method for inspecting infectious disease data comprises the following specific steps:

[0007] Establish a dynamic risk indicator system: comprehensively consider the incidence rate, transmission speed and population susceptibility indicators, build a dynamic risk indicator system, continuously adjust and optimize the indicators as the infectious disease develops and new data emerges, and dynamically adjust the weights of each indicator to more accurately reflect the current infectious disease risk level;

[0008] Implement dynamic inspection strategy: Based on the feedback of the dynamic risk indicator system, the inspection frequency and focus are adjusted dynamically according to the epidemic season of infectious diseases and the flow of people. During the high-incidence season of infectious diseases, during major events, or when risk indicators show increased risks, the number and scope of inspections are increased to enable timely detection of potential risks. When the data changes, the inspection parameters are automatically adjusted to increase the inspection intensity of the data related to the type of infectious disease. The inspection frequency adjustment formula is F = F base ×(1+λ×CRI), where F is the inspection frequency after adjustment, F base is the basic inspection frequency, λ is the adjustment coefficient, CRI is the comprehensive risk index, and the inspection focus is determined. According to the risk indicator feedback and actual conditions, when the comprehensive risk index of a certain area is high, according to the formula P area =P base +μ×CRI area Determine the area as a dynamic key area, where P area is the inspection focus level, P base is the basic inspection focus, μ is the adjustment coefficient, CRI area Based on the comprehensive risk index of the region, for dynamic key areas, the intensity and frequency of inspections will be increased, including increasing the number of samples collected, expanding the scope of testing, and strengthening contact tracing;

[0009] Data collection and analysis: Collect infectious disease-related data, including case reports, laboratory test results, and population flow data, analyze the collected data, calculate dynamic risk index values, and adjust inspection strategies based on the index values;

[0010] Risk warning and response: Different levels of warning thresholds are set according to the dynamic risk indicator system and actual conditions. The warning thresholds are adjusted as the infectious disease develops and experience accumulates. When the dynamic risk indicator reaches the preset warning threshold, a risk warning signal is issued, and relevant departments take corresponding prevention and control measures based on the warning signal.

[0011] Furthermore, in the step of establishing a dynamic risk indicator system, the incidence rate, transmission speed and population susceptibility index are comprehensively considered to construct a dynamic risk indicator system, wherein the calculation formula of the incidence rate is: Among them, N cases is the number of cases, N population is the total population, and the formula for calculating the propagation speed is: Among them, A spread is the spatial diffusion range, T span is the time span, and the calculation formula of population susceptibility index is: Among them, α and β are adjustment coefficients, N unvaccinated The number of people who have not been vaccinated is is the total number of people, is the proportion of people with a specific susceptibility gene.

[0012] Furthermore, in the step of establishing a dynamic risk indicator system, the incidence rate, transmission speed and population susceptibility index are comprehensively considered to construct a dynamic risk indicator system, and the comprehensive risk index calculation formula is CRI=w1×I+w2×S+w3×V, where w 1、 w 2、 w3 are the weight coefficients of incidence rate, population susceptibility and transmission speed respectively.

[0013] Furthermore, in the step of establishing a dynamic risk indicator system, as infectious diseases develop and new data emerge, the indicators are continuously adjusted and optimized, and the weights of each indicator are dynamically adjusted. The dynamic adjustment formula of the indicator weight is w i (t+1)=w i (t)+Δw i , where w i (t) represents the weight of a certain indicator at time t, w i (t+1) represents the weight of the indicator at time t+1, Δw i It is the weight adjustment amount, which is determined according to the changing trend of the indicator over a period of time and the degree of contribution to the overall risk.

[0014] Furthermore, in the data collection and analysis step, the data collection channels include report data from medical institutions, disease prevention and control institutions, community workstations, schools and corporate units, as well as information from Internet big data and social media channels.

[0015] Furthermore, in the data collection and analysis step, the collected data is analyzed to calculate the dynamic risk index value, and the calculation formula is: Among them, ΔD represents the amount of data change, n is the number of data indicators, and D i (t) represents the value of the i-th data indicator at time t, D i (t+1) represents the value of the i-th data indicator at time t+1. When the change exceeds the threshold, the inspection parameters are automatically adjusted, and data feedback is collected to continuously optimize the algorithm.

[0016] Furthermore, in the risk warning and response step, as the infectious disease develops and experience is accumulated, the warning threshold is adjusted, and the calculation formula for adjusting the warning threshold is: T threshold =T base ×(1+θ×CRI average ), where T threshold represents the warning threshold, T base is the basic warning threshold, θ is the adjustment coefficient, CRI average It is the average comprehensive risk index over a period of time. When the average comprehensive risk index is high, the warning threshold is increased accordingly.

[0017] In the second aspect, an infectious disease data inspection system includes the following components: a data collection module, a dynamic risk indicator system module, a dynamic inspection strategy module, a risk warning module and a response decision module;

[0018] Data collection module: responsible for collecting infectious disease-related data, including case reports, laboratory test results, and population flow data;

[0019] Dynamic risk indicator system module: build a dynamic risk indicator system, analyze the collected data, calculate the dynamic risk indicator value, and adjust the inspection strategy according to the indicator value;

[0020] Dynamic inspection strategy module: Based on the feedback from the dynamic risk indicator system, the inspection strategy is adjusted dynamically in real time using an adaptive inspection algorithm;

[0021] Risk warning module: According to the dynamic risk indicator system and actual conditions, different levels of warning thresholds are set, and the warning thresholds are adjusted as the infectious disease develops and experience accumulates. When the dynamic risk indicator reaches the preset warning threshold, a risk warning signal is issued;

[0022] Response decision-making module: Based on risk warning signals, formulate corresponding prevention and control measures, including strengthening monitoring, conducting epidemiological investigations and implementing isolation measures.

[0023] In a third aspect, an infectious disease data inspection device includes the following components: a processor, a memory, and an input and output device;

[0024] The processor is used to execute the program instructions of the above infectious disease data inspection method;

[0025] The memory is used to store program instructions and infectious disease related data;

[0026] The input and output devices are used to receive user input and output inspection results.

[0027] In a fourth aspect, a computer-readable storage medium stores a computer program, which, when executed by a processor, implements the above-mentioned infectious disease data inspection method.

[0028] Compared with the prior art, the infectious disease data inspection method, system, device and storable medium have the following beneficial effects:

[0029] 1. The present invention flexibly adjusts the inspection strategy according to factors such as the epidemic season of infectious diseases and population mobility through the mutual coordination of the dynamic risk indicator system and the dynamic inspection strategy to adapt to different infectious disease situations and prevention and control needs, so that the present invention can more effectively respond to various infectious diseases, improve the pertinence and effectiveness of prevention and control measures, and thus better protect public health.

[0030] 2. The present invention constructs a dynamic risk indicator system, comprehensively considers indicators of multiple dimensions, and continuously adjusts and optimizes these indicators according to the development of infectious diseases and the emergence of new data, so as to more accurately reflect the current risk level of infectious diseases and realize dynamic monitoring and early warning of infectious disease risks. At the same time, combined with dynamic inspection strategies, the frequency and focus of inspections are dynamically adjusted according to changes in risk indicators to ensure timely detection and handling of potential risks.

[0031] Other advantages, objectives and features of the present invention will be set forth in part in the following description and, in part, will be apparent to those skilled in the art based on an examination of the following or may be taught from the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0033] Figure 1 It is a flowchart of a method for inspecting infectious disease data;

[0034] Figure 2 A schematic diagram of an infectious disease data inspection system. DETAILED DESCRIPTION

[0035] The technical solutions in the embodiments of the present invention are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] Embodiment 1

[0037] This embodiment describes in detail a specific application of an infectious disease data inspection method, system, device and storable medium in school infectious disease prevention and control, aiming to implement infectious disease data inspection through the present invention and timely discover potential risks.

[0038] In the stage of establishing a dynamic risk indicator system, the number of students who are sick in the school within a specific period of time is counted from the school's medical records and the student absence information collected from each class teacher. cases At the same time, the total number of students N is obtained through the school's student archive system population , according to the formula Calculate the incidence index, which reflects the prevalence of infectious diseases in schools, and analyze the frequency of contact between students in classrooms, dormitories and other spaces, as well as the spread of diseases between classes and grades. Combined with the onset time and spatial distribution information of cases, determine the spatial spread range of new cases within a certain period of time. spread and time span T span , through the formula Calculate the transmission rate index, which reflects the speed of transmission of infectious diseases in schools, and conduct a sample survey of students to understand their vaccination status and determine the number of unvaccinated people N unvaccinated and the total number of students Calculate the ratio of unvaccinated people to the total population and analyze the proportion of students with specific susceptibility genes Taking these factors into consideration, according to the formula Calculate the susceptibility index of the population, where α and β are adjustment coefficients, which can be determined according to actual conditions. This index reflects the susceptibility of the student population to infectious diseases. In addition, invite school doctors and experts in the field of infectious disease prevention and control to set initial weights for indicators such as incidence rate, transmission speed, and population susceptibility based on their experience and judgment of the importance of different indicators. Regularly collect new data, analyze the changes in each indicator at different stages and its impact on the risk of infectious diseases, and use the formula w i (t+1)=w i (t)+Δw i Update the weight of each indicator. For example, if the spread of a certain infectious disease in a school significantly accelerates at a certain stage, the weight adjustment amount Δw2 of the spread speed indicator can be appropriately increased to update the weight of the spread speed indicator.

[0039] In the stage of implementing the dynamic inspection strategy, the historical epidemic data of different infectious diseases in schools are studied to understand their incidence patterns in different seasons. For example, infectious diseases such as influenza are prevalent in winter, and hand, foot and mouth disease is more common in spring and summer. According to the current season and historical data, it is judged whether the school is in the high-incidence season of infectious diseases. The student schedule and the monitoring data on campus are used to analyze the flow trend and aggregation of students in different time periods, identify crowded places such as classrooms, canteens, libraries and other key areas, and monitor the results of the dynamic risk indicator system in real time. When the comprehensive risk index CRI exceeds a certain threshold, it is judged that the risk is increased. The comprehensive risk index is calculated according to the formula CRI = w1×I+w2×S+w3×V, where w1, w2, and w3 are the weight coefficients of incidence, population susceptibility, and transmission speed, respectively. According to the size and resource conditions of the school, a basic inspection frequency is set. For example, a health check is conducted on each class once a week. When it is in a special period such as the high-incidence season of infectious diseases and the start of the school year, or when the risk indicator shows that the risk is increased, according to the formula F=F base ×(1+λ×CRI) to adjust the inspection frequency, where F represents the adjusted inspection frequency, F base is the basic inspection frequency, λ is the adjustment coefficient, which can be determined according to the actual situation. When the comprehensive risk index is high, the inspection frequency will be increased accordingly. For example, in the high-incidence season of influenza, if the comprehensive risk index reaches a certain level, the inspection frequency can be increased to once a day, and students will be tested for body temperature and symptoms. In addition, the school’s infirmary, classrooms, canteens, dormitories and other crowded places are identified as general key areas. These areas are prone to become high-risk areas for the spread of infectious diseases due to the gathering of students. According to the risk indicator feedback and the actual situation, when the comprehensive risk index of a certain area is high, according to the formula P area =P base +μ×CRI area Determine the area as a dynamic key area, where P area Indicates the inspection focus of a certain area, P base is the basic inspection focus level, μ is the adjustment coefficient, which can be determined according to actual conditions, CRI area is the comprehensive risk index of the area. For example, if a class has a high comprehensive risk index, the class will be listed as a dynamic key area, and inspections of the class will be increased, including increasing the number of temperature checks for students, strengthening ventilation and disinfection of classrooms, etc., and continuously monitoring changes in infectious disease-related data. Calculate the data change, where ΔD represents the data change, n is the number of data indicators, and D i (t) represents the value of the i-th data indicator at time t, D i(t+1) represents the value of the i-th data indicator at time t+1. For example, the changes in indicators such as the incidence rate and transmission speed of students are monitored. When the data change exceeds a certain threshold, the inspection parameters are automatically adjusted. For example, if the incidence rate of a certain infectious disease suddenly rises, the inspection intensity of data related to the infectious disease is increased, including increasing the number of samples, expanding the scope of detection, and strengthening contact tracing of sick students. In addition, data feedback from actual applications is collected, and the effect of the adaptive inspection algorithm is analyzed. According to the feedback results, the algorithm is continuously adjusted and optimized to improve its accuracy and response speed. For example, according to the characteristics of different infectious diseases and the actual situation of the school, the threshold of the data change and the adjustment strategy of the inspection parameters are adjusted.

[0040] During the data collection and analysis stage, an information sharing platform with the school clinic is established to regularly collect student case reports, laboratory test results and other data. Students' absence information, health status and other data are collected through teachers in each class. Teachers can note the students' physical conditions in the daily attendance records, such as the number of students with symptoms such as fever and cough. Internet big data is used to pay attention to news and information on social media related to school infectious diseases, extract useful information as auxiliary data, use statistical software and tools to conduct statistical analysis on the collected data, calculate dynamic risk indicator values, such as incidence, transmission speed, population susceptibility, etc., analyze the changing trends and correlations of each indicator, provide data support for infectious disease prevention and control, and use data mining technology to discover potential patterns and associations in the data. For example, find out the correlation between different infectious diseases, or group students with similar symptoms to better understand the transmission laws of infectious diseases. Present the analysis results in a visual way, such as using charts, maps, etc. to display data. For example, make a line graph of incidence over time and a heat map of transmission speed, so as to intuitively understand the development trend and risk distribution of infectious diseases.

[0041] In the risk warning and response stage, the basic warning threshold T is determined based on the school's historical infectious disease data and experience. base For example, it can be set that when the comprehensive risk index reaches a certain value, an early warning signal is issued. With the development of infectious diseases and the accumulation of experience, according to the average comprehensive risk index, according to the formula T threshold =T base ×(1+θ×CRI average ) adjusts the warning threshold, where T t hreshold is the warning threshold, θ is the adjustment coefficient, which can be determined according to the actual situation, CRI averageIt is the average comprehensive risk index over a period of time. When the dynamic risk index reaches the preset warning threshold, a risk warning signal will be issued to school leaders, teachers, parents and students through the school's broadcasting system, class WeChat group, text messages, etc. The warning information includes risk level, type of infectious disease involved, risk area and other information, so that relevant personnel can take corresponding prevention and control measures.

[0042] In summary, by introducing the present invention, this embodiment can effectively realize infectious disease data inspection, timely discover potential risks, take corresponding prevention and control measures, and ensure the health of students and the normal teaching order of the school.

[0043] Embodiment 2

[0044] This embodiment details an infectious disease data inspection method, system, device and storable medium for application in infectious disease prevention and control in community workstations, aiming to effectively implement infectious disease data inspection and timely discover potential risks through the present invention.

[0045] In the stage of establishing a dynamic risk indicator system, the number of community residents with illnesses in a specific period of time is counted from the electronic medical record system of the community health workstation and the reports of community workers. cases , combined with the community's population registration information to determine the total population of the community N population , according to the formula Calculate the incidence index to reflect the prevalence of infectious diseases in the community, analyze the daily activities of community residents, such as the flow of people in public places such as supermarkets and parks, and the time span T of the spread of the disease between different areas of the community span and spatial range, determine the spatial spread range A of new cases spread , through the formula Calculate the transmission speed index to reflect the transmission speed of infectious diseases in the community, and conduct a sample survey of community residents to understand the vaccination status of residents and determine the number of unvaccinated people N unvaccinated Total number of community residents The ratio of the community residents to the disease was analyzed by taking into account the influence of factors such as the age distribution of the community residents and whether they suffer from chronic diseases, and the proportion of people with specific susceptibility genes. Taking all these reasons into consideration, according to the formula Calculate the population susceptibility index, where α and β are adjustment coefficients, which can be determined according to actual conditions to reflect the susceptibility of community residents to infectious diseases. Invite doctors and public health experts from community workstations to set initial weights for indicators such as incidence, transmission speed, and population susceptibility based on their experience and judgment of the importance of different indicators. Collect new data regularly, analyze the changes in each indicator at different stages and its impact on the risk of infectious diseases, and use the formula w i (t+1)=wi (t)+Δw i Update the weights of each indicator. For example, if the spread of a certain infectious disease in a community accelerates and has a greater impact during a certain period, the weight adjustment of the spread speed indicator Δw can be appropriately increased. 2, Update the weight of the propagation speed indicator.

[0046] In the stage of implementing the dynamic inspection strategy, the historical epidemic data of different infectious diseases in the community are studied to understand their incidence patterns in different seasons. For example, intestinal infectious diseases may be prevalent in summer, while respiratory infectious diseases such as influenza are more common in winter. Based on the current season and historical data, it is determined whether the community is in the high-incidence season of infectious diseases. The community’s surveillance camera data and public transportation flow data are used to analyze the flow trends and aggregation of community residents, and to determine crowded places, such as community vegetable markets, shopping malls, fitness plazas and other key areas. The results of the dynamic risk indicator system are monitored in real time. When the comprehensive risk index CRI exceeds a certain threshold, the risk is judged to be increased. The comprehensive risk index is calculated according to the formula CRI = w1×I+w2×S+w3×V, where w1, w2, and w3 are the weight coefficients of incidence, population susceptibility, and transmission speed, respectively. According to the resources of the community workstation and the size of the community, a basic inspection frequency is set, such as a monthly inspection of key areas of the community. When it is in the high-incidence season of infectious diseases, when the community holds large-scale activities, or when the risk indicators show that the risk is increased, according to the formula F = F base ×(1+λ×CRI) to adjust the inspection frequency, where F represents the adjusted inspection frequency, F base is the basic inspection frequency, λ is the adjustment coefficient, which can be determined according to the actual situation. When the comprehensive risk index is high, the inspection frequency is increased. For example, in the high-incidence season of influenza and when the comprehensive risk index of the community is high, the inspection frequency can be increased to once a week, health promotion and disease screening can be carried out for community residents, and community workstations, community hospitals, nursing homes, kindergartens and other crowded places are identified as general key areas. According to the risk indicator feedback and actual situation, when the comprehensive risk index of a certain area is high, according to the formula P area =P base +μ×CRI area Determine the area as a dynamic key area, where P area Indicates the inspection focus of a certain area, P base is the basic inspection focus level, μ is the adjustment coefficient, which can be determined according to actual conditions, CRI area is the comprehensive risk index of the area. For example, if the comprehensive risk index of a community is high, the community will be listed as a dynamic key area, and the inspection of the community will be strengthened, including increasing health publicity, increasing the frequency of disease screening, etc. At the same time, the changes in infectious disease related data will be continuously monitored. According to the formula Calculate the data change, where ΔD represents the data change, n is the number of data indicators, and D i (t) represents the value D of the i-th data indicator at time t i (t+1) represents the value of the i-th data indicator at time t+1. For example, it monitors the changes in indicators such as the incidence rate and transmission speed of community residents. When the data change exceeds a certain threshold, it automatically adjusts the inspection parameters, collects data feedback from actual applications, analyzes the effect of the adaptive inspection algorithm, and continuously adjusts and optimizes the algorithm based on the feedback results to improve its accuracy and response speed.

[0047] During the data collection and analysis stage, an information sharing platform with the community workstation is established to regularly collect data such as residents' case reports and laboratory test results. At the same time, the health status information of residents and the registration information of outsiders are collected through the staff of the community neighborhood committee. The community neighborhood committee can pay attention to the health status of residents in daily work and report abnormal situations to the community workstation in a timely manner. It can also use Internet big data to pay attention to news and social media information related to community infectious diseases and extract useful information as auxiliary data. For example, it can understand the infectious disease situation in the surrounding communities so as to take preventive measures in time. Statistical software and tools are used to conduct statistical analysis on the collected data, calculate dynamic risk indicator values ​​such as incidence rate, transmission speed, population susceptibility, etc., analyze the changing trends and correlations of various indicators, provide data support for infectious disease prevention and control, and use data mining technology to discover potential patterns and associations in the data. For example, find out the correlation between different infectious diseases, or group residents with similar symptoms to better understand the transmission law of infectious diseases. The analysis results are presented in a visual way, such as using charts, maps, etc. to display data. For example, a line graph of incidence rate over time and a heat map of transmission speed are made to intuitively understand the development trend and risk distribution of infectious diseases.

[0048] In the risk warning and response stage, the basic warning threshold T is determined based on the historical infectious disease data and experience of the community. base For example, it can be set that when the comprehensive risk index reaches a certain value, an early warning signal is issued. With the development of infectious diseases and the accumulation of experience, according to the average comprehensive risk index, according to the formula T thresjold =T base ×(1+θ×CRI average ) adjust the warning threshold, where T t jreshold is the warning threshold, θ is the adjustment coefficient, which can be determined according to the actual situation, CRI averageIt is the average comprehensive risk index over a period of time. When the dynamic risk index reaches the preset warning threshold, a risk warning signal will be issued to community residents, community workers and relevant departments through community broadcasts, mobile phone text messages, community bulletin boards, etc. The warning information includes risk level, type of infectious disease involved, risk area and other information, so that relevant personnel can take corresponding prevention and control measures.

[0049] In summary, by introducing the present invention, this embodiment can effectively realize infectious disease data inspection, timely discover potential risks, take corresponding prevention and control measures, and ensure the health and safety of community residents.

[0050] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A method for inspecting infectious disease data, characterized in that: The method comprises the following specific steps: Establish a dynamic risk indicator system: comprehensively consider the incidence rate, transmission speed and population susceptibility indicators, build a dynamic risk indicator system, continuously adjust and optimize the indicators as the infectious disease develops and new data emerges, and dynamically adjust the weights of each indicator to more accurately reflect the current infectious disease risk level; Implement dynamic inspection strategy: Based on the feedback of the dynamic risk indicator system, the inspection frequency and focus are adjusted dynamically according to the epidemic season of infectious diseases and the flow of people. During the high-incidence season of infectious diseases, during major events, or when risk indicators show increased risks, the number and scope of inspections are increased to enable timely detection of potential risks. When the data changes, the inspection parameters are automatically adjusted to increase the inspection intensity of data related to this type of infectious disease. The inspection frequency adjustment formula is F = Fbase × (1 + λ × CRI), where F is the adjusted inspection frequency and F base is the basic inspection frequency, λ is the adjustment coefficient, CRI is the comprehensive risk index, and the inspection focus is determined. According to the risk indicator feedback and actual conditions, when the comprehensive risk index of a certain area is high, according to the formula P area =P base +μ×CRI area Determine the area as a dynamic key area, where P area is the inspection focus level, P base is the basic inspection focus, μ is the adjustment coefficient, CRI area Based on the comprehensive risk index of the region, for dynamic key areas, the intensity and frequency of inspections will be increased, including increasing the number of samples collected, expanding the scope of testing, and strengthening contact tracing; Data collection and analysis: Collect infectious disease-related data, including case reports, laboratory test results, and population flow data, analyze the collected data, calculate dynamic risk index values, and adjust inspection strategies based on the index values; Risk warning and response: Different levels of warning thresholds are set according to the dynamic risk indicator system and actual conditions. The warning thresholds are adjusted as the infectious disease develops and experience accumulates. When the dynamic risk indicator reaches the preset warning threshold, a risk warning signal is issued, and relevant departments take corresponding prevention and control measures based on the warning signal.

2. The infectious disease data inspection method according to claim 1, characterized in that: In the step of establishing a dynamic risk indicator system, the incidence rate, transmission speed and population susceptibility index are comprehensively considered to construct a dynamic risk indicator system, wherein the calculation formula of the incidence rate is: Among them, N cases is the number of cases, N population is the total population, and the formula for calculating the propagation speed is: Among them, A spread is the spatial diffusion range, T span is the time span, and the calculation formula of population susceptibility index is: Among them, α and β are adjustment coefficients, N unvaccinated The number of people who have not been vaccinated is is the total number of people, is the proportion of people with a specific susceptibility gene.

3. The infectious disease data inspection method according to claim 2, characterized in that: In the step of establishing a dynamic risk indicator system, the incidence rate, transmission speed and population susceptibility index are comprehensively considered to construct a dynamic risk indicator system, and the calculation formula of the comprehensive risk index is CRI=w1×I+w2×S+w3×V, where w 1、 w 2、 w3 are the weight coefficients of incidence rate, population susceptibility and transmission speed respectively.

4. The infectious disease data inspection method according to claim 1, characterized in that: In the step of establishing a dynamic risk indicator system, as infectious diseases develop and new data emerge, the indicators are continuously adjusted and optimized, and the weights of each indicator are dynamically adjusted. The dynamic adjustment formula of the indicator weight is w i( t+1 ) =w i( t ) +Δw i , where w i( t ) represents the weight of an indicator at time t, w i( t+1 ) represents the weight of the indicator at time t+1, Δw i It is the weight adjustment amount, which is determined according to the changing trend of the indicator over a period of time and the degree of contribution to the overall risk.

5. The infectious disease data inspection method according to claim 1, characterized in that: In the data collection and analysis steps, the data collection channels include reported data from medical institutions, disease prevention and control institutions, community workstations, schools and corporate units, as well as information from Internet big data and social media channels.

6. The infectious disease data inspection method according to claim 1, characterized in that: In the data collection and analysis step, the collected data is analyzed to calculate the dynamic risk index value, and the calculation formula is: Among them, ΔD represents the amount of data change, n is the number of data indicators, and D i ( t ) represents the value of the i-th data indicator at time t, D i( t+1 ) It represents the value of the i-th data indicator at time t+1. When the change exceeds the threshold, the inspection parameters are automatically adjusted. At the same time, data feedback is collected to continuously optimize the algorithm.

7. The infectious disease data inspection method according to claim 1, characterized in that: In the risk warning and response steps, as the infectious disease develops and experience accumulates, the warning threshold is adjusted. The calculation formula for adjusting the warning threshold is: T threshold =T base × ( 1+θ×CRI average ) , where T threshold represents the warning threshold, T base is the basic warning threshold, θ is the adjustment coefficient, CRI average It is the average comprehensive risk index over a period of time. When the average comprehensive risk index is high, the warning threshold is increased accordingly.

8. An infectious disease data inspection system, characterized in that: The system includes the following components: data collection module, dynamic risk indicator system module, dynamic inspection strategy module, risk warning module and response decision module; Data collection module: responsible for collecting infectious disease-related data, including case reports, laboratory test results, and population flow data; Dynamic risk indicator system module: build a dynamic risk indicator system, analyze the collected data, calculate the dynamic risk indicator value, and adjust the inspection strategy according to the indicator value; Dynamic inspection strategy module: Based on the feedback from the dynamic risk indicator system, the inspection strategy is adjusted dynamically in real time using an adaptive inspection algorithm; Risk warning module: According to the dynamic risk indicator system and actual conditions, different levels of warning thresholds are set, and the warning thresholds are adjusted as the infectious disease develops and experience accumulates. When the dynamic risk indicator reaches the preset warning threshold, a risk warning signal is issued; Response decision-making module: Based on risk warning signals, formulate corresponding prevention and control measures, including strengthening monitoring, conducting epidemiological investigations and implementing isolation measures.

9. An infectious disease data inspection device, characterized in that: The device comprises the following components: a processor, a memory and an input and output device; The processor is used to execute the program instructions of the above infectious disease data inspection method; The memory is used to store program instructions and infectious disease related data; The input and output devices are used to receive user input and output inspection results.

10. A computer-readable storage medium, characterized in that: The readable storage medium stores a computer program, which, when executed by a processor, implements the above-mentioned infectious disease data inspection method.

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