WO2022135197A1 - Procédé de prédiction d'épidémie et dispositif électronique - Google Patents

Procédé de prédiction d'épidémie et dispositif électronique Download PDF

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Publication number
WO2022135197A1
WO2022135197A1 PCT/CN2021/137280 CN2021137280W WO2022135197A1 WO 2022135197 A1 WO2022135197 A1 WO 2022135197A1 CN 2021137280 W CN2021137280 W CN 2021137280W WO 2022135197 A1 WO2022135197 A1 WO 2022135197A1
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user
risk
information
epidemic
electronic device
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PCT/CN2021/137280
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English (en)
Chinese (zh)
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李君劲
吴莲
陈勇
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华为技术有限公司
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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/80—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for detecting, monitoring or modelling epidemics or pandemics, e.g. flu
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
    • A61B5/02055—Simultaneously evaluating both cardiovascular condition and temperature
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/024—Detecting, measuring or recording pulse rate or heart rate
    • A61B5/02438—Detecting, measuring or recording pulse rate or heart rate with portable devices, e.g. worn by the patient
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
    • A61B5/14542—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue for measuring blood gases
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
    • A61B5/1455—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue using optical sensors, e.g. spectral photometrical oximeters
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
    • A61B5/1455—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue using optical sensors, e.g. spectral photometrical oximeters
    • A61B5/14551—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue using optical sensors, e.g. spectral photometrical oximeters for measuring blood gases
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/48—Other medical applications
    • A61B5/4806—Sleep evaluation
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/6802—Sensor mounted on worn items
    • A61B5/681—Wristwatch-type devices
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/10—Protocols in which an application is distributed across nodes in the network
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • H04W4/029—Location-based management or tracking services

Definitions

  • the present application relates to the field of electronic technology, and in particular, to a method and electronic device for epidemic prediction.
  • the outbreak of the epidemic will bring serious harm to society and individuals.
  • people cannot understand the multi-directional epidemic development information in real time based on electronic equipment, and the epidemic prevention and control mainly relies on human screening.
  • this may increase the risk of related staff being infected during the screening process; on the other hand, it cannot enable users to obtain timely and comprehensive regional epidemic development trends.
  • users can get information on the development of the epidemic at any time and understand their own infection risks, it will be convenient for people to rationally plan travel and arrange daily life, etc., which is conducive to epidemic prevention and control.
  • the user's multi-dimensional information is collected through the electronic device of the user terminal and reported to the server, so that the server can predict the epidemic development trend of the relevant area, and the user can timely and conveniently understand himself. health risks and regional epidemic trends.
  • a method for epidemic prediction is provided.
  • the method is applied to an electronic device on the user side.
  • the method mainly includes: the electronic device obtains, from a server, the trajectory information and the infectious disease of a person diagnosed with one or more infectious diseases. feature information, and then use the user's historical trajectory information and the confirmed person's trajectory information stored in the electronic device to determine whether the user has had close contact with the confirmed person.
  • the electronic device will monitor the physiological signs of the user, and calculate the health risk score of the user based on the monitoring results of the physiological signs, and report the health risk score of the physiological signs to the server, so that the server will be based on the health risk score. Predict the trend of epidemic risk in a specific area.
  • the electronic device can obtain the trajectory information of the diagnosed person from the server, and the trajectory information includes location information and time information corresponding to the location information, such as the location corresponding to the confirmed person at a certain moment.
  • the electronic device may locate the user, acquire and store the user's trajectory information (eg, GPS information).
  • the user's trajectory information eg, GPS information
  • the electronic device may also acquire characteristic information of infectious diseases from the server, and the characteristic information may include: transmission route, transmission distance, incubation period, and physiological signs related to infectious diseases, etc. of infectious diseases.
  • physiological signs related to infectious diseases mentioned in this application may refer to the physiological signs that are affected when a user is infected with an infectious disease virus. If blood oxygen drops, the physiological signs related to the infectious disease can be body temperature and blood oxygen saturation; or, after viral infection of some infectious diseases, the heart rate, body temperature, and blood oxygen saturation of the infected person will change.
  • the physiological signs related to the infectious disease may be heart rate, body temperature, and blood oxygen saturation.
  • the electronic device may monitor the physiological signs of the user after obtaining authorization from the user.
  • the electronic device may report the user's health risk score after obtaining the user's authorization.
  • the electronic device may include a display screen.
  • the electronic device may determine that the user is a close contact based on the user's historical movement trajectory and the movement trajectory of the diagnosed person, the electronic device may The first information is displayed to the user through the display screen, and the first information can be used to query the user whether it is determined to be a close contact of the confirmed person.
  • the user can input first confirmation information into the electronic device, indicating that the user is a close contact of the confirmed person.
  • the electronic device may further display second information, which is The second information is used to request the user to monitor physiological signs; after that, after the electronic device obtains authorization from the user, for example, the electronic device receives the second confirmation information input by the user, and the second confirmation information is used to indicate that the user agrees to the electronic device to perform physiological monitoring.
  • the electronic device may monitor the physiological signs of the user, or the electronic device may instruct other associated devices to monitor the physiological signs of the user.
  • the physiological signs monitored by the electronic device include physiological signs related to infectious diseases.
  • the electronic device can focus on monitoring the physiological signs of users who are at high risk of being infected, and timely give early warnings to the health risks of users, so that users can take corresponding measures in a timely manner, such as timely Seek medical attention to avoid further damage to the user's health.
  • the electronic device may also display first prompt information, where the first prompt information is used to indicate to the user There are health risks.
  • the electronic device may further display third information, where the third information is used to request the user to report the monitoring data of the physiological signs; if the user agrees to report his physiological signs monitoring data, the user can input the third confirmation information to the electronic device, the third confirmation information is used to indicate the consent to report the data of the physiological sign monitoring; after receiving the third confirmation information, the electronic device can report it to the server according to the user's instruction User's physiological signs monitoring data.
  • the electronic device may receive first indication information sent by the server, where the first indication information is used to indicate the epidemic risk level of the first area and/or the risk level of the first area. Total number of people at risk; based on the first indication information, the electronic device can display fourth information, and the fourth information can prompt the user of the epidemic risk level of the first area and/or the total number of people at risk in the first area.
  • the server predicts the epidemic situation in the first area based on the data reported by the electronic device, including the total number of persons at risk (including the number of confirmed persons and suspected persons) in the first area, and then the server may The risk level of the first area is sent to the electronic device, and the electronic device displays it to the user.
  • the above method by prompting the user of the epidemic risk level and/or the total number of people at risk in a specific area, it is convenient for the user to understand the epidemic risk area, reasonably adjust the travel route, and reduce the risk of being infected by an infectious disease.
  • the electronic device calculates the user's health risk score according to the user's physiological sign information and infectious disease characteristic information, which may include: at least one first physiological sign associated with the infectious disease, where the first physiological sign is a feature affected by the infectious disease; after that, obtain monitoring data of at least one first physiological sign information of the user; and then according to the at least one physiological sign
  • the monitoring data is weighted and calculated by at least one first preset weight corresponding to each other, so as to obtain the health risk score of the user.
  • the server after determining that the user is a close contact of the epidemic based on the trajectory information of the user and the confirmed patient, with the authorization of the user, physical sign detection is carried out to realize automatic alarm on the risk of the epidemic. , and allows the server to predict the development of the epidemic according to the reported data, reducing human participation, thereby reducing the number of infected people and improving the efficiency of epidemic prevention and control.
  • the electronic device may further display the monitoring data of the first physiological sign corresponding to different time points to the user; and/or, display the monitoring data of the first physiological sign Monitor data trends over time.
  • the electronic device may mark the epidemic risk level of the region at the position corresponding to the first region on the map page according to the epidemic risk level of the first region predicted by the server.
  • the total risk population corresponding to the area may also be marked on the map page. So that the user can intuitively obtain the epidemic risk level of the first area or the total number of people at risk in the first area from the map page displayed by the electronic device.
  • the characteristic information of the infectious disease includes the transmission distance of the infectious disease, and determining the infectious disease according to the trajectory information of the user and the trajectory information of the confirmed person.
  • the user is a close contact of the confirmed person, including: determining the contact distance between the user and the confirmed person according to the user's trajectory information and the confirmed person's trajectory information; when the contact distance is smaller than the confirmed person
  • the transmission distance is determined, and the contact time between the user and the confirmed person is greater than the first threshold, it is determined that the user is a close contact of the confirmed person.
  • the server after determining that the user is a close contact of the epidemic based on the trajectory information of the user and the confirmed patient, with the authorization of the user, physical sign detection is carried out to realize automatic alarm on the risk of the epidemic. , and allows the server to predict the development of the epidemic according to the reported data, reducing human participation, thereby reducing the number of infected people and improving the efficiency of epidemic prevention and control.
  • the trajectory information further includes a location identifier
  • the method further includes: when it is determined according to the location identifier that the user and the diagnosed person are in the first When the space is confined, it is determined that the user is a close contact of the confirmed person.
  • the server after determining that the user is a close contact of the epidemic based on the trajectory information of the user and the confirmed patient, with the authorization of the user, physical sign detection is carried out to realize automatic alarm on the risk of the epidemic. , and allows the server to predict the development of the epidemic according to the reported data, reducing human participation, thereby reducing the number of infected people and improving the efficiency of epidemic prevention and control.
  • the location identifier includes at least one of the following: train number and/or compartment number, room identifier, or elevator identifier; the first enclosed space includes at least one of the following Type: train car, room, or elevator car.
  • the characteristic information of the infectious disease includes at least one of the following: the transmission route of the infectious disease virus, the transmission distance of the infectious disease virus, the infectious disease virus Incubation period of the disease, physiological signs associated with the infectious disease.
  • the physiological signs include at least one of the following: body temperature, heart rate, RRI during one heartbeat, electrocardiogram (ECG), blood oxygen saturation Spo2, and sleep characteristics.
  • the server after determining that the user is a close contact of the epidemic based on the trajectory information of the user and the confirmed patient, with the authorization of the user, physical sign detection is carried out to realize automatic alarm on the risk of the epidemic. , and allows the server to predict the development of the epidemic according to the reported data, reducing human participation, thereby reducing the number of infected people and improving the efficiency of epidemic prevention and control.
  • a method for epidemic prediction is provided, which is applied to a server.
  • the method mainly includes: the server sends trajectory information of a person diagnosed with an infectious disease and feature information of the infectious disease to an electronic device, wherein the trajectory information of the confirmed person includes: Location information and time information corresponding to the location information; after that, the server can receive the user's health risk score sent by the electronic device, and the user here can be a person who is self-confirmed on the electronic device side as a close contact of the confirmed person; Predict the epidemic risk of the first area according to the user's health risk score, the first area is the area where the user has stayed in a preset historical time period (such as within a week), and the epidemic risk in this area includes confirmed and suspected infectious diseases. total number of people at risk.
  • the epidemic prediction method after determining that the user is a close contact of the epidemic based on the trajectory information of the user and the confirmed patient, the user is monitored for physiological signs, so as to automatically alert the epidemic risk, and make the server Based on the reported data, it is possible to predict the development of regional epidemic trends, so that users can reasonably plan travel routes based on the predicted epidemic development trends and reduce the risk of infection.
  • This method can improve the efficiency of epidemic prevention and control while reducing human participation and the number of infected people.
  • the server may preset multiple risk levels, each risk level has a corresponding health risk score interval, and the server may report the user's health risk score according to the electronic device.
  • the health risk score interval to which the user belongs is determined, and the risk level corresponding to the user is determined, wherein each of the risk levels has a corresponding second preset weight; according to the number of newly-increased risk numbers corresponding to the multiple risk levels, multiple risk levels are determined.
  • the number of people at risk includes those who have been diagnosed and those who are suspected of being infected.
  • the diffusion coefficients of different risk levels are first calculated, and then the diffusion coefficients of each risk level and the second preset weights corresponding to each risk level are weighted and calculated to obtain the revised diffusion coefficient, which can be used to predict the number of new risk people. It is associated with the risk level to achieve a more accurate prediction of the epidemic risk.
  • the method further includes: determining the epidemic risk level of the first area according to the total number of people at risk; sending a first indication to the electronic device information, where the first indication information is used to indicate the epidemic risk level of the first area and/or the total number of people at risk in the first area.
  • the total risk population includes:
  • N r (t) is the total number of people at risk at time point t
  • rs sm is the average confirmation rate of the user confirming that he is a close contact through the electronic device
  • rs sp is the Corrected diffusion coefficient
  • N con is the current new risk person obtained by other means
  • N b is the new risk person determined according to the data sent by the electronic device.
  • an electronic device including: a receiving module configured to obtain trajectory information of a person diagnosed with an infectious disease and feature information of the infectious disease, where the trajectory information includes location information and time corresponding to the location information information; according to the trajectory information of the user and the trajectory information of the confirmed person, when it is detected that the user is a close contact of the confirmed person, the monitoring data of the physiological signs of the user is obtained; the processing module is used for according to The monitoring data and the characteristic information of the infectious disease determine the health risk score of the user; the sending module is used to report the health risk score to the server, and the health risk score is used to predict the epidemic risk in the first area , the first area is an area where the user has stayed in a preset historical time period, and the epidemic risk includes the total number of at-risk persons of the infectious disease confirmed persons and suspected persons.
  • the electronic device further includes a display module configured to display first information, where the first information is used to query the user whether he is the close contact person , the first information includes location information and/or time information of the close contact.
  • the display module is further configured to display second information, where the second information is used to request the user for physiological sign monitoring; the receiving module is further configured to Second confirmation information input by a user is received, and the second confirmation information user indicates that the user agrees to the electronic device to perform the physiological sign monitoring.
  • the display module is further configured to display third information, where the third information is used to request the user to report the monitoring data of the physiological sign; the receiving module is further configured to The third confirmation information is used to receive the third confirmation information input by the user, and the third confirmation information is used to indicate that the user agrees to report the data of the physiological sign monitoring.
  • the receiving module is further configured to receive first indication information sent by the server, where the first indication information is used to indicate an epidemic risk in the first area level and/or the total number of people at risk in the first area; the display module is further configured to display fourth information, where the fourth information is used to prompt the user of the epidemic risk level and/or of the first area or the total at-risk population of the first region.
  • the processing module is further configured to acquire at least one first physiological sign according to the infectious disease characteristic information, where the first physiological sign is related to the infectious disease obtain the monitoring data of the at least one first physiological sign of the user; weight the monitoring data of the at least one physiological sign according to at least one first preset weight to obtain the health risk score of the user, wherein, the at least one first preset weight is in a one-to-one correspondence with the at least one physiological sign.
  • the display module is further configured to display monitoring data of the first physiological sign corresponding to different time points; and/or, display the first physiological sign Monitor data trends over time.
  • the display module is further configured to display a map page, where the epidemic risk level of the first area is marked on the map page.
  • the processing module is further configured to determine the contact distance between the user and the confirmed person according to the user's trajectory information and the confirmed person's trajectory information; When the contact distance is less than the transmission distance, and the contact time between the user and the confirmed person is greater than a first threshold, it is determined that the user is a close contact of the confirmed person.
  • the processing module is further configured to, when it is determined according to the location identifier that the user and the confirmed person are in the first confined space at the same time, determine that the user is close contacts of the confirmed person.
  • the location identification includes at least one of the following: train number and/or compartment number, room identification or elevator identification; the first enclosed space includes at least one of the following Type: train car, room, or elevator car.
  • the transmission route of the infectious disease virus the transmission distance of the infectious disease virus, the incubation period of the infectious disease, and the physiological signs related to the infectious disease .
  • the physiological signs include at least one of the following: body temperature, heart rate, RRI during one heartbeat, blood oxygen saturation Spo2, and sleep characteristics.
  • a server comprising: a sending module for sending trajectory information of a person diagnosed with an infectious disease and feature information of the infectious disease to an electronic device, the trajectory information including location information and time information; a receiving module , for receiving the user health risk score sent by the electronic device, the user is a person who is confirmed to be a close contact of the confirmed person; a processing module, used for predicting the epidemic situation in the first area according to the health risk score Risk, the first area is an area where the user has stayed in a preset historical time period, and the epidemic risk includes the total number of at-risk persons of the infectious disease confirmed and suspected persons.
  • the processing module is further configured to determine the risk level corresponding to the user according to the health risk score interval to which the user's health risk score belongs, and each The risk level has a corresponding second preset weight; according to the number of newly-increased risk numbers corresponding to the multiple risk levels, the diffusion coefficients corresponding to the multiple risk levels are determined respectively; the diffusion coefficients of the multiple risk levels are divided The coefficient and the corresponding second preset weight are weighted to obtain a modified diffusion coefficient; according to the modified diffusion coefficient and the existing number of people at risk in the first area, the total number of people at risk in the first area is predicted.
  • the processing module is further configured to determine the epidemic risk level of the first area according to the total number of people at risk; the sending module is configured to send the electronic The device sends first indication information, where the first indication information is used to indicate the epidemic risk level of the first area and/or the total number of people at risk in the first area.
  • the processing module is further configured to calculate the total number of risk persons:
  • N r (t) is the total number of people at risk at time point t
  • rs sm is the average confirmation rate of the user confirming that he is a close contact through the electronic device
  • rs sp is the Corrected diffusion coefficient
  • N con is the current new risk person obtained by other means
  • N b is the new risk person determined according to the data sent by the electronic device.
  • an electronic device comprising a communication interface, a processor, a memory, and a computer program stored in the memory and executable on the processor, when the processor is executing the computer program At the time, the electronic device is made to implement the method for epidemic prediction according to any one of the implementation manners of the first aspect above.
  • a server comprising a communication interface, a processor, a memory, and a computer program stored in the memory and executable on the processor, when the processor executes the computer program , so that the server implements the method for epidemic prediction according to any implementation manner of the second aspect above.
  • a computer-readable storage medium comprising computer instructions, which, when the computer instructions are executed on a computer, cause the computer to execute the implementation of any one of the first aspect or the second aspect above.
  • a computer product is provided, characterized in that, when the computer product is run on a computer, the computer is caused to execute the epidemic prediction according to any implementation manner of the first aspect or the second aspect. method.
  • FIG. 1 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present application.
  • FIG. 2 is a schematic diagram of a system architecture for epidemic prediction provided by an embodiment of the present application.
  • FIG. 3 is a schematic diagram of a user graphical interface in an epidemic prediction process provided by an embodiment of the present application.
  • FIG. 4 is a schematic diagram of a user graphical interface in another epidemic prediction process provided by an embodiment of the present application.
  • FIG. 5 is a schematic diagram of displaying a monitoring result of a physiological sign of a user according to an embodiment of the present application.
  • FIG. 6 is a schematic diagram of another system architecture for epidemic prediction provided by an embodiment of the present application.
  • FIG. 7 is a schematic diagram of a graphical user interface in an epidemic prediction process provided by an embodiment of the present application.
  • FIG. 8 is a schematic diagram of an epidemic risk display provided by an embodiment of the present application.
  • FIG. 9 is a schematic flowchart of a method for epidemic prediction provided by an embodiment of the present application.
  • FIG. 10 is a schematic flowchart of another method for epidemic prediction provided by an embodiment of the present application.
  • FIG. 11 is a schematic diagram of distribution of persons at risk of an epidemic according to an embodiment of the present application.
  • FIG. 12 is a schematic diagram of a change trend of a predicted total number of people at risk according to an embodiment of the present application.
  • FIG. 13 is a schematic structural diagram of an electronic device provided by an embodiment of the present application.
  • FIG. 14 is a schematic structural diagram of a server provided by an embodiment of the present application.
  • first and second are only used for descriptive purposes, and should not be understood as indicating or implying relative importance and implicitly indicating the number of the indicated technical features.
  • a reference to a "first”, “second” feature may expressly or implicitly include one or more of that feature.
  • the current personnel tracking methods mainly include: (1) When personnel enter public places such as shopping malls and shopping centers, the venue requires scanning codes and reporting to the back-end server for personnel mobility tracking; (2) When personnel take public transportation, pass The ticket information is traceable to the mobile personnel. If an infectious person is found in a public place, the CDC, hospitals and other government agencies and social public institutions will conduct social investigations to analyze the close contacts of the epidemic based on the trajectory information of the confirmed patients and users; then observe all close contacts within the relevant time period Physiological characteristics of the epidemic, analyze the risk level of the epidemic in the region, and evaluate the impact of related risks.
  • the trajectory information is obtained based on the positioning information of the user's electronic device, such as GPS information of a mobile phone or a wearable device.
  • the positioning information is limited in accuracy and cannot reflect various complex scenarios that may appear in reality, a large judgment error will occur in practical applications.
  • this situation may in practice be: (1) The user and the confirmed patient are in the same building, but on different floors, For example, the diagnosed patient is located on a high floor, and the user only stays in the underground garage for a period of time; or, (2) when the user and the diagnosed patient are driving on the road, due to red lights and other reasons, they park at a similar location at the same time.
  • the risk of the user being infected is low, and if it is directly determined that the users in the similar situation are all patients, a large error will occur.
  • the current screening of infected patients is mainly done by manpower, and limited manpower cannot screen all suspected patients in a timely and effective manner, and it will also increase the risk of virus infection by testing personnel in the process.
  • the general public has limited information on the actions of confirmed patients, and cannot judge by themselves whether they have had close contact with confirmed patients; even if close contact can be confirmed, due to the lack of understanding of the characteristics of the new virus, they cannot accurately judge whether it is based on their own physical signs. Infection with the virus, determine the risk of disease. Therefore, it is necessary to provide a method that can facilitate users to inquire about their own risk of disease, so that users can actively understand their own risks and facilitate early response measures.
  • the embodiments of the present application provide a method for epidemic prediction, which can determine the user's risk through multi-dimensional information, which can accurately monitor the epidemic risk, and facilitate the user to query information such as their own infection risk and epidemic development trend, so that the Users can adjust their daily travel based on their own conditions and the development of the epidemic, and it is also convenient for relevant departments to take more targeted measures for epidemic prevention and control.
  • the methods for epidemic prediction provided in the embodiments of the present application can be applied to electronic devices such as mobile phones, tablet computers, wearable devices, and in-vehicle devices.
  • electronic devices such as mobile phones, tablet computers, wearable devices, and in-vehicle devices.
  • the embodiment of the present application does not limit the specific type of the electronic device.
  • FIG. 1 shows a schematic structural diagram of an electronic device provided by an embodiment of the present application.
  • the electronic device 100 may include a processor 110, an external memory interface 120, an internal memory 121, a universal serial bus (USB) 130, a charge management module 140, a power management module 141, a battery 142, an antenna 1, an antenna 2, Mobile communication module 150, wireless communication module 160, audio module 170, speaker 170A, receiver 170B, microphone 170C, headphone jack 170D, sensor module 180, buttons 190, motor 191, indicator 192, camera 193, display screen 194, and user Identity module (subscriber identification module, SIM) card interface 195 and so on.
  • SIM subscriber identification module
  • the sensor module 180 may include a pressure sensor 180A, a gyroscope sensor 180B, an air pressure sensor 180C, a magnetic sensor 180D, an acceleration sensor 180E, a distance sensor 180F, a proximity light sensor 180G, a fingerprint sensor 180H, a temperature sensor 180J, a touch sensor 180K, and an environmental sensor Light sensor 180L, bone conduction sensor 180M, etc.
  • the structures illustrated in the embodiments of the present application do not constitute a specific limitation on the electronic device 100 .
  • the electronic device 100 may include more or less components than shown, or combine some components, or separate some components, or arrange different components.
  • the illustrated components may be implemented in hardware, software, or a combination of software and hardware.
  • the processor 110 may include one or more processing units, for example, the processor 110 may include an application processor (application processor, AP), a modem processor, a graphics processor (graphics processing, GPU), an image signal processor ( image signal processor (ISP), audio processor/digital processor (the audio processor), controller, memory, video codec, audio codec, digital signal processor (DSP), baseband processor and/or neural-network processing unit (NPU), etc. Wherein, different processing units may be independent devices, or may be integrated in one or more processors.
  • application processor application processor, AP
  • modem processor graphics processor
  • ISP image signal processor
  • audio processor/digital processor the audio processor
  • controller memory
  • video codec audio codec
  • DSP digital signal processor
  • NPU neural-network processing unit
  • the controller may be the nerve center and command center of the electronic device 100 .
  • the controller can generate an operation control signal according to the instruction operation code and timing signal, and complete the control of fetching and executing instructions.
  • a memory may also be provided in the processor 110 for storing instructions and data.
  • the memory in processor 110 is cache memory. This memory may hold instructions or data that have just been used or recycled by the processor 110 . If the processor 110 needs to use the instruction or data again, it can be called directly from the memory. Repeated accesses are avoided, and the waiting events of the processor 110 are reduced, thereby improving the efficiency of the system.
  • firmware program firmware is stored in the memory, so that the controller or the processor can implement the audio processing method of the present application through an interface or a protocol.
  • the processor 110 may include one or more interfaces.
  • the interface may include an integrated circuit (inter-integrated circuit, I2C) interface, an integrated circuit built-in audio (inter-integrated circuit sound, I2S) interface, a pulse code modulation (pulse code modulation, PCM) interface, a universal asynchronous transceiver (universal asynchronous transmitter) receiver/transmitter, UART) interface, mobile industry processor interface (MIPI), general-purpose input/output (GPIO), user identification module interface, and/or universal serial bus interface, etc.
  • I2C integrated circuit
  • I2S integrated circuit built-in audio
  • PCM pulse code modulation
  • PCM pulse code modulation
  • UART universal asynchronous transceiver
  • MIPI mobile industry processor interface
  • GPIO general-purpose input/output
  • user identification module interface and/or universal serial bus interface, etc.
  • the I2C interface is a bidirectional synchronous serial bus that includes a serial data line (SDA) and a serial clock line (SCL).
  • the processor 110 may contain multiple sets of I2C buses.
  • the processor 110 can be respectively coupled to the touch sensor 180K, the microphone 170C, the camera 193 and the like through different I2C bus interfaces.
  • the processor 110 may be coupled to the touch sensor 180K through an I2C interface, and the processor 110 communicates with the touch sensor 180K through an I2C bus interface to implement the touch function of the electronic device 100 .
  • the I2S interface can be used for audio data transmission.
  • the processor 110 may contain multiple sets of I2S buses.
  • the processor 110 may be coupled with the audio module 170 through an I2S bus to implement communication between the processor 110 and the audio module 170 .
  • the audio module 170 may receive audio signals through an I2S interface to implement the function of recording audio.
  • the PCM interface can also be used for audio communications, sampling, quantizing and encoding analog signals.
  • the audio module 170 and the wireless communication module 160 may be coupled through a PCM bus interface.
  • the audio module 170 can also transmit audio signals to the wireless communication module 160 through the PCM interface, so as to realize the function of answering calls through the Bluetooth headset; Audio data collected by the microphone.
  • the UART interface is a universal serial data bus used for asynchronous communication.
  • the bus may be a bidirectional communication bus. It converts the data to be transmitted between serial communication and parallel communication.
  • a UART interface is typically used to connect the processor 110 with the wireless communication module 160 .
  • the processor 110 communicates with the Bluetooth module in the wireless communication module 160 through the UART interface to implement the Bluetooth function.
  • the audio module 170 can receive the audio signal transmitted by the Bluetooth module through the UART interface, so as to realize the function of recording audio through the wireless microphone in the Bluetooth headset.
  • the MIPI interface can be used to connect the processor 110 with peripheral devices such as the display screen 194 and the camera 193 .
  • MIPI interfaces include camera serial interface (CSI), display serial interface (DSI), etc.
  • the processor 110 communicates with the camera 193 through a CSI interface, so as to realize the photographing function of the electronic device 100 .
  • the processor 110 communicates with the display screen 194 through the DSI interface to implement the display function of the electronic device 100 .
  • the GPIO interface can be configured by software. GPIO can be configured as a control signal or as a data signal. In some embodiments, the GPIO interface may be used to connect the processor 110 with the camera 193, the display screen 194, the wireless communication module 160, the audio module 170, the sensor module 180, and the like.
  • the GPIO interface can also be configured as I2C interface, I2S interface, UART interface, MIPI interface, etc.
  • the USB interface 130 is an interface that conforms to the USB standard specification, and may specifically be a Mini USB interface, a Micro USB interface, a USB Type C interface, and the like.
  • the USB interface 130 can be used to connect a charger to charge the electronic device 100, and can also be used to transmit data between the electronic device 100 and peripheral devices. It can also be used to connect headphones to play audio through the headphones.
  • the interface can also be used to connect other electronic devices, such as AR devices.
  • the interface connection relationship between the modules illustrated in the embodiments of the present application is only a schematic illustration, and does not constitute a structural limitation of the electronic device 100 .
  • the electronic device 100 may also adopt different interface connection manners in the foregoing embodiments, or a combination of multiple interface connection manners.
  • Internal memory 121 may be used to store computer executable program code, which includes instructions.
  • the processor 110 executes various functional applications and data processing of the electronic device 100 by executing the instructions stored in the internal memory 121.
  • the internal memory 121 may include a storage program area and a storage data area.
  • the storage program area can store an operating system, an application program required for at least one function (such as an audio playback function, an image playback function, etc.), and the like.
  • the storage data area may store data (such as audio data, phone book, etc.) created during the use of the electronic device 100 and the like.
  • the internal memory 121 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, universal flash storage (UFS), and the like.
  • the power management module 141 is used for connecting the battery 142 , the charging management module 140 and the processor 110 .
  • the power management module 141 receives input from the battery 142 and/or the charging management module 140 and supplies power to the processor 110 , the internal memory 121 , the external memory, the display screen 194 , the camera 193 , and the wireless communication module 160 .
  • the power management module 141 can also be used to monitor parameters such as battery capacity, battery cycle times, battery health status (leakage, impedance).
  • the power management module 141 may also be provided in the processor 110 .
  • the power management module 141 and the charging management module 140 may also be provided in the same device.
  • Display screen 194 is used to display images, videos, and the like.
  • Display screen 194 includes a display panel.
  • the display panel can use liquid crystal display (LCD), organic light-emitting diode (OLED), active-matrix organic light-emitting diode (AMOLED), flexible light-emitting diode Diode (flex light-emitting diode, FLED), quantum dot light emitting diode (quantum dot light emitting diodes, QLED), etc.
  • LCD liquid crystal display
  • OLED organic light-emitting diode
  • AMOLED active-matrix organic light-emitting diode
  • FLED flexible light-emitting diode Diode
  • QLED quantum dot light emitting diode
  • the wireless communication function of the electronic device 100 may be implemented by the antenna 1, the antenna 2, the mobile communication module 150, the wireless communication module 160, the modulation and demodulation processor, the baseband processor, and the like.
  • the wireless communication module 160 may provide a wireless communication solution including 2G/3G/4G/5G etc. applied on the electronic device 100 .
  • the electronic device 100 may implement audio functions through an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, an earphone interface 170D, an application processor, and the like.
  • the keys 190 of the electronic device 100 may include a power-on key, a volume key, and the like.
  • the key 190 may be a mechanical key or a touch key.
  • Motor 191 can generate vibrating cues.
  • the motor 191 can be used for vibrating alerts for incoming calls, and can also be used for touch vibration feedback.
  • the indicator 192 can be an indicator light, which can be used to indicate the charging status, the change of power, and also can be used to indicate messages, missed calls, notifications, and the like.
  • the SIM card interface 195 is used to connect a SIM card.
  • the electronic device 100 also includes various sensors, such as a pressure sensor 180A, for sensing pressure signals, which can be converted into electrical signals.
  • the gyro sensor 180B may be used to determine the motion attitude of the electronic device 100 .
  • the air pressure sensor 180C is used to measure air pressure.
  • the magnetic sensor 180D includes a Hall sensor.
  • the acceleration sensor 180E can detect the magnitude of the acceleration of the electronic device 100 in one direction (generally three axes).
  • Distance sensor 180F for measuring distance.
  • the electronic device 100 can measure the distance through infrared or laser.
  • Proximity light sensor 180G may include, for example, light emitting diodes (LEDs) and light detectors, such as photodiodes.
  • the ambient light sensor 180L is used to sense ambient light brightness.
  • the electronic device 100 can adaptively adjust the brightness of the display screen 160 according to the perceived ambient light brightness.
  • the fingerprint sensor 180H is used to collect fingerprints.
  • the electronic device 100 can use the collected fingerprint characteristics to realize fingerprint unlocking, accessing application locks, taking pictures with fingerprints, answering incoming calls with fingerprints, and the like.
  • Touch sensor 180K also called "touch panel”.
  • the touch sensor 180K may be disposed on the display screen 194 , and the touch sensor 180K and the display screen 194 form a touch screen, also called a “touch screen”.
  • the touch sensor 180K is used to detect a touch operation on or near it.
  • the touch sensor 180K may pass the detected touch operation to the application processor to determine the type of touch event.
  • the embodiment of the present application further includes a temperature sensor 180J and a bone conduction sensor 180M.
  • the temperature sensor 180J is used to detect the temperature.
  • the temperature sensor 180J may be a non-contact infrared temperature sensor that can measure the temperature of an object using infrared rays. It should be understood that the types and numbers of infrared temperature sensors are not limited in the embodiments of the present application.
  • the temperature sensor 180J can receive the human body temperature signal to realize the temperature detection function.
  • the electronic device 100 uses the temperature detected by the temperature sensor 180J to execute a temperature processing strategy.
  • the bone conduction sensor 180M can acquire vibration signals.
  • the bone conduction sensor 180M can acquire the vibration signal of the vibrating bone mass of the human voice.
  • the bone conduction sensor 180M can also contact the pulse of the human body and receive the blood pressure beating signal.
  • the bone conduction sensor 180M can also be disposed in the earphone, combined with the bone conduction earphone.
  • the audio module can parse out the voice signal based on the vibration signal of the voice part vibrating bone mass obtained by the bone conduction sensor 180M, so as to realize the voice function.
  • the application processor may analyze the heart rate information based on the blood pressure beat signal obtained by the bone conduction sensor 180M, so as to realize the heart rate detection function and the sleep monitoring function.
  • the processor 110 of the electronic device 100 can also perform signal extraction, signal enhancement, and algorithm training by optimizing the hardware optical path and algorithm, integrating multiple light sources, and utilizing the characteristics of different reflection and absorption rates of oxyhemoglobin and deoxyhemoglobin to specific light. , abnormal suppression and other measures to measure the pulse oxygen saturation.
  • the method for epidemic prediction provided by the embodiments of the present application may be executed by a single device at the user end, for example, through a smart watch or smart bracelet at the user end; or may be executed by multiple devices (such as a mobile phone and a smart bracelet)
  • the method for epidemic prediction provided by the embodiment of the present application is performed by multi-device cooperation.
  • FIG. 2 shows a schematic diagram of the system architecture when the client is a single device.
  • the system architecture includes a server and electronic devices on the client side, and there may be multiple clients on the system architecture (eg, user 1, user 2, and user 3).
  • system maintenance personnel can obtain the track information of confirmed persons (hereinafter referred to as track information) and virus feature information of infectious diseases (hereinafter referred to as feature information) published by government agencies such as CDCs, hospitals, etc.
  • track information confirmed persons
  • feature information virus feature information of infectious diseases
  • the acquired trajectory information is converted into geographic information required by the system (the GPS information is taken as an example below) and the corresponding time information is input to the server.
  • the server After the server receives the feature information and trajectory information, it stores the information in the regional sample database.
  • the system maintenance personnel may also input additional information in the trajectory information, such as train number, carriage number, house number, and the like.
  • the system maintainer can add the trajectory information of a patient diagnosed with a virus and the characteristic information of the virus according to the latest published epidemic information, or perform the tracking information of the confirmed patient or the characteristic information of the virus already stored in the database. renew.
  • the server can receive and store the characteristic information of the new type of virus and the trajectory information of the confirmed person corresponding to the virus; or, when the characteristic information of a certain virus is updated, the server can receive and update the information.
  • the characteristic information of the virus or, when it is found that a virus has a newly diagnosed person, the server receives the trajectory information of the new person and adds it to the trajectory information of the confirmed person corresponding to the virus.
  • the server may send the updated trajectory information and virus feature information to an electronic device on the client side, such as a smart watch.
  • the electronic device may store the acquired trajectory information and virus characteristic information in the internal memory 121 .
  • FIG. 3 shows a schematic diagram of a graphical user interface (graphical user interface, GUI) in an epidemic prediction process provided by an embodiment of the present application.
  • GUI graphical user interface
  • the user can click on the "View XX infectious disease confirmed personnel's action route" option on the main interface of the smart watch, and the main interface can also include Bluetooth icons, battery information and time information, etc.;
  • the smart watch can display a search interface for the movement trajectory of the diagnosed person as shown in (b) in Figure 3, which includes: a search box for infectious disease types, a search box for location/region, and a search box for time etc., the user can enter the corresponding content in the search box, and then click the search icon; alternatively, the user can also click the drop-down box control, and the electronic device can respond to the user's click operation, and can display as shown in (c) in Figure 3 option, when the user clicks the drop-down control corresponding to the disease type search box, the S infectious disease, X infectious disease, and Y infectious disease can be displayed in the drop-down list.
  • the user can also drag the slider on the right side of the drop-down option area to query more The type of infectious disease in XX; the user enters or selects the type of infectious disease, location/area, and date, such as the user enters S infectious disease, XX city, XX district, after June 18, 2020, as shown in (d) in Figure 3 , the user clicks the search icon, indicating that the user inquires about the trajectory of the confirmed infectious disease patients in XX District, XX City on June 18, 2020; the user's search operation is detected, and the smart watch can display as shown in (e) in Figure 3 The map page displayed is marked with the trajectory and route of the confirmed S infectious disease person in the area and time period queried by the user.
  • the specific steps for the user to query the action route of the diagnosed person may also include other various steps, which are not limited to the steps listed above, which are not limited in the present application.
  • the smart watch after receiving the track information and feature information, determines whether the user is a close contact of the confirmed person based on the user's historical track information stored locally, and reminds the user of the risk of close contact. For example, when it is detected that the user has close contact with the confirmed person, as shown in (a) in Figure 4, the smart watch interface can display risk prompt information, such as "You start at 2020-06-18, 13:00.
  • the smart watch interface can display the prompt information of physiological signs monitoring, such as "whether to agree to monitor the physiological signs related to S infectious disease"; when it is detected that the user clicks the "confirm” icon, it means that the user agrees to the electronic device to monitor the physiological signs. , the smart watch can turn on the physiological sign monitoring function.
  • the physiological signs monitored by the smart watch include physiological signs related to the S infectious disease. For example, after the virus infection of the S infectious disease, the body temperature of the infected person will rise and the blood oxygen will drop. Physiological signs can be body temperature and blood oxygen saturation; or, for example, after viral infection of S infectious disease, the heart rate, body temperature, and blood oxygen saturation of the infected person will change, then the monitored physiological signs can include heart rate, Body temperature, blood oxygen saturation.
  • the detected physiological signs may also include other various types, which are not limited here.
  • the electronic device monitors the physiological signs of the user; after that, as shown in (c) of FIG. 4 , the smart watch can further display the physiological signs of the user
  • the prompt information of the information report such as "Do you agree to report your physiological sign data for risk analysis”; when it is detected that the user clicks the "Confirm” operation, it means that the user agrees to the smart watch to report the monitoring data of his physiological signs to the server, Then, the smart watch can report the measured physiological sign data of the user to the server.
  • the smart watch can also calculate the user's health risk score based on certain criteria according to the acquired physiological sign monitoring data, where the health risk score is used to indicate the probability of the user contracting an infectious disease.
  • the smart watch can continuously monitor changes in the user's physiological sign data for multiple consecutive days, and then draw a change trend graph of the health risk score and/or a change trend graph of the physiological sign monitoring results.
  • the smart watch can alert the user of health risks based on the monitoring results of various physiological signs and/or health risk scores, as shown in (d) in Figure 4, when the monitoring results of the user's physiological signs indicate that the user's physiological signs meet the
  • the smart watch interface can display, for example, "It is detected that you are a high-risk group of infectious diseases, please seek medical treatment in time”.
  • the smart watch can further display prompt information reported by the user's health risk score, such as " Whether you agree to report your health risk score for risk analysis”; when it is detected that the user clicks the “Confirm” icon, it means that the user agrees to the smart watch to report its health risk score, and the smart watch will report the user’s health risk score to the server. .
  • the electronic device may periodically detect whether the user is a close contact of a confirmed person and report user data (physiological sign measurement result or health risk score). For example, the electronic device detects whether the user is a close contact based on the updated trajectory information of the confirmed person every 30 minutes; every 1 hour, it reports the user's physiological sign monitoring data, etc. Wherein, the period for detecting whether the user is a close contact by the electronic device may be the same as or different from the period for reporting user data, which is not limited here.
  • the detection process of the user's physiological signs by the electronic device can be carried out in real time and continuously.
  • the electronic device turns on the physiological sign.
  • the sign detection function can continuously monitor the user's physiological signs in the background to obtain accurate sign data of the user at different times.
  • the server predicts the development trend of the regional epidemic situation based on a certain calculation model, such as predicting the total number of risk personnel in certain regions.
  • the server may, according to the predicted epidemic development trend, update the epidemic situation of certain areas where the user stayed in the preset historical time period, and send the risk level of these areas to the user's electronic device.
  • the user can query the monitoring results of various physiological signs on the monitoring result query interface of the smart watch, and each physiological sign includes, for example: heart rate, R-wave interval (R-R interval, RRI) heart rate, blood oxygen, sleep characteristics, electrocardiogram (ECG), etc.
  • R-R interval RRI
  • ECG electrocardiogram
  • the smart watch can display the monitoring results of the corresponding physiological signs. For example, as shown in (f) in Figure 4, the user clicks on the heart rate option, and the smart watch responds to the user's click operation and displays (g) in Figure 4, presenting the monitoring results and status (heart rate) of the heart rate to the user. , 65, normal state).
  • the monitoring result query interface may include query options.
  • the smart watch can simultaneously display multiple detected items. Results of physiological signs (similar to that shown in (a) in Figure 5). This application does not limit this.
  • FIG. 5 shows a schematic diagram of a display interface of a physiological sign measurement result provided by an embodiment of the present application.
  • the smart watch when it detects the user's operation of inputting a physical sign monitoring result query, it can also display the interface shown in (a) in FIG. 5 , which can be a physiological sign monitoring result display interface, including multiple Physiological sign measurement results and the changing trend of physiological signs data.
  • the physiological signs are, for example, blood oxygen, heart rate, and sleep characteristics.
  • the change trend graph of this interface is used to indicate the change trend of blood oxygen (as shown in the uppermost curve in (a) of Figure 5) and the change trend of heart rate (as shown in the lowermost curve of (a) in Figure 5) ) and sleep features (as shown by the dotted filled area in Fig. 5(a)). It can be seen from (a) in Figure 5 that at 01:15, the user's blood oxygen is 98%, the heart rate is 65, and the user is in an awake state at this time.
  • the smart watch may also display the user's health risk score.
  • the smart watch displays the health risk score of the user calculated according to certain criteria.
  • the display interface includes health risk scores corresponding to different dates.
  • the smart watch can also mark the status corresponding to the health risk score corresponding to different dates on the calendar page, and display it to the user.
  • the user's risk score on a certain date is in the preset normal state score range
  • the lower part of the date is marked as normal, indicating that the user's health is in a normal state
  • the user's health risk score on a certain date is in the preset normal state score range
  • the risk status (such as low risk, medium risk, high risk, etc.) is in the score range
  • the corresponding risk status (such as low risk, medium risk, high risk, etc.) is marked below the date, indicating that the user’s current health has health risks.
  • the calendar interface can also display the risk level (60% as shown in (c) in Figure 5); it can also display a suggestion option in the risk state, and the user can click on the suggestion option to obtain appropriate health advice.
  • the smart watch can integrate the monitoring data of the user's physiological signs to analyze the user's health risk score.
  • the method for epidemic prediction provided by the embodiments of the present application may also be implemented through the system architecture shown in FIG. 6 .
  • multiple electronic devices at the user end may be a combination, and the electronic devices in the combination have different divisions of labor.
  • the combination of electronic devices including a mobile phone and a smart watch as an example, the mobile phone and the smart watch can establish a wireless connection, such as a Bluetooth connection, and the mobile phone and the smart watch can work together.
  • the division of labor of each electronic device in the electronic device combination shown in FIG. 6 may include but is not limited to the following situations:
  • Scenario 1 The mobile phone uses its communication function and computing power to interact with the server and the user, and analyzes whether the user is a close contact with the epidemic, as well as the user's health risk score; while the smartwatch mainly uses physiological signs
  • the monitoring function is used to detect the physiological signs of the user under the instruction of the mobile phone, and send the detected data to the mobile phone for the mobile phone to calculate the health risk score, or for the user to view.
  • Scenario 2 The smart watch is used to monitor the user's physiological sign data, process the physiological sign data, and interact with the server and the user; while the mobile phone uses its display function to receive the physiological sign monitoring results of the smart watch and display various items to the user. Results of physiological signs, health risk scores, reminder messages, etc.
  • the server can send the trajectory information of the confirmed person and the characteristic information of the infectious disease to the mobile phone, and the mobile phone can determine whether the user is a close contact of the confirmed person based on the stored historical trajectory information of the user; when it is determined that the user is a close contact
  • the mobile phone can prompt the user that there is a risk of close contact; if the mobile phone obtains the user's confirmation of the close contact operation and the user authorizes the monitoring of physiological signs, the mobile phone can instruct the smart watch worn by the user to monitor the physiological signs;
  • the smart watch turns on the physiological sign monitoring function, and sends the obtained physical sign monitoring results to the mobile phone, and the mobile phone calculates the health risk score and reports the relevant data.
  • FIG. 7 shows a schematic diagram of a graphical user interface in an epidemic prediction process provided by an embodiment of the present application.
  • a mobile phone and a smart watch is still used as an example for description.
  • the screen display interface of the mobile phone displays the current interface content 701
  • the interface content 701 may be the main interface of the mobile phone.
  • the interface content 701 displays a variety of applications (application, App), such as clock, calendar, gallery, memo, file management, email, music, calculator, Huawei video, weather, browser, smart life, settings, voice recorder , an app store, and apps for camera, contacts, phone, messaging, and fitness. It should be understood that the interface content 701 may further include other more application programs, which is not limited in this embodiment of the present application.
  • the health interface 702 may include a plurality of display sub-areas, including a step counting display sub-area 10, a vital sign data query sub-area 20, and an epidemic risk query sub-area 30 and the like.
  • the step count display sub-area 10 may include data such as the number of steps of the day, the distance walked, and the calories consumed by the user;
  • the vital sign data query sub-area 20 may include a number of physiological sign measurement results query options, including heart rate, blood oxygen saturation, etc.
  • it also includes healthy life options, which are used to enable users to query information such as health advice.
  • the mobile phone When the mobile phone detects that the user clicks the epidemic risk query icon, the mobile phone can display the interface as shown in (c) in Figure 7, which is the query interface for the trajectory information of the diagnosed person and the infectious disease characteristic information, including the movement trajectory query of the confirmed person icon, the infectious disease characteristic information query icon.
  • the mobile phone can display the interface shown in (d) in Figure 7, including the type of infectious disease, In the input area of location/area and time (area 703), the user can input the name of the infectious disease, as well as the location and time of the query; Select the option you want to view.
  • the mobile phone When the mobile phone detects the query information entered by the user, for example, the user enters or selects S infectious disease in the infectious disease type search box, enters or selects XX district in XX city in the location/region search box, and enters or selects 2020-6 in the time search box After -18, click the search icon (704); in response to the search operation input by the user, as shown in (e) of Figure 7, the mobile phone can display the S infectious disease confirmed person 2020-6-18 queried by the user in a certain
  • the movement track of XX District of XX City such as the mobile phone interface, can display a map page, and the movement path of the diagnosed person, as well as the information of the stop place and the corresponding stay time are marked on the map page.
  • the mobile phone when the mobile phone detects that the user clicks to query the characteristic information of infectious diseases on the interface as shown in (c) of FIG. 7 , the mobile phone can display the characteristic information of various infectious diseases, including: incubation period, Transmission distance, disease symptoms, etc.
  • a prompt message is displayed, for example, prompting the user "at XX time, XX place is close to the confirmed person If you have been in contact for X hours, there is a risk of close contact”; the user judges whether the close contact has actually occurred based on the historical path he has passed, and excludes the misjudgment of close contact only because of the geographical proximity. If there is close contact, you can Click "Confirm”, otherwise, click "Cancel”.
  • the prompt information can prompt the user to recall whether he was close to the confirmed person at the indicated time and place. Contact, improve the accuracy of close contact judgment.
  • the mobile phone when the user clicks "Confirm”, it indicates that the user confirms that there is close contact, and there may be a greater risk of infection.
  • the mobile phone detects that the user clicks the "Confirm” icon, it means that the user confirms that there has been close contact with the confirmed person, and in response to the confirmation operation, the mobile phone can display the prompt information of physiological sign monitoring to the user, such as "Do you agree to your When it is detected that the user clicks "confirm", the mobile phone can instruct the wearable device connected to it to monitor the physiological signs of the user.
  • the smart watch After receiving the instructions of the mobile phone, the smart watch monitors the physiological signs of the user. Specifically, the smart watch can send the monitoring data to the mobile phone during the monitoring process; or, after the monitoring is completed, the smart watch can send the monitoring data to the mobile phone.
  • the mobile phone can also display prompt information, such as prompting the user "whether to agree to report your physiological sign information for risk analysis"; when it is detected that the user clicks "confirm” , indicating that the user agrees to the mobile phone to report the monitoring data of its physiological signs to the server, then the mobile phone can report the physiological signs data measured by itself to the server.
  • prompt information such as prompting the user "whether to agree to report your physiological sign information for risk analysis”; when it is detected that the user clicks "confirm” , indicating that the user agrees to the mobile phone to report the monitoring data of its physiological signs to the server, then the mobile phone can report the physiological signs data measured by itself to the server.
  • the mobile phone may further calculate the user's health risk score based on certain criteria according to the acquired sign information, where the health risk score is used to indicate the probability that the user is infected with a virus.
  • the smart watch can provide health risk reminders to users, such as displaying a reminder message that "you are detected as a high-risk group of S infectious diseases, please seek medical attention in time".
  • the mobile phone may further display prompt information for reporting the user's health risk score, such as "Do you agree to report your health risk score for risk analysis?" ;
  • prompt information for reporting the user's health risk score such as "Do you agree to report your health risk score for risk analysis?" ;
  • the user clicks the "Confirm” operation it means that the user agrees to the mobile phone to report its health risk score to the server, and the mobile phone can report the user's health risk score to the server.
  • the user can query the monitoring results of various physiological signs on the detection and query interface of the mobile phone, and each physiological sign includes, for example, heart rate, RRI heart rate, blood oxygen, sleep characteristics, ECG, and the like.
  • each physiological sign includes, for example, heart rate, RRI heart rate, blood oxygen, sleep characteristics, ECG, and the like.
  • the mobile phone can display the monitoring results of the corresponding physiological signs.
  • the mobile phone can simultaneously display the monitoring results of multiple monitored physiological signs.
  • FIG. 5 For a schematic diagram of an interface for displaying the monitoring results of the physiological signs displayed by the mobile phone, see FIG. 5 , which will not be repeated here.
  • the electronic device for reporting user data may also receive data sent by multiple devices. For example, in a family scenario, if the smart watches of multiple family members are connected to one electronic device , multiple devices can send the separately measured physical data of different users to the electronic device, the electronic device calculates the health risk scores of different users, and reports the health risk scores, so that multiple health risk scores can be reported.
  • the server may predict the development trend of the epidemic in the area reported by the user based on the reported data of the user's electronic device, including the total number of people at risk in the area, the epidemic risk level, and the like.
  • the server sends the generated information to the electronic device, and the electronic device can further display the total number of people at risk and/or the epidemic risk level in the area to the user.
  • FIG. 8 it is a schematic diagram of an example of a risk map provided in this embodiment of the present application.
  • the electronic device can mark the epidemic risk level of different regions on the map page based on the obtained epidemic risk level of each region, such as "XX high-risk area of infectious disease epidemic” and "XX infectious disease epidemic medium-risk area” for users. Viewing, it is convenient for users to plan travel routes and avoid areas with high epidemic risk levels.
  • FIG. 9 shows an epidemic prediction method provided by an embodiment of the present application. Can be applied to electronic equipment. The method includes the following steps:
  • S901 Acquire trajectory information of a person diagnosed with an infectious disease and feature information of the infectious disease, where the trajectory information includes location information and time information corresponding to the location information.
  • the electronic device can obtain the track information of the diagnosed person from the server, and the track information includes location information and time information, such as the position corresponding to the diagnosed person at a certain moment.
  • the electronic device may also obtain characteristic information of the infectious disease from the server, and the characteristic information may include the transmission route, transmission distance, incubation period, and physiological signs related to the infectious disease, etc. of the infectious disease virus.
  • physiological signs related to infectious diseases mentioned in this application may refer to the physiological signs that are affected when a user is infected with an infectious disease virus. If blood oxygen drops, the physiological signs related to the infectious disease can be body temperature and blood oxygen saturation; or, after viral infection of some infectious diseases, the heart rate, body temperature, and blood oxygen saturation of the infected person will change.
  • the physiological signs related to the infectious disease may be heart rate, body temperature, and blood oxygen saturation.
  • the trajectory information of the diagnosed person and the historical trajectory information of the user may both be GPS information.
  • the user's trajectory information may be the user's trajectory information within a preset historical time period, for example, the trajectory information within a week.
  • the electronic device may obtain the contact distance between the user and the confirmed person according to the location information and time information in the historical track information of the user and the location information and time information of the confirmed person, where the contact distance here may be Refers to the distance between the user's location and the location of the confirmed person at the same time.
  • the contact distance between the user and the confirmed person is less than the transmission distance of the infectious disease virus (that is, close contact)
  • the risk of the user being infected with the virus is greater
  • the time of close contact between the user and the confirmed person can be further judged; when the user and the confirmed person are in close contact
  • the duration of close contact of the confirmed person is greater than the first threshold, it is determined that the user is a close contact of the confirmed person.
  • the electronic device can obtain the trajectory information of the diagnosed person based on step S901, and determine whether the user's historical trajectory information stored on the electronic device appears in the preset interval of the confirmed person's route, and the time in the preset interval is greater than the first threshold. , if so, the user is considered to be a close contact of the confirmed person.
  • the user has only a very brief (less than the first threshold) close contact with the confirmed person, the risk of the user being infected is low, and the user is not regarded as a close contact of the confirmed person at this time;
  • the duration of the close contact is greater than or equal to the first threshold, the user is considered to be a close contact of the confirmed person, and physical signs monitoring and data reporting will be carried out later.
  • the electronic device can also score the close contact risk according to the contact distance between the user and the confirmed person.
  • the calculation formula of the close contact risk score is shown in formula (1-1):
  • ds is the close contact risk score
  • d is the contact distance between the user and the confirmed person
  • dmax is the maximum transmission distance of the infectious virus.
  • the electronic device determines, based on the additional information in the trajectory information of the confirmed person, that the user and the confirmed person used to be in the same confined space, for example, the same confined space as a train car, room, elevator car, etc., it may not be Then consider the length of time that they are in the same confined space, and directly determine that the user is a close contact of the confirmed person.
  • the electronic device may display first information (the close contact risk prompt information shown in (a) of FIG. 4 ), the first information The information is used to inquire whether the user is a close contact of the confirmed person, and the first information includes location information and/or time information of the close contact between the user and the confirmed person.
  • the risk level of the close contact may be determined according to ds, and the risk level of the close contact may be prompted to the user.
  • the electronic device receives the first confirmation information input by the user (as shown in (a) of FIG. 4 , the user clicks the confirmation option), and the first confirmation information may be used to indicate that the user is a close contact person.
  • the electronic device may display second information (such as the physiological sign monitoring prompt information shown in (b) of FIG. 4 ), where the second information is used to request the user to perform physiological sign monitoring.
  • the electronic device receives the second confirmation information input by the user (the user clicks the confirmation option as shown in (b) in FIG. 4 )
  • the user's physiological sign monitoring can be started, and the second confirmation information can be used to indicate that the user agrees Electronic devices monitor physiological signs.
  • the electronic device when the electronic device itself supports the function of monitoring physiological signs, the electronic device can monitor the physiological signs of the user; The user performs physiological sign monitoring.
  • S903 obtain the health risk score of the user according to the monitoring data and the characteristic information of the infectious disease.
  • the electronic device may acquire weights corresponding to different physiological signs, and the weights may be preset weights according to a characteristic model of an infectious disease.
  • the electronic device may acquire at least one first physiological sign according to the feature information of the infectious disease, where the first physiological sign is a feature associated with the infectious disease; after that, the electronic device may acquire at least one first physiological sign of the user for the at least one first physiological sign. Monitoring the physical sign information, and obtaining the monitoring data of the first physiological sign; then, the electronic device can perform weighted calculation on the monitoring data of the at least one first physiological sign according to the preset weight corresponding to the at least one first physiological sign, and obtain The user's health risk score.
  • the calculation formula of the health score can be formula (1-2):
  • S health is a health risk score
  • hr weight is a preset weight corresponding to heart rate
  • RRI weight is a preset weight corresponding to heart rate
  • T weight is a preset weight corresponding to body temperature.
  • the change value of each physiological sign may be a change value between the monitored physiological sign monitoring data and the preset normal data of the physiological sign.
  • the weight of the physiological sign that is more related to the infectious disease can be set to be larger, and the weight of the physiological sign that is less related to the infectious disease can be set to be smaller. This application does not limit this.
  • the electronic device may display the first prompt information to the user according to the user's health score to prompt the user that there is a health risk. For example, if the electronic device determines that the user's health score is not within the normal range, the electronic device may display risk prompt information as shown in (d) of FIG. 4 .
  • the electronic device may also display third information to the user (as shown in (e) in FIG. 4 ), and request the user to report the user's health risk score;
  • the electronic device receives the third confirmation information input by the user (the user clicks the confirmation option as shown in (e) in Figure 4), that is, when the user agrees to report his health risk score, the electronic device can report the user's health risk score to the server. .
  • the electronic device may display the first physiological sign information of the user at different time points; and/or, display the changing trend of the first physiological sign information over time (as shown in FIG. 5( a) shown in the figure).
  • the electronic device may display the health risk scores of the user at different time points (as shown in (b) of FIG. 5 ); or, mark the health risks corresponding to different dates on the calendar interface level (as shown in (c) in Figure 5).
  • S904 report a health risk score to the server, where the health risk score is used to predict the epidemic risk in the first area, where the first area is the area where the user stayed in the preset historical time period, and the epidemic risk includes infectious disease confirmed personnel and suspected personnel total number of people at risk.
  • the electronic device can report the health risk score to the server; the server can predict the health risk score according to the health risk score Outbreak risk in the first region.
  • the first area may be an area where the user has stayed within a preset historical time, and the preset historical time may be flexibly set in advance, such as a week, etc., which is not limited in this embodiment of the present application.
  • the area where the user stays in the embodiment of the present application may refer to the area where the user stays longer than a second threshold, wherein the second threshold can be flexibly set according to actual conditions such as the transmission ability of infectious diseases and viruses, which is not done here. limited.
  • the server may send the predicted epidemic risk of the first area to the electronic device, and the electronic device may prompt the user of the epidemic risk level of the first area.
  • the electronic device may display on the map page of the electronic device that the first area is an epidemic risk area (as shown in FIG. 8 ), and the map page may be marked with the epidemic risk level of the first area.
  • the server after determining that the user is a close contact of the epidemic based on the trajectory information of the user and the confirmed patient, with the authorization of the user, physical sign detection is carried out to realize automatic alarm on the risk of the epidemic. , and allows the server to predict the development of the epidemic according to the reported data, reducing human participation, thereby reducing the number of infected people and improving the efficiency of epidemic prevention and control.
  • the server can use the risk analysis model of the infected population to predict the development trend of the epidemic situation in the first area, such as the prediction of the total number of people at risk (including the number of confirmed and suspected people), and based on the predicted total number of people at risk Assess the risk level of the area.
  • the server can combine historical risk populations, newly diagnosed populations, and risk populations reported for data analysis into seed risks; use the growth rate of the number of confirmed and suspected individuals (increased risk populations) as a diffusion coefficient to predict the total risk number of people.
  • the calibration factor for the diffusion coefficient and the total number of people at risk can be calibrated with the user's confirmation rate.
  • FIG. 10 shows a schematic flowchart of epidemic risk prediction on the server side provided by an embodiment of the present application.
  • the process shown in FIG. 10 may be executed by the server, and may specifically include the following steps:
  • the first area may be an area where the user has stayed within a preset historical time period.
  • the diffusion coefficient of the infectious disease in the first region refers to the growth rate of the number of people at risk in that region. Among them, the number of people who are at increased risk is the number of users who have confirmed close contact with confirmed people through electronic devices.
  • the growth rate of the risk population is directly used as a diffusion coefficient to predict the possible total risk population in the future.
  • the user is divided into risk levels by reporting the health risk score of the user, and the diffusion coefficient (growth rate) of each risk level is determined. Corrected to obtain the corrected total diffusion coefficient associated with the epidemic level.
  • X3 is a confirmed person
  • X1, X2, X4 - X6 are close contacts of X3 , specifically, the close contact parameters of X1 and X3 (including the contact distance
  • the contact time) is X (1, 3)
  • the close contact parameter of X 2 and X 3 is X (2, 3)
  • the close contact parameter of X 4 and X 3 is X (4, 3)
  • X 5 The close contact parameter with X 3 is X (3, 5)
  • the close contact parameter between X 6 and X 3 is X (3, 6)
  • different people have different health risk scores, such as X 1 to X 6
  • the health risk scores of are corresponding to h 1 to h 6 .
  • the server calculates the diffusion coefficient according to the close contacts, it needs to combine the risk levels corresponding to the health risk scores of different close contacts (such as h 1 to h 6 ) to calculate the diffusion coefficient of each risk level and the weight of the risk level. Perform weighted calculations to obtain a more accurate diffusion coefficient, and then more accurately predict the total number of people at risk of future epidemics.
  • the server determines the risk level corresponding to the user according to the score range to which the health risk score belongs, for example, when the user's health risk score belongs to the score range corresponding to the high risk level , it is determined that the user belongs to the high risk level; when the user's health risk score belongs to the score range corresponding to the medium risk level, it is determined that the user belongs to the medium risk level; when the user's health risk score belongs to the score or score range corresponding to the low risk level , it is determined that the user is at low risk; when the user's health risk score belongs to the score or score range corresponding to the risk-free level, it is determined that the user is at no risk.
  • the server may preset weights corresponding to different risk levels. For example, as shown in Table 1, the weight corresponding to the high risk level is 100%, the weight corresponding to the medium risk level is 50%, and the weight corresponding to the low risk level is 100%. The weight is 20%, and the weight corresponding to the risk-free level is 0.
  • r high risk is the diffusion coefficient corresponding to high risk level
  • r medium risk is the diffusion coefficient corresponding to medium risk level
  • r low risk is the diffusion coefficient corresponding to low risk level
  • r no risk is the diffusion coefficient corresponding to no risk level.
  • the diffusion coefficient of each risk level can be calculated according to the new number of people at the risk level and the existing number of risk people at the risk level.
  • the server uses the risk analysis model of the infected population to predict the total number of people at risk of the epidemic in the first region.
  • the total number of people at risk in the first area can be calculated based on the confirmed people and risk groups and the revised diffusion coefficient. Among them, the formula for calculating the total number of people at risk is shown in (1-4).
  • the total number of people at risk Nr(t) in the first area is composed of multiple personnel, including the current number of new risks Ncon(t) obtained by other means, and the new risks of electronic equipment risk analysis.
  • other methods in the current number of newly-increased risk persons obtained by other methods refer to other methods other than the method of reporting the health risk score through an electronic device.
  • the server can predict the number of new at-risk persons in the first area according to the diffusion coefficient, and draw a trend graph of the total number of at-risk persons (as shown in Figure 12).
  • the server may send the predicted total number of people at risk to the electronic device, and the electronic device may display it to the user to prompt the development trend of the epidemic.
  • the server can also send the change trend graph of the total number of people at risk to the electronic device, and the electronic device can display it to the user, so that the user can obtain the development trend of the epidemic more intuitively.
  • S1003 Determine the epidemic risk level of the first area according to the predicted total number of people at risk.
  • the server may determine the epidemic risk level of the first area according to the predicted total number of people at risk. For example, when the total number of people at risk is less than or equal to 10, the epidemic risk level of the corresponding first area is low risk; when the total number of people at risk is greater than 10 and less than or equal to 100, the corresponding epidemic risk level of the first area is medium Risk level; when the total number of people at risk is greater than 100, the corresponding epidemic risk level of the first area is a high risk level.
  • the server can send the epidemic risk level to the electronic device; the electronic device can mark its risk level in the first area of the map page according to the epidemic risk level (as shown in FIG. 8 ), so that the user can more intuitively Get the epidemic situation in different regions.
  • the server after determining that the user is a close contact of the epidemic based on the trajectory information of the user and the confirmed patient, with the authorization of the user, physical sign detection is carried out to realize automatic alarm on the risk of the epidemic. , and allows the server to predict the development of the epidemic according to the reported data, reducing human participation, thereby reducing the number of infected people and improving the efficiency of epidemic prevention and control.
  • FIG. 13 it is a schematic structural diagram of an electronic device provided in an embodiment of the present application.
  • the electronic device 1300 includes a receiving module 1301 , a monitoring module 1302 , a processing module 1303 and a sending module 1304 .
  • the receiving module 1301 can be used to obtain the trajectory information of the person diagnosed with the infectious disease and the characteristic information of the infectious disease, where the trajectory information includes location information and time information.
  • the monitoring module 1302 can be used to monitor the physiological signs of the user when it is detected that the user is a close contact of the confirmed person according to the trajectory information of the user and the trajectory information of the confirmed person, and obtain all the information. monitoring data of the above-mentioned physiological signs.
  • the processing module 1303 may be configured to obtain the health risk score of the user according to the monitoring data and the characteristic information of the infectious disease.
  • the sending module 1304 can be used to report the health risk score to the server, and the health risk score is used for the server to predict the epidemic risk of the first area, where the first area is where the user stays in a preset historical time period
  • the epidemic risk includes the total number of at-risk persons of the infectious disease confirmed and suspected persons.
  • the electronic device 1300 may further include a display module, which may be configured to display first information, where the first information is used to query the user whether it is the close contact person, and the first information includes the Location and/or time information of close encounters.
  • a display module which may be configured to display first information, where the first information is used to query the user whether it is the close contact person, and the first information includes the Location and/or time information of close encounters.
  • the receiving module 1301 may also be configured to receive first confirmation information input by the user, where the first confirmation information is used to indicate that the user is the close contact person.
  • the display module may be further configured to display second information, where the second information is used to request the user to perform physiological sign monitoring.
  • the receiving module 1301 may also be configured to receive second confirmation information input by a user, where the second confirmation information user indicates that the user agrees to the electronic device to monitor the physiological signs.
  • the display module may be further configured to display first prompt information according to the health risk score, where the first prompt information is used to indicate to the user that there is a health risk.
  • the display module may also be configured to display third information, where the third information is used to request the user to report the data of the monitoring of physiological signs.
  • the receiving module 1301 may also be configured to receive third confirmation information input by the user, where the third confirmation information is used to indicate that the user agrees to report the data of physiological sign monitoring.
  • the display module may be further configured to display fourth information, where the fourth information is used to prompt the user of the epidemic risk level and/or the total number of persons at risk in the first area.
  • the processing module may be further configured to acquire at least one first physiological sign according to the infectious disease characteristic information, where the first physiological sign is a characteristic related to an infectious disease; acquire the at least one first physiological sign of the user Monitoring data of physical sign information; weight the monitoring data according to the preset weight, and calculate the health risk score of the user.
  • the display module may also be configured to display monitoring data of the first physiological sign corresponding to different time points; and/or, display a change trend of the monitoring data of the first physiological sign over time.
  • the display module may also be configured to display a map page, where the epidemic risk level of the first area is marked on the map page.
  • the processing module 1303 can also be used to determine the contact distance between the user and the confirmed person according to the user's trajectory information and the confirmed person's trajectory information; when the contact distance is less than the transmission distance, and the contact time between the user and the confirmed person is greater than At the first threshold, it is determined that the user is a close contact of the confirmed person.
  • the processing module 1303 may also be configured to determine that the user is a close contact of the confirmed person when it is determined according to the location identifier that the user and the confirmed person are in the first confined space at the same time.
  • the location may include at least one of the following: train number and/or compartment number, room identification or elevator identification; the first enclosed space includes at least one of the following: a train compartment, a room, or an elevator car.
  • the characteristic information of the infectious disease in the embodiment of the present application includes at least one of the following: the transmission route of the infectious disease virus, the transmission distance of the infectious disease virus, the incubation period of the infectious disease, and the physiological signs related to the infectious disease.
  • Physiological signs include at least one of the following: body temperature, heart rate, RRI during one heartbeat, blood oxygen saturation Spo2, and sleep characteristics.
  • FIG. 14 it is a schematic structural diagram of a server provided by an embodiment of the present application.
  • the server 1400 includes a sending module 1401 , a receiving module 1402 and a processing module 1403 .
  • the sending module 1401 may be configured to send trajectory information of a person diagnosed with an infectious disease and feature information of an infectious disease to the electronic device, where the trajectory information includes location information and time information.
  • the receiving module 1402 may be configured to receive the health risk score of the user sent by the electronic device, and the user is a person who is confirmed to be a close contact of the confirmed person.
  • the processing module 1403 can be used to predict the epidemic risk of the first area according to the health risk score, the first area is the area where the user has stayed in the preset historical time period, and the epidemic risk includes the total number of infectious disease confirmed personnel and suspected personnel. Number of people at risk.
  • the processing module 1403 can also be used to determine the diffusion coefficient of the infectious disease in the first area according to the risk score; predict the total number of people at risk in the first area according to the diffusion coefficient and the existing number of people at risk and the diffusion coefficient in the first area. Number of people at risk; determine the epidemic risk level of the first area according to the total number of people on the sub-line.
  • the processing module 1403 may be further configured to determine diffusion coefficients corresponding to multiple risk levels, where the diffusion coefficients are used to indicate the growth rate of the number of people corresponding to the risk levels, and the risk levels are used to indicate is the probability of a person diagnosed with the infectious disease; according to the preset weights corresponding to the plurality of diffusion coefficients, the plurality of diffusion coefficients are weighted to determine the diffusion coefficient of the infectious disease in the first region.
  • the processing module 1403 can also be used to calculate the total number of people at risk according to the following formula:
  • N r (t) is the total number of people at risk at time point t
  • rs sm is the average confirmation rate of users in the first area confirming that they are close contacts
  • rs sp is the first The diffusion coefficient of infectious diseases in a region
  • N con is the current newly diagnosed person known from the outside
  • N b is the newly added risk number determined according to the data sent by the electronic device.
  • Embodiments of the present application also provide a computer-readable storage medium, where instructions are stored in the computer-readable storage medium, and when the computer or processor is run on a computer or a processor, the computer or the processor is made to execute any one of the above methods. or multiple steps.
  • Embodiments of the present application also provide a computer program product including instructions.
  • the computer program product when run on a computer or processor, causes the computer or processor to perform one or more steps of any of the above methods.
  • the computer program product includes one or more computer instructions.
  • the computer may be a general purpose computer, special purpose computer, computer network, or other programmable device.
  • the computer instructions may be stored in or transmitted over a computer-readable storage medium. The computer instructions can be sent from one website site, computer, server, or data center to another website site, computer, server or data center for transmission.
  • the computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, a data center, or the like that includes an integration of one or more available media.
  • the usable media may be magnetic media (eg, floppy disks, hard disks, magnetic tapes), optical media (eg, DVDs), or semiconductor media (eg, solid state disks (SSDs)), and the like.
  • the process can be completed by instructing the relevant hardware by a computer program, and the program can be stored in a computer-readable storage medium.
  • the program When the program is executed , which may include the processes of the foregoing method embodiments.
  • the aforementioned storage medium includes: ROM or random storage memory RAM, magnetic disk or optical disk and other mediums that can store program codes.

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Abstract

Selon des modes de réalisation, la présente demande concerne le domaine de la technologie électronique et porte sur un procédé de prédiction d'une épidémie et sur un dispositif électronique. Le procédé consiste principalement : à déterminer, au moyen d'un dispositif électronique côté utilisateur, si un utilisateur est une personne ayant été en contact étroit avec un cas confirmé sur la base du trajet du cas confirmé et de l'historique de trajets de l'utilisateur, puis à surveiller des signes physiologiques de l'utilisateur, et à rapporter les données de surveillance et le score de risque sanitaire de l'utilisateur, de sorte qu'un serveur peut prédire la tendance de développement d'une épidémie dans une zone particulière, ce qui rappelle à l'utilisateur la situation épidémique. Au moyen du procédé, une analyse de risque sanitaire et une tendance de développement d'une épidémie peuvent être facilement fournis aux utilisateurs en temps opportun, de telle sorte que les utilisateurs peuvent connaître leurs propres risques d'infection, et les gens peuvent planifier raisonnablement des voyages et organiser leur vie quotidienne.
PCT/CN2021/137280 2020-12-22 2021-12-11 Procédé de prédiction d'épidémie et dispositif électronique WO2022135197A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN202011532380.5A CN114724727A (zh) 2020-12-22 2020-12-22 一种疫情预测的方法及电子设备
CN202011532380.5 2020-12-22

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