Disease monitoring, analyzing and early warning system for entry-exit port

Abstract

The invention discloses an entry-exit port disease monitoring, analyzing and early warning system, which belongs to the technical field of disease monitoring and early warning, and realizes accurate disease monitoring and risk assessment of entry-exit personnel through a data collection and monitoring module, a personnel classification detection module, a risk judgment module and an early warning module. A sentinel detector is used for collecting health information and appearance characteristics of personnel, a disease risk value is analyzed in combination with a risk city mark, a symptom total evaluation value and a characteristic total evaluation value, and the personnel are divided into high, medium and low risk levels and arranged to corresponding detection channels in a data collection and monitoring module; the risk judgment and early warning module comprehensively considers the number of personnel, the disease transmission range, the seasonal factor and the fatality rate factor, analyzes and calculates a risk early warning value, divides early warning levels and takes accurate prevention and control measures; the scientificity and accuracy of prevention and control of infectious diseases are effectively improved, and the public health safety of entry and exit ports is guaranteed.

Description

Technical Field

[0001] The invention belongs to the technical field of disease monitoring and early warning, and specifically relates to a disease monitoring, analysis and early warning system for entry-exit ports. Background Art

[0002] With the acceleration of globalization, the number of people entering and leaving the country is increasing day by day, and the cross-border flow of people is becoming more frequent. As key hubs for the cross-border flow of people and goods, entry and exit ports face severe challenges in disease prevention and control. The risk of various infectious diseases spreading globally has increased significantly. Once there are loopholes in the prevention and control of ports, infectious diseases can easily spread rapidly, which not only threatens the health of people entering and leaving the country, but may also trigger regional or even global public health crises.

[0003] The main technical challenges in disease monitoring, analysis and early warning at entry and exit ports are as follows:

[0004] 1. It is difficult to identify people who may carry infectious diseases (vectors) when entering or leaving the country, and there is a lack of an efficient personnel risk assessment mechanism, which leads to loopholes in infectious disease prevention and control;

[0005] 2. The assessment of the risk and degree of harm of disease transmission is not comprehensive enough;

[0006] 3. The lack of real-time monitoring and rapid response capabilities to dynamic changes leads to delayed early warning information, making it difficult to adjust prevention and control strategies in a timely manner, and difficult to take precise prevention and control measures according to different risk levels, thus making it impossible to avoid waste of resources while ensuring public health safety. For this reason, we propose a disease monitoring, analysis and early warning system for entry and exit ports. Summary of the invention

[0007] The purpose of the present invention is to provide an entry-exit port disease monitoring, analysis and early warning system to solve the problems raised in the above-mentioned background technology.

[0008] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a disease monitoring, analysis and early warning system for entry and exit ports, comprising: a data collection and monitoring module, a personnel classification monitoring module, and a risk judgment and early warning module;

[0009] The data collection and monitoring module collects test information and monitors diseases of people entering and leaving the country;

[0010] The personnel classification detection module marks risk cities according to the infectious disease situation in the city, compares the cities that people entering and leaving the city pass through, and for people passing through risk cities, analyzes the symptom total evaluation value based on personal health information and the feature total evaluation value based on appearance feature information, and analyzes the disease risk value based on the symptom total evaluation value and the feature total evaluation value, and marks people of different levels of risk accordingly, and arranges corresponding risk detection channels for infectious disease screening;

[0011] The risk assessment and early warning module analyzes the number of people entering and leaving the country, the distribution of risk personnel, the scope of disease transmission, seasonal factors, and the disease mortality rate to obtain the total number of inspectors, high-wind transmission value, stroke transmission value, high-wind mortality rate, and stroke mortality rate, and conducts a comprehensive analysis to obtain the risk warning value, divides the risk level according to the risk warning value, and formulates corresponding prevention and control measures.

[0012] Preferably, the specific process of the data collection and monitoring module collecting detection information of entry and exit personnel is as follows:

[0013] Collect test information and conduct disease monitoring on inbound and outbound passengers at the passenger passages and waiting areas of entry and exit ports; the test information includes: appearance characteristics and personal health information;

[0014] Capture the appearance characteristics of people entering and leaving the country; appearance characteristics include: eye characteristics, mouth characteristics, facial muscle characteristics, hand movement characteristics, leg movement characteristics and body posture characteristics;

[0015] The personal health information of people entering and leaving the country shall be collected; personal health information includes: recent travel history, whether there are symptoms of illness, and symptoms of illness include: fever, cough, and diarrhea.

[0016] Preferably, the specific process of the data collection and monitoring module for disease monitoring of entry-exit personnel is as follows:

[0017] Establish three disease monitoring channels, namely low-risk monitoring channel, medium-risk monitoring channel and high-risk monitoring channel;

[0018] The low-risk monitoring channel is equipped with infrared sensor measurement equipment to measure the body temperature of people entering and leaving the country, and simultaneously collect their body temperature information;

[0019] The medium-risk monitoring channel is equipped with antigen detectors based on the equipment of the low-risk monitoring channel, which are used to conduct antigen reagent tests on people entering and leaving the country and collect reagent test data;

[0020] In addition to infrared sensing measurement equipment and antigen detectors, high-risk monitoring channels are equipped with biochip detectors to collect disease samples from people entering and leaving the country. After the disease samples are collected, the disease samples are tested. The disease samples include: blood samples, respiratory samples, and saliva samples; and disease sample testing data are collected.

[0021] Preferably, the specific process of analyzing the total symptom evaluation value by the personnel classification detection module is:

[0022] Cities that have shown a high incidence of infectious diseases so far are marked as risk cities, and a risk city list is formed. For each inbound and outbound person, the corresponding appearance feature information and personal health information are retrieved from the data collection and monitoring module. The cities that the inbound and outbound person has passed through during his or her travels are obtained based on his or her recent travel history. Each city that the inbound and outbound person has passed through is compared with the risk city list one by one to detect whether any of the cities that have been passed through are marked as risk cities;

[0023] If there are risky cities among the cities along the route, obtain the highly infectious diseases corresponding to all risky cities along the route and mark them as detected diseases; establish a corresponding disease symptom library and disease feature library for each detected disease; establish a disease symptom library containing all symptoms corresponding to the detected disease, and a disease feature library containing all appearance features corresponding to the detected disease;

[0024] For each detected disease, each disease symptom in the preset disease symptom library corresponds to a disease diagnosis value. The disease symptoms in the personal health information of the entry and exit personnel are matched with all the disease symptoms in the disease symptom library. If the same disease symptoms exist, the corresponding disease diagnosis value is output, and then all the disease diagnosis values ​​corresponding to the same disease symptoms are added together to obtain the symptom total evaluation value ZP.

[0025] Preferably, the specific process of analyzing the total feature evaluation value by the personnel classification detection module is as follows:

[0026] For eye features, mouth features, facial muscle features, hand movement features, leg movement features, and body posture features, establish parameter ranges for various appearance features under normal conditions; for each detected disease, preset the deviation intervals of various appearance features in the disease feature library relative to the normal range under the diseased state, which are recorded as the disease feature deviation interval standard; calculate the deviation values ​​of various appearance features in the appearance feature information of entry-exit personnel relative to the normal range, which are recorded as the actual deviation values ​​of personnel features, and each type of appearance feature in the preset disease feature library corresponds to a feature diagnosis value;

[0027] For each type of appearance feature in the disease feature library, the actual deviation value of the corresponding personnel feature is matched with the disease feature deviation interval standard corresponding to this type of appearance feature. If the actual deviation value of the personnel feature is within the disease feature deviation interval standard, the feature diagnosis value corresponding to this type of appearance feature is output; then the feature diagnosis values ​​of all appearance feature categories are summarized to obtain the feature total evaluation value TP.

[0028] Preferably, the personnel classification detection module analyzes the disease risk value, marks the personnel at different risk levels accordingly, and arranges corresponding risk detection channels for infectious disease screening in the following specific process:

[0029] For each detected disease, the corresponding symptom total evaluation value ZP and feature total evaluation value TP are normalized, and the disease risk value JFX is obtained using the formula: JFX=ZP×a1+TP×a2, where a1 and a2 are preset weight coefficients; the disease risk value corresponding to the entry-exit personnel is compared with the disease risk value threshold. If the disease risk value is greater than or equal to the disease risk value threshold, the entry-exit personnel is marked as a suspected patient of the detected disease;

[0030] If the corresponding disease risk value of an entry-exit person is greater than or equal to the corresponding disease risk value threshold in the calculation of multiple disease risk values, the entry-exit person will be marked as a suspected patient of multiple detected diseases;

[0031] Entry-exit persons who are marked as suspected patients of a certain or multiple detectable diseases will be recorded as high-risk persons;

[0032] Those entering and leaving the country who are not marked as suspected patients of any disease detected will be recorded as medium-risk persons;

[0033] If there is no risk city among the cities that the inbound and outbound personnel pass through during their travel, the inbound and outbound personnel will be recorded as low-risk personnel;

[0034] For every person entering or leaving the country, they will be assigned to the risk detection channel of the corresponding risk level for detection according to the corresponding risk level.

[0035] Preferably, the specific process of the risk judgment and early warning module analyzing and obtaining the total number of inspectors, high-risk transmission value, and moderate-risk transmission value is as follows:

[0036] For each batch of entry and exit personnel, obtain the total number of entry and exit personnel, recorded as the total number of inspectors ZY, and at the same time obtain the total number of high-risk personnel GR and the total number of medium-risk personnel ZR of the same batch of entry and exit personnel, obtain the spatial area AS of the passenger channel and waiting area of ​​the entry and exit port, and use the formula: SM=ZY / AS to obtain the actual density of personnel SM; at the same time, obtain the area corresponding to the high-risk monitoring channel and the medium-risk monitoring channel, recorded as the high channel area GS and the medium channel area ZS, and use the formula: Kg=(GR / GS) / SM to obtain the high-risk personnel density correction factor Kg, and use the formula: Kz=(ZR / ZS) / SM to obtain the medium-risk personnel density correction factor Kz;

[0037] For the detected diseases corresponding to high-risk and medium-risk persons, obtain the number of cities affected by each detected disease in the world within one year. For each detected disease, preset several intervals of the number of affected cities, and each interval of the number of affected cities corresponds to a transmission risk value. For each detected disease corresponding to high-risk persons, match it with the corresponding several intervals of the number of affected cities, and output the corresponding transmission risk value CFi, i=1, 2, ..., n; n is the total number of detected diseases for high-risk persons. For each detected disease corresponding to high-risk persons, obtain the corresponding number of high-risk persons RYi, and preset seasonal transmission influence factors respectively to clarify the current season, match this season with all seasonal transmission influence factors corresponding to the detected disease, and output the seasonal transmission influence factor SJi corresponding to the current season; use the formula: , and obtain the high-wind transmission value CFZ; the implementation method of analyzing the high-wind transmission value is recorded as the risk transmission analysis method. Similarly, the risk transmission analysis method is used to analyze the risk transmission of the detected disease corresponding to the medium-risk personnel to obtain the stroke transmission value ZFC.

[0038] Preferably, the specific process of the risk judgment and early warning module analyzing and obtaining the mortality rate of high-intensity stroke and the mortality rate of stroke is:

[0039] Obtain the fatality rate of each detected disease corresponding to high-risk personnel and medium-risk personnel. The fatality rate of the detected disease corresponding to high-risk personnel is marked as high-risk fatality rate GLi; use the formula: , and get the high stroke hazard value GFS. The implementation method of analyzing the high stroke hazard value is recorded as the hazard degree analysis method. Similarly, the hazard degree analysis method is used to analyze the hazard degree of the detected disease corresponding to the medium-risk personnel to obtain the stroke hazard value ZFS.

[0040] Preferably, the risk judgment and early warning module analyzes and obtains the risk early warning value, classifies the risk level according to the risk early warning value, and formulates the specific process of corresponding prevention and control measures as follows:

[0041] The total number of inspectors ZY, high-risk transmission value CFZ, medium-risk transmission value ZFC, high-risk hazard value GFS and stroke hazard value ZFS corresponding to the current batch are normalized and substituted into the preset formula model: FYZ=ZY×w1+CFZ×w2+ZFC×w3+GFS×w4+ZFS×w5 to obtain the risk warning value FYZ, where w1, w2, w3, w4 and w5 are preset weight coefficients;

[0042] Three warning levels are preset, namely level one, level two and level three, and each warning level corresponds to a risk warning value range. By matching the risk warning value corresponding to this batch of inbound and outbound personnel with the risk warning value ranges corresponding to the three warning levels, the corresponding warning level is output and the corresponding level of prevention and control measures are implemented.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] (1) A disease monitoring, analysis and early warning system for entry and exit ports, a personnel classification detection module, can accurately identify entry and exit personnel who may carry infectious diseases. The module marks risk cities according to the infectious disease situation of the city, compares the cities through which the entry and exit personnel pass, analyzes the symptom total evaluation value based on personal health information, and analyzes the feature total evaluation value based on appearance feature information, and then analyzes the disease risk value, marks high, medium and low risk personnel accordingly, and arranges high, medium and low risk detection channels for infectious disease screening accordingly; through this method based on multi-dimensional information comprehensive evaluation, the accuracy of personnel risk assessment is greatly improved, the loopholes in infectious disease prevention and control are effectively filled, and the accurate prevention and control of infectious diseases at entry and exit ports is ensured.

[0045] (2) In this entry-exit port disease monitoring, analysis and early warning system, the risk assessment and early warning module comprehensively considers a variety of factors, including the number of people entering and leaving the country, the distribution of risk personnel, the scope of disease transmission, seasonal factors, disease mortality rate, etc. By analyzing the above data, the total number of inspectors, high-wind transmission value, stroke transmission value, high-wind mortality rate and stroke mortality rate are obtained, and a comprehensive analysis is performed to obtain the risk warning value, and then the risk level is divided; this assessment method not only conducts a comprehensive and scientific assessment of the risk of disease transmission and the degree of harm from the perspective of the number and distribution of personnel, but also from multiple dimensions such as the scope of disease transmission, seasonal changes and the degree of harm, providing an accurate basis for subsequent prevention and control measures, and effectively improving the scientificity and effectiveness of disease prevention and control.

[0046] (3) This is a disease monitoring, analysis and early warning system for entry and exit ports. It continuously collects the health information and appearance characteristics of people entering and leaving the country through sentinel detectors, obtains disease transmission data released by authoritative agencies in real time, and dynamically updates key parameters such as risk city markers, disease transmission range and seasonal transmission influencing factors to ensure the timeliness and accuracy of early warning information. It calculates risk warning values ​​based on real-time monitoring data, divides different warning levels according to risk warning values, and takes different prevention and control measures, which helps to achieve precise prevention and control according to the degree of risk, avoids the waste of resources caused by excessive prevention and control, and ensures effective prevention and control of disease transmission under different risk conditions, thereby protecting the public health safety of entry and exit ports. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a flowchart of the present invention. DETAILED DESCRIPTION

[0048] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0049] Embodiment 1

[0050] See also Figure 1 ,The present invention provides an entry-exit port disease monitoring, analysis and early warning system, including: a data collection and monitoring module, a personnel classification detection module, and a risk judgment and early warning module;

[0051] The data collection and monitoring module collects information and monitors diseases of people entering and leaving the country through sentinel detectors; the sentinel detectors include: high-definition cameras, intelligent voice interaction devices, infrared sensors, antigen detectors, and biochip detectors; the specific process is as follows:

[0052] Sentinel detectors are deployed at key locations such as passenger passages and waiting areas (cars and ships) at entry and exit ports to collect test information and monitor diseases of entry and exit personnel within their working range; the test information includes: appearance characteristics information and personal health information;

[0053] The appearance characteristics of people entering and leaving the country are captured in real time through high-definition cameras; the appearance characteristics include: eye characteristics, mouth characteristics, facial muscle characteristics, hand movement characteristics, leg movement characteristics and body posture characteristics;

[0054] The personal health information of people entering and leaving the country is collected through intelligent voice interaction devices; personal health information includes: recent travel history, whether there are symptoms of illness, and symptoms of illness include: fever, cough, diarrhea, etc.

[0055] The process of disease monitoring is as follows: Establish three disease monitoring channels, namely low-risk monitoring channel, medium-risk monitoring channel and high-risk monitoring channel;

[0056] The low-risk monitoring channel is equipped with infrared sensors to measure the body temperature of people entering and leaving the country, and simultaneously collect their body temperature information;

[0057] The medium-risk monitoring channel is equipped with antigen detectors based on the equipment of the low-risk monitoring channel, which are used to conduct antigen reagent tests on people entering and leaving the country and collect reagent test data;

[0058] In addition to infrared sensor measurement equipment and antigen detectors, high-risk monitoring channels are additionally equipped with biochip detectors to collect disease samples from people entering and leaving the country. After the disease samples are collected, the disease samples are tested. The disease samples include: blood samples, respiratory samples, and saliva samples; and the disease sample test data is collected;

[0059] The personnel classification detection module marks risk cities according to the infectious disease situation in the city, compares the cities that the inbound and outbound personnel pass through, and for those who pass through the risk cities, analyzes the symptom total evaluation value based on personal health information and the feature total evaluation value based on appearance feature information, and analyzes the disease risk value based on the symptom total evaluation value and the feature total evaluation value, and marks high, medium and low risk personnel accordingly, and arranges high, medium and low risk monitoring channels for infectious disease screening. The specific process is as follows:

[0060] Cities that still show a high incidence of infectious diseases are marked as risk cities. All risk cities are sorted out to form a risk city list. For each inbound and outbound person, the corresponding appearance feature information and personal health information are retrieved from the data collection and monitoring module. The cities that the inbound and outbound person has passed through during his travels are obtained based on his recent travel history. Each city that the inbound and outbound person has passed through is compared with the risk city list one by one to detect whether any of the cities passed through are marked as risk cities;

[0061] If there are risky cities among the cities along the way, obtain the highly infectious diseases corresponding to all risky cities along the way and mark them as detected diseases; for each detected disease, establish a corresponding disease symptom library and disease feature library; the established disease symptom library contains all the symptoms corresponding to the detected disease, and the disease feature library contains all the appearance features corresponding to the detected disease;

[0062] For each detected disease, each disease symptom in the preset disease symptom library corresponds to a disease diagnosis value. The disease symptoms in the personal health information of the entry-exit personnel are matched with all the disease symptoms in the disease symptom library. If the same disease symptoms exist, the corresponding disease diagnosis value is output, and then all the disease diagnosis values ​​corresponding to the same disease symptoms are added together to obtain the symptom total evaluation value ZP;

[0063] For eye features, mouth features, facial muscle features, hand movement features, leg movement features, and body posture features, establish parameter ranges for various appearance features under normal conditions; for each detected disease, preset the deviation intervals of various appearance features in the disease feature library relative to the normal range under the diseased state, which are recorded as the disease feature deviation interval standard; calculate the deviation values ​​of various appearance features in the appearance feature information of entry-exit personnel relative to the normal range, which are recorded as the actual deviation values ​​of personnel features, and each type of appearance feature in the preset disease feature library corresponds to a feature diagnosis value;

[0064] For each type of appearance feature in the disease feature database, the actual deviation value of the corresponding person feature is matched with the disease feature deviation interval standard corresponding to the type of appearance feature. If the actual deviation value of the person feature is within the disease feature deviation interval standard, the feature diagnosis value corresponding to the type of appearance feature is output; then the feature diagnosis values ​​of all appearance feature categories are summarized to obtain the feature total evaluation value TP;

[0065] For each detected disease, the corresponding symptom total evaluation value ZP and feature total evaluation value TP are normalized, and the disease risk value JFX is obtained using the formula: JFX=ZP×a1+TP×a2, where a1 and a2 are preset weight coefficients; the larger the disease risk value, the greater the probability that the inbound and outbound personnel suffer from this infectious disease; the disease risk value threshold is preset, and the disease risk value corresponding to the inbound and outbound personnel is compared with the disease risk value threshold. If the disease risk value is greater than or equal to the disease risk value threshold, the inbound and outbound personnel is marked as a suspected patient of the detected disease;

[0066] If the corresponding disease risk value of an entry-exit person is greater than or equal to the corresponding disease risk value threshold in the calculation of multiple disease risk values, the entry-exit person will be marked as a suspected patient of multiple detected diseases;

[0067] Entry-exit persons who are marked as suspected patients of a single or multiple diseases will be recorded as high-risk persons;

[0068] Those entering and leaving the country who are not marked as suspected patients of any disease detected will be recorded as medium-risk persons;

[0069] If there is no risk city among the cities that the inbound and outbound personnel pass through during their travel, the inbound and outbound personnel will be recorded as low-risk personnel;

[0070] For each entry-exit person, according to the corresponding risk level, they will be assigned to the risk detection channel of the corresponding risk level for detection. The higher the level of the risk monitoring channel, the more detection items there are;

[0071] It should be noted that by dynamically marking risk cities and comparing them with transit cities, people entering and leaving the country who may be exposed to the risk of infectious diseases can be identified. By analyzing the symptom total score based on personal health information and the feature total score based on appearance feature information, the disease risk value is analyzed based on the symptom total score and the feature total score, which greatly improves the accuracy of infectious disease risk assessment. People are diverted to different detection channels according to their risk levels, achieving efficient use of resources. Unnecessary excessive testing of all personnel is avoided, and detection efficiency is improved while ensuring that high-risk personnel receive key attention and accurate testing. By marking high-, medium-, and low-risk personnel and implementing corresponding tests, the spread of infectious diseases can be effectively blocked.

[0072] The risk judgment and early warning module obtains the total number of inspectors, high-risk transmission value, stroke transmission value, high-risk mortality rate and stroke mortality rate by analyzing the number of people entering and leaving the country, the distribution of risk personnel, the scope of disease transmission, seasonal factors and disease mortality rate, and conducts a comprehensive analysis to obtain the risk warning value, divides the risk level according to the risk warning value, and formulates corresponding prevention and control measures. The specific process is as follows:

[0073] For each batch of entry and exit personnel, obtain the total number of entry and exit personnel, recorded as the total number of inspectors ZY, and at the same time obtain the total number of high-risk personnel GR and the total number of medium-risk personnel ZR of the same batch of entry and exit personnel, obtain the spatial area AS of the passenger channel and waiting area (car, ship) of the entry and exit port, and use the formula: SM=ZY / AS to obtain the actual density of personnel SM; at the same time, obtain the area area corresponding to the high-risk monitoring channel and the medium-risk monitoring channel, recorded as the high channel area GS and the medium channel area ZS, and use the formula: Kg=(GR / GS) / SM to obtain the high-risk personnel density correction factor Kg, and use the formula: Kz=(ZR / ZS) / SM to obtain the medium-risk personnel density correction factor Kz;

[0074] For the detected diseases corresponding to high-risk and medium-risk persons, according to the data released by the World Health Organization, the number of cities affected by each detected disease in the world in the recent year is obtained. For each detected disease, several intervals of the number of affected cities are preset, and each interval of the number of affected cities corresponds to a transmission risk value. For each detected disease corresponding to high-risk persons, it is matched with the corresponding several intervals of the number of affected cities, and the corresponding transmission risk value CFi is output, i=1, 2, ..., n; n is the total number of detected diseases for high-risk persons. For each detected disease corresponding to a high-risk person, the corresponding number of high-risk persons RYi is obtained. At the same time, according to the four seasons of spring, summer, autumn and winter, the corresponding seasonal transmission impact factors are preset respectively, and the current season is clarified. This season is matched with all seasonal transmission impact factors corresponding to the detected disease, and the transmission impact factor SJi corresponding to the current season is output; using the formula: , and obtain the high-wind transmission value CFZ; the larger the high-wind transmission value, the wider the global spread of the detected disease carried by the high-risk group of this batch of inbound and outbound personnel, and the more cities involved; the implementation method of analyzing the high-wind transmission value is recorded as the risk transmission analysis method, and similarly, the risk transmission analysis method is used to analyze the risk transmission of the detected disease corresponding to the medium-risk personnel to obtain the stroke transmission value ZFC;

[0075] Obtain the fatality rate of each detected disease corresponding to high-risk and medium-risk individuals from authoritative medical databases, research literature, and public health agency reports. The fatality rate of the detected disease corresponding to high-risk individuals is marked as high-risk fatality rate GLi; use the formula: , get the high stroke hazard value GFS, and record the implementation method of analyzing the high stroke hazard value as the hazard degree analysis method. Similarly, use the hazard degree analysis method to analyze the hazard degree of the detected disease corresponding to the medium-risk personnel to get the stroke hazard value ZFS;

[0076] The total number of inspectors ZY, high-risk transmission value CFZ, medium-risk transmission value ZFC, high-risk hazard value GFS and stroke hazard value ZFS corresponding to the current batch are normalized and substituted into the preset formula model: FYZ=ZY×w1+CFZ×w2+ZFC×w3+GFS×w4+ZFS×w5 to obtain the risk warning value FYZ, where w1, w2, w3, w4 and w5 are preset weight coefficients; the larger the risk warning value, the greater the public health and safety challenges faced by the entry and exit ports in terms of personnel flow, disease transmission range and degree of hazard, and the higher the required warning level;

[0077] Three warning levels are preset, namely level one, level two and level three, and each warning level corresponds to a risk warning value range, where level one is smaller than level two, and level two is smaller than level three. The higher the warning level, the higher the risk level and the greater the intensity of screening for people entering and leaving the country. By matching the risk warning value corresponding to this batch of people entering and leaving the country with the risk warning value ranges corresponding to the three warning levels, the corresponding warning level is output, and prevention and control measures of the corresponding level are implemented. The higher the warning level, the stricter the prevention and control measures to be implemented.

[0078] It should be noted that by comprehensively considering factors such as the total number of inspectors, the number of high- and medium-risk personnel, the area of ​​ports and monitoring channels to calculate the personnel density correction factor, spatial factors can be incorporated into the risk assessment system to reflect the impact of the relative density of high- and medium-risk personnel in different regions on the risk of disease transmission. Combined with the data of the World Health Organization, the high-wind transmission value and the stroke transmission value are calculated based on the number of cities affected by the disease globally and the seasonal transmission influencing factor. The disease transmission risk is comprehensively assessed from multiple dimensions such as the global transmission range and seasonal changes, and the dynamics and complexity of disease transmission are fully taken into account, which improves the scientificity and accuracy of risk assessment. Analyzing the high-wind hazard value and the stroke hazard value helps to measure the degree of harm of infectious diseases to people entering and leaving the country. By dividing into different warning levels and taking different prevention and control measures, it helps to achieve precise prevention and control according to the degree of risk, which not only avoids the waste of resources caused by excessive prevention and control, but also ensures effective prevention and control of disease transmission under different risk conditions, and protects the public health safety of entry and exit ports.

[0079] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A disease monitoring, analysis and early warning system for entry and exit ports, comprising: Data collection and monitoring module, personnel classification monitoring module, risk judgment and early warning module, characterized by: The data collection and monitoring module collects test information and monitors diseases of people entering and leaving the country; the test information includes: appearance characteristics information and personal health information; disease monitoring is carried out by setting up monitoring channels of different levels; The personnel classification detection module marks risk cities according to the infectious disease situation in the city, compares the cities that the inbound and outbound personnel pass through, and determines the corresponding high-incidence infectious diseases as the detection diseases for those who pass through the risk cities; for each detection disease, a corresponding disease symptom library and disease feature library are constructed; the disease symptom library covers various symptoms corresponding to the disease, and the disease feature library reflects the relevant appearance characteristics when the disease occurs; at the same time, the diagnosis values ​​are preset for the symptoms in the disease symptom library and the appearance characteristics in the disease feature library; During the actual test, the symptoms in the personal health information of the inbound and outbound personnel are matched with the disease symptom database; the actual deviation of the appearance characteristics in the appearance characteristic information of the personnel is analyzed and compared with the preset deviation standards in the disease characteristic database; the diagnosis values ​​corresponding to the successfully matched symptoms and the appearance characteristics that meet the deviation standards are summarized respectively, and then the total symptom evaluation value and the total characteristic evaluation value are obtained; Analyze the disease risk value based on the total symptom and feature evaluation values, mark people at different risk levels accordingly, and arrange corresponding risk detection channels for infectious disease screening; The risk assessment and early warning module analyzes the number of people entering and leaving the country, the distribution of risk personnel, the scope of disease transmission, seasonal factors, and the disease mortality rate to obtain the total number of inspectors, high-wind transmission value, stroke transmission value, high-wind mortality rate, and stroke mortality rate, and conducts a comprehensive analysis to obtain the risk warning value, divides the risk level according to the risk warning value, and formulates corresponding prevention and control measures.

2. The disease monitoring, analysis and early warning system for entry and exit ports according to claim 1 is characterized by: The specific process of the data collection and monitoring module to collect information on entry and exit personnel is as follows: Collect test information and conduct disease monitoring on people entering and leaving the country at the passenger passages and waiting areas at entry and exit ports; Capture the appearance characteristics of people entering and leaving the country; Appearance features include: eye features, mouth features, facial muscle features, hand movement features, leg movement features, and body posture features; The personal health information of people entering and leaving the country shall be collected; personal health information includes: recent travel history, whether there are symptoms of illness, and symptoms of illness include: fever, cough, and diarrhea.

3. The disease monitoring, analysis and early warning system for entry and exit ports according to claim 2 is characterized by: The specific process of disease monitoring for entry-exit personnel in the data collection and monitoring module is as follows: Establish three disease monitoring channels, namely low-risk monitoring channel, medium-risk monitoring channel and high-risk monitoring channel; The low-risk monitoring channel is equipped with infrared sensor measurement equipment to measure the body temperature of people entering and leaving the country, and simultaneously collect their body temperature information; The medium-risk monitoring channel is equipped with antigen detectors based on the equipment of the low-risk monitoring channel, which are used to conduct antigen reagent tests on people entering and leaving the country and collect reagent test data; The high-risk monitoring channel is equipped with infrared sensor measurement equipment and antigen detectors, and is equipped with biochip detectors to collect disease samples from people entering and leaving the country. After the disease samples are collected, the disease samples are tested. The disease samples include: blood samples, respiratory samples, and saliva samples; And collect disease sample testing data.

4. The disease monitoring, analysis and early warning system for entry and exit ports according to claim 3 is characterized by: The specific process of analyzing the total symptom evaluation value by the personnel classification detection module is as follows: Cities that have shown a high incidence of infectious diseases so far are marked as risk cities, and a risk city list is formed. For each inbound and outbound person, the corresponding appearance feature information and personal health information are retrieved from the data collection and monitoring module. The cities that the inbound and outbound person has passed through during his or her travels are obtained based on his or her recent travel history. Each city that the inbound and outbound person has passed through is compared with the risk city list one by one to detect whether any of the cities that have been passed through are marked as risk cities; If there are risky cities among the cities along the route, obtain the highly infectious diseases corresponding to all risky cities along the route and mark them as detected diseases; establish a corresponding disease symptom library and disease feature library for each detected disease; establish a disease symptom library containing all symptoms corresponding to the detected disease, and a disease feature library containing all appearance features corresponding to the detected disease; For each detected disease, each disease symptom in the preset disease symptom library corresponds to a disease diagnosis value. The disease symptoms in the personal health information of the entry and exit personnel are matched with all the disease symptoms in the disease symptom library. If the same disease symptoms exist, the corresponding disease diagnosis value is output, and then all the disease diagnosis values ​​corresponding to the same disease symptoms are added together to obtain the symptom total evaluation value ZP.

5. The disease monitoring, analysis and early warning system for entry and exit ports according to claim 4 is characterized by: The specific process of analyzing the total feature evaluation value of the personnel classification detection module is as follows: For eye features, mouth features, facial muscle features, hand movement features, leg movement features, and body posture features, establish parameter ranges for various appearance features under normal conditions; for each detected disease, preset the deviation intervals of various appearance features in the disease feature library relative to the normal range under the diseased state, which are recorded as the disease feature deviation interval standard; calculate the deviation values ​​of various appearance features in the appearance feature information of entry-exit personnel relative to the normal range, which are recorded as the actual deviation values ​​of personnel features, and each type of appearance feature in the preset disease feature library corresponds to a feature diagnosis value; For each type of appearance feature in the disease feature library, the actual deviation value of the corresponding personnel feature is matched with the disease feature deviation interval standard corresponding to this type of appearance feature. If the actual deviation value of the personnel feature is within the disease feature deviation interval standard, the feature diagnosis value corresponding to this type of appearance feature is output; then the feature diagnosis values ​​of all appearance feature categories are summarized to obtain the feature total evaluation value TP.

6. The disease monitoring, analysis and early warning system for entry and exit ports according to claim 5 is characterized by: The personnel classification detection module analyzes the disease risk value, marks the personnel at different risk levels, and arranges corresponding risk detection channels for infectious disease screening. The specific process is as follows: For each detected disease, the corresponding symptom total evaluation value ZP and feature total evaluation value TP are normalized, and the disease risk value JFX is obtained using the formula: JFX=ZP×a1+TP×a2, where a1 and a2 are preset weight coefficients; the disease risk value corresponding to the entry-exit personnel is compared with the disease risk value threshold. If the disease risk value is greater than or equal to the disease risk value threshold, the entry-exit personnel is marked as a suspected patient of the detected disease; If the corresponding disease risk value of an entry-exit person is greater than or equal to the corresponding disease risk value threshold in the calculation of multiple disease risk values, the entry-exit person will be marked as a suspected patient of multiple detected diseases; Entry-exit persons who are marked as suspected patients of a certain or multiple detectable diseases will be recorded as high-risk persons; Those entering and leaving the country who are not marked as suspected patients of any disease detected will be recorded as medium-risk persons; If there is no risk city among the cities that the inbound and outbound personnel pass through during their travel, the inbound and outbound personnel will be recorded as low-risk personnel; For every person entering or leaving the country, they will be assigned to the risk detection channel of the corresponding risk level for detection according to the corresponding risk level.

7. The disease monitoring, analysis and early warning system for entry and exit ports according to claim 6 is characterized by: The specific process of analyzing the total number of inspectors, high-risk transmission value, and moderate-risk transmission value by the risk judgment and early warning module is as follows: For each batch of entry and exit personnel, obtain the total number of entry and exit personnel, recorded as the total number of inspectors ZY, and at the same time obtain the total number of high-risk personnel GR and the total number of medium-risk personnel ZR of the same batch of entry and exit personnel, obtain the spatial area AS of the passenger channel and waiting area of ​​the entry and exit port, and use the formula: SM=ZY / AS to obtain the actual density of personnel SM; at the same time, obtain the area corresponding to the high-risk monitoring channel and the medium-risk monitoring channel, recorded as the high channel area GS and the medium channel area ZS, and use the formula: Kg=(GR / GS) / SM to obtain the high-risk personnel density correction factor Kg, and use the formula: Kz=(ZR / ZS) / SM to obtain the medium-risk personnel density correction factor Kz; For the detected diseases corresponding to high-risk and medium-risk persons, obtain the number of cities affected by each detected disease in the world within one year. For each detected disease, preset several intervals of the number of affected cities, and each interval of the number of affected cities corresponds to a transmission risk value. For each detected disease corresponding to high-risk persons, match it with the corresponding several intervals of the number of affected cities, and output the corresponding transmission risk value CFi, i=1, 2, ..., n; n is the total number of detected diseases for high-risk persons. For each detected disease corresponding to high-risk persons, obtain the corresponding number of high-risk persons RYi, and preset seasonal transmission influence factors respectively, clarify the current season, match this season with all seasonal transmission influence factors corresponding to the detected disease, and output the seasonal transmission influence factor SJi corresponding to the current season; use the formula: , and obtain the high-wind transmission value CFZ; the implementation method of analyzing the high-wind transmission value is recorded as the risk transmission analysis method. Similarly, the risk transmission analysis method is used to analyze the risk transmission of the detected disease corresponding to the medium-risk personnel to obtain the stroke transmission value ZFC.

8. The disease monitoring, analysis and early warning system for entry and exit ports according to claim 7 is characterized by: The specific process of analyzing the high-risk and stroke-related mortality rates by the risk judgment and early warning module is as follows: Obtain the fatality rate of each detected disease corresponding to high-risk personnel and medium-risk personnel. The fatality rate of the detected disease corresponding to high-risk personnel is marked as high-risk fatality rate GLi; use the formula: , get the high stroke hazard value GFS, and analyze the implementation method of the high stroke hazard value as the hazard level analysis method. Similarly, use the hazard level analysis method to analyze the hazard level of the detected disease corresponding to the medium-risk personnel to get the stroke hazard value ZFS.

9. The disease monitoring, analysis and early warning system for entry and exit ports according to claim 8, characterized in that: The risk judgment and early warning module analyzes the risk warning value, divides the risk level according to the risk warning value, and formulates corresponding prevention and control measures. The specific process is as follows: The total number of inspectors ZY, high-risk transmission value CFZ, medium-risk transmission value ZFC, high-risk hazard value GFS and stroke hazard value ZFS corresponding to the current batch are normalized and substituted into the preset formula model: FYZ=ZY×w1+CFZ×w2+ZFC×w3+GFS×w4+ZFS×w5 to obtain the risk warning value FYZ, where w1, w2, w3, w4 and w5 are preset weight coefficients; Three warning levels are preset, namely level one, level two and level three, and each warning level corresponds to a risk warning value range. By matching the risk warning value corresponding to this batch of inbound and outbound personnel with the risk warning value ranges corresponding to the three warning levels, the corresponding warning level is output and the corresponding level of prevention and control measures are implemented.

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