Sensing control management system based on risk assessment

Abstract

The invention discloses a risk assessment-based sensing control management system, which comprises an information acquisition module, a model construction module, a risk assessment module and a prevention and control decision module, and is characterized in that the information acquisition module is used for acquiring initial air information, current personal information, historical place information and current place information; the model building module is used for building a pathogen content prediction model by utilizing initial air information, historical place information and current place information, rapidly predicting the content of pathogens in the current air and improving the risk assessment speed, and the risk assessment module is used for calculating immunity scores and potential risks and predicting direct risks. The individual infection risk is calculated and evaluated according to the immunity score, the direct risk and the potential risk, the prevention and control decision module makes prevention and control measures according to the evaluation result, the efficiency and the comprehensiveness of risk evaluation are improved, the prevention and control measures can be implemented in time, and the infection rate is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field, and in particular to an infection control management system based on risk assessment. Background Art

[0002] In human life, we are often accompanied by the invasion of various infectious diseases. The prevention of infectious diseases has always been an extremely important thing for human society. Only by timely prevention can we reduce the probability of illness and reduce unnecessary disease harm.

[0003] When assessing the infection risk of an individual, the content of pathogens in the place where the individual is located is one of the most direct influencing factors. However, in the prior art, the method for detecting the content of pathogens in a place is generally to sample and then culture the pathogens for testing. This method is time-consuming and leads to large errors. It is impossible to accurately assess the infection risk of an individual. In addition, the risk assessment method in the prior art is too single and does not integrate multiple factors such as individuals and the environment for assessment. It lacks comprehensiveness and cannot make timely and effective prevention and control measures. Summary of the invention

[0004] The technical problem solved by the present invention is that the method of detecting the pathogen content in the existing technology is generally to sample and then culture the pathogens for testing. This method is time-consuming and leads to large errors, and it is impossible to accurately assess the individual's infection risk. In addition, the risk assessment method in the existing technology is too single and does not integrate multiple factors such as individuals and the environment for assessment. It lacks comprehensiveness and cannot make timely and effective prevention and control measures.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: an infection control management system based on risk assessment, characterized in that it comprises: the system comprises an information collection module, a model building module, a risk assessment module and a prevention and control decision module;

[0006] The information collection module includes an air information collection unit, a personal information collection unit and a place information collection unit, wherein the air information collection unit is used to collect initial air information in advance, the personal information collection unit is used to collect current personal information, and the place information collection unit is used to collect historical place information and current place information;

[0007] The model building module is used to build a relationship model among historical place information, current place information and initial air information, and predict current air information based on the historical place information, current place information and initial air information;

[0008] The risk assessment module includes an immunity scoring unit, a direct risk prediction unit and a potential risk calculation unit. The immunity scoring unit calculates the individual's immunity score based on current personal information, the direct risk prediction unit predicts the direct risk in the current air based on current air information, and the potential risk calculation unit calculates the potential risk in the current place based on current place information. According to the weights of the immunity score, direct risk and potential risk, the individual's infection risk is calculated and evaluated to obtain an infection risk score, and the infection risk score is transmitted to the prevention and control decision module;

[0009] The prevention and control decision module is used to receive the infection risk score, classify the infection risk level according to the infection risk score, and formulate prevention and control measures according to the infection risk level.

[0010] Preferably, the information collection module includes a personal information collection unit, an air information collection unit and a place information collection unit;

[0011] The personal information collection unit includes a face recognition camera, which is used to collect personal facial images, extract image features of the personal facial images after denoising, graying and edge detection, and search for a facial image with the highest similarity to the personal facial image from a personal facial image library based on the image features, thereby determining the personal identity, and matching personal information corresponding to the personal identity from the database, and outputting it as current personal information, wherein the current personal information includes name, gender, age, genetic genes, pathogen infection history, vaccination history and other disease history;

[0012] The air information collection unit is used to collect initial air information in advance. The initial air information is the name and content of pathogens in the air at the initial time node. The collection method is:

[0013] Using air sampling equipment to collect air samples, inoculating the collected air samples onto culture media, culturing under suitable conditions to allow pathogens to multiply, performing component analysis on the propagated pathogens to determine the names of the pathogens, using quantitative analysis methods to determine the content of the pathogens in the air, and combining the names of the pathogens and the content of the pathogens to output as initial air information;

[0014] The place information collection unit is used to collect historical place information and current place information, taking the time node of collecting initial air information as the initial time node, obtaining the sum of all infected persons in the place that has entered the current preset range from the initial time node to the current time node, and outputting it as historical place information, and obtaining the number of infected persons in the place located in the current preset range at the current time node, and outputting it as current place information.

[0015] Preferably, the model building module is used to build a relationship model among historical place information, current place information and initial air information, and predict current air information based on the historical place information, current place information and initial air information. The training process includes:

[0016] Pre-acquire multiple sets of training data sets, wherein the multiple sets of training data sets include 80% training sets and 20% test sets, and the training data sets include initial air information, historical location information, and current location information;

[0017] Inputting the initial air information, historical site information, and current site information in the training set into a machine learning model, outputting predicted current air information, and obtaining a pathogen content prediction model;

[0018] The initial air information, historical site information and current site information in the test set are input into the pathogen content prediction model, and the accuracy of the pathogen content prediction model is verified. When the accuracy reaches the accuracy threshold, the training is completed to obtain a trained pathogen content prediction model.

[0019] Preferably, the immunity scoring unit calculates the individual's immunity score based on the current personal information, specifically including:

[0020] An individual's immunity is scored based on their name, sex, age, genetics, pathogen infection history, vaccination history, and other medical history:

[0021] When the age is between 18 and 30 years old, the age score is 20 points; when the age is between 8 and 18 years old or between 30 and 45 years old, the age score is 15 points; when the age is between 3 and 8 years old or between 45 and 60 years old, the age score is 10 points; when the age is between 0 and 3 years old or over 60 years old, the age score is 5 points;

[0022] When there is no genetic disease gene, the genetic gene score is 20 points, when there is one genetic disease gene, the genetic gene score is 18 points, when there are two genetic disease genes, the genetic gene score is 16 points, when there are three genetic disease genes, the genetic gene score is 14 points, and so on, the lowest genetic gene score is 0 points;

[0023] When there is a history of pathogen infection, the pathogen immunity score is 20 points, and when there is no history of pathogen infection, the pathogen immunity score is 10 points;

[0024] When there is a vaccination history, the vaccine immunity score is 20 points, and when there is no vaccination history, the vaccine immunity score is 10 points;

[0025] When there is no history of other diseases, the other immune score is 20 points, when there is a history of one other disease, the other immune score is 18 points, when there are two other disease histories, the other immune score is 16 points, when there are three other disease histories, the other immune score is 14 points, and so on, and the lowest other immune score is 0 points;

[0026] An individual's immunity score is calculated as:

[0027] MY = age score + genetic score + pathogen immunity score + vaccine immunity score + other immunity scores;

[0028] Among them, MY represents the immunity score.

[0029] Preferably, the direct risk prediction unit predicts the direct risk in the current air according to the current air information, specifically:

[0030] Inputting initial air information, historical site information and current site information into a pathogen content prediction model, and outputting predicted current air information, wherein the current air information is the current pathogen content in the air;

[0031] Comparing the current pathogen content with the pathogen content risk threshold, and calculating the percentage by which the current pathogen content exceeds the pathogen content risk threshold as the direct risk;

[0032] The direct risk is calculated as follows:

[0033]

[0034] Among them, ZF represents direct risk, B represents the current pathogen content, and B 0 Indicates the pathogen content risk threshold.

[0035] Preferably, the potential risk calculation unit calculates the potential risk in the current place according to the current place information, specifically:

[0036] Get the current location information, get the number of infected people in the current preset range at the current time node, calculate the density of infected people based on the area of ​​the current preset range, and use the density of infected people as a potential risk;

[0037] The calculation formula for the potential risk is:

[0038]

[0039] Among them, QF represents potential risk, R represents the number of infected people in the current preset range, and A represents the area of ​​the current preset range.

[0040] Preferably, the infection risk of an individual is calculated and evaluated according to the immunity score, the weights of the direct risk and the potential risk, to obtain an infection risk score;

[0041] The infection risk is calculated as:

[0042] GF=α(1-MY)%+βZF+γQF+θ

[0043] Among them, GF represents infection risk, MY represents immunity score, ZF represents direct risk, QF represents potential risk, α, β and γ represent the weights of immunity score, direct risk and potential risk respectively, and θ represents the error term;

[0044] The infection risk is in the form of a percentage, and the infection risk is multiplied by 100 to obtain an infection risk score. Preferably, the prevention and control decision module is used to receive the infection risk score and classify the infection risk level according to the infection risk score, specifically including:

[0045] When the infection risk score is 0 to 30 points, there is no infection risk;

[0046] When the infection risk score is 30 to 60 points, it is a first-level infection risk;

[0047] When the infection risk score is 60 to 80 points, it is a secondary infection risk;

[0048] When the infection risk score is greater than 80 points, it is a level 3 infection risk.

[0049] Preferably, the prevention and control decision module formulates prevention and control decisions according to the infection risk level, specifically including:

[0050] When there is no risk of infection, there is no need to formulate prevention and control measures;

[0051] When the infection risk is level one, the level one prevention and control measures are implemented, and the level one prevention and control measures are: sending alcohol disinfection and mask wearing instructions to personal devices;

[0052] When the infection risk is level 2, level 2 prevention and control measures are implemented, which are: sending alcohol disinfection and mask wearing instructions to personal devices, and sending a level 2 prevention and control alarm to the person in charge of the current place, who will conduct a physical examination and observation on the individual;

[0053] When the infection risk is level three, level three prevention and control measures are implemented, which are: sending alcohol disinfection and mask wearing instructions to personal devices, sending a level three prevention and control alarm to the person in charge of the current place, and having the person in charge of the current place conduct a physical examination and observation on the individual, and evacuate, isolate and disinfect the personnel in the current place.

[0054] A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, an infection control management system based on risk assessment is implemented.

[0055] Beneficial effects of the present invention: The present invention constructs a pathogen content prediction model, and uses historical venue information, current venue information and initial air information to quickly predict the pathogen content in the current air, thereby enabling a rapid assessment of an individual's infection risk; and the present invention integrates multiple influencing factors such as personal information, air information and venue information to accurately assess an individual's infection risk. The present invention achieves a rapid and accurate assessment of infection risk. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 A system schematic diagram of an infection control management system based on risk assessment provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0057] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, but not all of the embodiments.

[0058] Reference Figure 1 , is an embodiment of the present invention, and provides an infection control management system based on risk assessment, comprising:

[0059] An infection control management system based on risk assessment, characterized in that it comprises: the system comprises an information collection module, a model building module, a risk assessment module and a prevention and control decision module;

[0060] The information collection module includes an air information collection unit, a personal information collection unit and a place information collection unit, wherein the air information collection unit is used to collect initial air information in advance, the personal information collection unit is used to collect current personal information, and the place information collection unit is used to collect historical place information and current place information;

[0061] The model building module is used to build a relationship model among historical place information, current place information and initial air information, and predict current air information based on the historical place information, current place information and initial air information;

[0062] The risk assessment module includes an immunity scoring unit, a direct risk prediction unit and a potential risk calculation unit. The immunity scoring unit calculates the individual's immunity score based on current personal information, the direct risk prediction unit predicts the direct risk in the current air based on current air information, and the potential risk calculation unit calculates the potential risk in the current place based on current place information. According to the weights of the immunity score, direct risk and potential risk, the individual's infection risk is calculated and evaluated to obtain an infection risk score, and the infection risk score is transmitted to the prevention and control decision module;

[0063] The prevention and control decision module is used to receive the infection risk score, classify the infection risk level according to the infection risk score, and formulate prevention and control measures according to the infection risk level.

[0064] Specifically, by constructing a pathogen content prediction model, using historical venue information, current venue information and initial air information, the pathogen content in the current air can be quickly predicted, so that the individual's infection risk can be quickly assessed; and the present invention combines multiple influencing factors such as personal information, air information, and venue information to accurately assess the individual's infection risk. The present invention achieves a rapid and accurate assessment of infection risk.

[0065] The information collection module includes a personal information collection unit, an air information collection unit and a place information collection unit;

[0066] The personal information collection unit includes a face recognition camera, which is used to collect personal facial images, extract image features of the personal facial images after denoising, graying and edge detection, and search for a facial image with the highest similarity to the personal facial image from a personal facial image library based on the image features, thereby determining the personal identity, and matching personal information corresponding to the personal identity from the database, and outputting it as current personal information, wherein the current personal information includes name, gender, age, genetic genes, pathogen infection history, vaccination history and other disease history;

[0067] The air information collection unit is used to collect initial air information in advance. The initial air information is the name and content of pathogens in the air at the initial time node. The collection method is:

[0068] Using air sampling equipment to collect air samples, inoculating the collected air samples onto culture media, culturing under suitable conditions to allow pathogens to multiply, performing component analysis on the propagated pathogens to determine the names of the pathogens, using quantitative analysis methods to determine the content of the pathogens in the air, and combining the names of the pathogens and the content of the pathogens to output as initial air information;

[0069] Specifically, the suitable conditions are a temperature of 25 to 30° C. and a relative humidity of 50% to 60%, which are suitable growth conditions for most viruses.

[0070] The place information collection unit is used to collect historical place information and current place information, taking the time node of collecting initial air information as the initial time node, obtaining the sum of all infected persons in the place that has entered the current preset range from the initial time node to the current time node, and outputting it as historical place information, and obtaining the number of infected persons in the place located in the current preset range at the current time node, and outputting it as current place information.

[0071] The model building module is used to build a relationship model among historical place information, current place information and initial air information, and predict current air information according to the historical place information, current place information and initial air information. The training process includes:

[0072] Pre-acquire multiple sets of training data sets, wherein the multiple sets of training data sets include 80% training sets and 20% test sets, and the training data sets include initial air information, historical location information, and current location information;

[0073] Inputting the initial air information, historical site information, and current site information in the training set into a machine learning model, outputting predicted current air information, and obtaining a pathogen content prediction model;

[0074] The initial air information, historical site information and current site information in the test set are input into the pathogen content prediction model, and the accuracy of the pathogen content prediction model is verified. When the accuracy reaches the accuracy threshold, the training is completed to obtain a trained pathogen content prediction model.

[0075] Specifically, the pathogen content is obtained by culturing and testing the pathogens as the initial air information. As infected people enter and exit the venue, the pathogen content in the air will increase significantly. The initial air information and the number of infected people are used as input to construct a pathogen content prediction model, which can realize the function of predicting the pathogen content in the air after a period of time.

[0076] The immunity scoring unit calculates the individual's immunity score based on the current personal information, specifically including:

[0077] An individual's immunity is scored based on their name, sex, age, genetics, pathogen infection history, vaccination history, and other medical history:

[0078] When the age is between 18 and 30 years old, the age score is 20 points; when the age is between 8 and 18 years old or between 30 and 45 years old, the age score is 15 points; when the age is between 3 and 8 years old or between 45 and 60 years old, the age score is 10 points; when the age is between 0 and 3 years old or over 60 years old, the age score is 5 points;

[0079] Specifically, adults between the ages of 18 and 30 have the strongest immunity, so their age scores are also the highest. Infants and the elderly have the weakest immunity, so their age scores are also the lowest.

[0080] When there is no genetic disease gene, the genetic gene score is 20 points, when there is one genetic disease gene, the genetic gene score is 18 points, when there are two genetic disease genes, the genetic gene score is 16 points, when there are three genetic disease genes, the genetic gene score is 14 points, and so on, the lowest genetic gene score is 0 points;

[0081] Specifically, when there are genetic disease genes in the body, the body's immunity will be affected and the immunity will be reduced. Therefore, when there are no genetic disease genes in the body, the gene score is the highest;

[0082] When there is a history of pathogen infection, the pathogen immunity score is 20 points, and when there is no history of pathogen infection, the pathogen immunity score is 10 points;

[0083] Specifically, when there is a history of pathogen infection, antibodies against the pathogen will be produced in the human body, so the probability of being infected again will also decrease. Therefore, when there is a history of pathogen infection, the pathogen immunity score is the highest.

[0084] When there is a vaccination history, the vaccine immunity score is 20 points, and when there is no vaccination history, the vaccine immunity score is 10 points;

[0085] Specifically, when there is a history of vaccination, antibodies against the pathogen are produced in the human body, and the probability of infection is not high, so the vaccine immunity score is the highest;

[0086] When there is no history of other diseases, the other immune score is 20 points, when there is a history of one other disease, the other immune score is 18 points, when there are two other disease histories, the other immune score is 16 points, when there are three other disease histories, the other immune score is 14 points, and so on, and the lowest other immune score is 0 points;

[0087] Specifically, when there is a history of other diseases, one's own immunity will be affected and the immunity will be reduced. Therefore, when there is no history of other diseases, the other immunity score is the highest.

[0088] An individual's immunity score is calculated as:

[0089] MY = age score + genetic score + pathogen immunity score + vaccine immunity score + other immunity scores;

[0090] Among them, MY represents immunity score;

[0091] Specifically, an adult M, who is 20 years old, has one genetic gene, has no history of pathogen infection, has been vaccinated, and has a history of other diseases, has an immunity score of:

[0092] MY=20+18+10+20+18=86

[0093] The direct risk prediction unit predicts the direct risk in the current air according to the current air information, specifically:

[0094] Inputting initial air information, historical site information and current site information into a pathogen content prediction model, and outputting predicted current air information, wherein the current air information is the current pathogen content in the air;

[0095] Comparing the current pathogen content with the pathogen content risk threshold, and calculating the percentage by which the current pathogen content exceeds the pathogen content risk threshold as the direct risk;

[0096] The direct risk is calculated as follows:

[0097]

[0098] Among them, ZF represents direct risk, B represents the current pathogen content, and B 0 Indicates the pathogen content risk threshold.

[0099] Specifically, assuming that the pathogen content risk threshold is 1 unit, and the current pathogen content is 1.8 units, the direct risk is:

[0100]

[0101] The potential risk calculation unit calculates the potential risk in the current place according to the current place information, specifically:

[0102] Get the current location information, get the number of infected people in the current preset range at the current time node, calculate the density of infected people based on the area of ​​the current preset range, and use the density of infected people as a potential risk;

[0103] The calculation formula for the potential risk is:

[0104]

[0105] Among them, QF represents potential risk, R represents the number of infected people in the current preset range, and A represents the area of ​​the current preset range.

[0106] Specifically, assuming that the number of infected people in the current preset range is 2, and the area of ​​the current preset range is 100 units, then the potential risk is:

[0107]

[0108] The individual's infection risk is calculated and evaluated according to the immunity score, the weights of the direct risk and the potential risk, to obtain an infection risk score;

[0109] The infection risk is calculated as:

[0110] GF=α(1-MY)%+βZF+γQF+θ

[0111] Among them, GF represents infection risk, MY represents immunity score, ZF represents direct risk, QF represents potential risk, α, β and γ represent the weights of immunity score, direct risk and potential risk respectively, and θ represents the error term;

[0112] Specifically, assuming that α, β, and γ are 0.2, 0.7, and 0.1 respectively, and θ is 10%, substitute the immunity score of 86, the direct risk of 80%, and the potential risk of 2% into the infection risk calculation formula:

[0113] GF=α(1-MY)%+βZF+γQF+θ=0.2×(1-86)%+0.7×80%+0.1×2%+10%=69%

[0114] The infection risk is in the form of a percentage. The infection risk is multiplied by 100 to obtain an infection risk score.

[0115] Multiplying 69% by 100 gives an infection risk score of 69.

[0116] The prevention and control decision module is used to receive the infection risk score and classify the infection risk level according to the infection risk score, specifically including:

[0117] When the infection risk score is 0 to 30 points, there is no infection risk;

[0118] When the infection risk score is 31 to 60 points, it is a first-level infection risk;

[0119] When the infection risk score is 61 to 80 points, it is a secondary infection risk;

[0120] When the infection risk score is greater than 81 points, it is a level 3 infection risk.

[0121] The prevention and control decision module makes prevention and control decisions according to the infection risk level, specifically including:

[0122] When there is no risk of infection, there is no need to formulate prevention and control measures;

[0123] When the infection risk is level one, the level one prevention and control measures are implemented, and the level one prevention and control measures are: sending alcohol disinfection and mask wearing instructions to personal devices;

[0124] When the infection risk is level 2, level 2 prevention and control measures are implemented, which are: sending alcohol disinfection and mask wearing instructions to personal devices, and sending a level 2 prevention and control alarm to the person in charge of the current place, who will conduct a physical examination and observation on the individual;

[0125] When the infection risk is level three, level three prevention and control measures are implemented, which are: sending alcohol disinfection and mask wearing instructions to personal devices, sending a level three prevention and control alarm to the person in charge of the current place, and having the person in charge of the current place conduct a physical examination and observation on the individual, and evacuate, isolate and disinfect the personnel in the current place.

[0126] Specifically, when the infection risk score is 69 points, it is a level 2 infection risk, and level 2 prevention and control measures are implemented, alcohol disinfection and mask wearing instructions are sent to personal devices, and a level 2 prevention and control alarm is sent to the person in charge of the current place. The person in charge of the current place will conduct physical examinations and observations on the individual, and conduct regular physical examinations and observations on the individual to determine whether there are signs of infection.

[0127] The present invention, by constructing a pathogen content prediction model, can quickly predict the pathogen content in the current air by using historical location information, current location information and initial air information, so as to quickly evaluate the infection risk of an individual; and the present invention combines multiple influencing factors such as personal information, air information and location information to accurately evaluate the infection risk of an individual, thereby achieving a rapid and accurate assessment of the infection risk, so that prevention and control measures can be implemented in a timely and effective manner to reduce the infection rate.

[0128] It should be understood by those skilled in the art that the embodiments of the present invention can be provided as methods, systems or computer program products. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program codes. Among them, the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, referred to as EPROM), programmable read-only memory (Programmable Red-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, disk or optical disk. These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0129] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A risk assessment-based infection control management system, characterized in that: include: The system includes an information collection module, a model building module, a risk assessment module and a prevention and control decision module; The information collection module includes an air information collection unit, a personal information collection unit and a place information collection unit, wherein the air information collection unit is used to collect initial air information in advance, the personal information collection unit is used to collect current personal information, and the place information collection unit is used to collect historical place information and current place information; The model building module is used to build a relationship model among historical place information, current place information and initial air information, and predict current air information based on the historical place information, current place information and initial air information; The risk assessment module includes an immunity scoring unit, a direct risk prediction unit and a potential risk calculation unit. The immunity scoring unit calculates the individual's immunity score based on current personal information, the direct risk prediction unit predicts the direct risk in the current air based on current air information, and the potential risk calculation unit calculates the potential risk in the current place based on current place information. According to the weights of the immunity score, direct risk and potential risk, the individual's infection risk is calculated and evaluated to obtain an infection risk score, and the infection risk score is transmitted to the prevention and control decision module; The prevention and control decision module is used to receive the infection risk score, classify the infection risk level according to the infection risk score, and formulate prevention and control measures according to the infection risk level.

2. The infection control management system based on risk assessment as claimed in claim 1, characterized in that: The information collection module includes a personal information collection unit, an air information collection unit and a place information collection unit; The personal information collection unit includes a face recognition camera, which is used to collect personal facial images, extract image features of the personal facial images after denoising, graying and edge detection, and search for a facial image with the highest similarity to the personal facial image from a personal facial image library based on the image features, thereby determining the personal identity, and matching personal information corresponding to the personal identity from the database, and outputting it as current personal information, wherein the current personal information includes name, gender, age, genetic genes, pathogen infection history, vaccination history and other disease history; The air information collection unit is used to collect initial air information in advance. The initial air information is the name and content of pathogens in the air at the initial time node. The collection method is: Using air sampling equipment to collect air samples, inoculating the collected air samples onto culture media, culturing under suitable conditions to allow pathogens to multiply, performing component analysis on the propagated pathogens to determine the names of the pathogens, using quantitative analysis methods to determine the content of the pathogens in the air, and combining the names of the pathogens and the content of the pathogens to output as initial air information; The place information collection unit is used to collect historical place information and current place information, taking the time node of collecting the initial air information as the initial time node, obtaining the total number of all infected persons in the place that has entered the current preset range from the initial time node to the current time node, and outputting it as the historical place information, and obtaining the number of infected persons in the place located in the current preset range at the current time node, and outputting it as the current place information.

3. The infection control management system based on risk assessment as claimed in claim 2, characterized in that: The model building module is used to build a relationship model among historical place information, current place information and initial air information, and predict current air information according to the historical place information, current place information and initial air information. The training process includes: Pre-acquire multiple sets of training data sets, wherein the multiple sets of training data sets include 80% training sets and 20% test sets, and the training data sets include initial air information, historical location information, and current location information; Inputting the initial air information, historical site information, and current site information in the training set into a machine learning model, outputting predicted current air information, and obtaining a pathogen content prediction model; The initial air information, historical site information and current site information in the test set are input into the pathogen content prediction model, and the accuracy of the pathogen content prediction model is verified. When the accuracy reaches the accuracy threshold, the training is completed to obtain a trained pathogen content prediction model.

4. The infection control management system based on risk assessment as claimed in claim 3, characterized in that: The immunity scoring unit calculates the individual's immunity score based on the current personal information, specifically including: An individual's immunity is scored based on their name, sex, age, genetics, pathogen infection history, vaccination history, and other medical history: When the age is between 18 and 30 years old, the age score is 20 points; when the age is between 8 and 18 years old or between 30 and 45 years old, the age score is 15 points; when the age is between 3 and 8 years old or between 45 and 60 years old, the age score is 10 points; when the age is between 0 and 3 years old or over 60 years old, the age score is 5 points; When there is no genetic disease gene, the genetic gene score is 20 points, when there is one genetic disease gene, the genetic gene score is 18 points, when there are two genetic disease genes, the genetic gene score is 16 points, when there are three genetic disease genes, the genetic gene score is 14 points, and so on, the lowest genetic gene score is 0 points; When there is a history of pathogen infection, the pathogen immunity score is 20 points, and when there is no history of pathogen infection, the pathogen immunity score is 10 points; When there is a vaccination history, the vaccine immunity score is 20 points, and when there is no vaccination history, the vaccine immunity score is 10 points; When there is no history of other diseases, the other immune score is 20 points, when there is a history of one other disease, the other immune score is 18 points, when there are two other disease histories, the other immune score is 16 points, when there are three other disease histories, the other immune score is 14 points, and so on, and the lowest other immune score is 0 points; An individual's immunity score is calculated as: MY = age score + genetic score + pathogen immunity score + vaccine immunity score + other immunity scores; Among them, MY represents the immunity score.

5. The infection control management system based on risk assessment as claimed in claim 4, characterized in that: The direct risk prediction unit predicts the direct risk in the current air according to the current air information, specifically: Inputting initial air information, historical site information and current site information into a pathogen content prediction model, and outputting predicted current air information, wherein the current air information is the current pathogen content in the air; Comparing the current pathogen content with the pathogen content risk threshold, and calculating the percentage by which the current pathogen content exceeds the pathogen content risk threshold as the direct risk; The direct risk is calculated as follows: Among them, ZF represents direct risk, B represents the current pathogen content, and B0 represents the pathogen content risk threshold.

6. The infection control management system based on risk assessment as claimed in claim 5, characterized in that: The potential risk calculation unit calculates the potential risk in the current place according to the current place information, specifically: Get the current location information, get the number of infected people in the current preset range at the current time node, calculate the density of infected people based on the area of ​​the current preset range, and use the density of infected people as a potential risk; The calculation formula for the potential risk is: Among them, QF represents potential risk, R represents the number of infected people in the current preset range, and A represents the area of ​​the current preset range.

7. The infection control management system based on risk assessment as claimed in claim 6, characterized in that: The individual's infection risk is calculated and evaluated according to the immunity score, the weights of the direct risk and the potential risk, to obtain an infection risk score; The infection risk is calculated as: GF=α(1-MY)%+βZF+γQF+θ Among them, GF represents infection risk, MY represents immunity score, ZF represents direct risk, QF represents potential risk, α, β and γ represent the weights of immunity score, direct risk and potential risk respectively, and θ represents the error term; The infection risk is in the form of a percentage. The infection risk is multiplied by 100 to obtain an infection risk score.

8. The infection control management system based on risk assessment as claimed in claim 7, characterized in that: The prevention and control decision module is used to receive the infection risk score and classify the infection risk level according to the infection risk score, specifically including: When the infection risk score is 0 to 30 points, there is no infection risk; When the infection risk score is 31 to 60 points, it is a first-level infection risk; When the infection risk score is 61 to 80 points, it is a secondary infection risk; When the infection risk score is greater than 81 points, it is a level 3 infection risk.

9. The infection control management system based on risk assessment as claimed in claim 8, characterized in that: The prevention and control decision module makes prevention and control decisions according to the infection risk level, specifically including: When there is no risk of infection, there is no need to formulate prevention and control measures; When the infection risk is level one, the level one prevention and control measures are implemented, and the level one prevention and control measures are: sending alcohol disinfection and mask wearing instructions to personal devices; When the infection risk is level 2, level 2 prevention and control measures are implemented, which are: sending alcohol disinfection and mask wearing instructions to personal devices, and sending a level 2 prevention and control alarm to the person in charge of the current place, who will conduct a physical examination and observation on the individual; When the infection risk is level three, level three prevention and control measures are implemented, which are: sending alcohol disinfection and mask wearing instructions to personal devices, sending a level three prevention and control alarm to the person in charge of the current place, and having the person in charge of the current place conduct a physical examination and observation on the individual, and evacuate, isolate and disinfect the personnel in the current place.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the infection control management system based on risk assessment according to any one of claims 1 to 9 is implemented.

Images