WO2022217829A1 - Procédé et appareil de prévention et de commande de maladie infectieuse, dispositif informatique et support de stockage - Google Patents
Procédé et appareil de prévention et de commande de maladie infectieuse, dispositif informatique et support de stockage Download PDFInfo
- Publication number
- WO2022217829A1 WO2022217829A1 PCT/CN2021/118521 CN2021118521W WO2022217829A1 WO 2022217829 A1 WO2022217829 A1 WO 2022217829A1 CN 2021118521 W CN2021118521 W CN 2021118521W WO 2022217829 A1 WO2022217829 A1 WO 2022217829A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- user
- infectious disease
- information
- confirmed
- users
- Prior art date
Links
- 208000035473 Communicable disease Diseases 0.000 title claims abstract description 142
- 208000015181 infectious disease Diseases 0.000 title claims abstract description 91
- 238000000034 method Methods 0.000 title claims abstract description 45
- 230000006806 disease prevention Effects 0.000 title claims abstract description 24
- 230000002265 prevention Effects 0.000 claims abstract description 11
- 230000005541 medical transmission Effects 0.000 claims description 11
- 230000005540 biological transmission Effects 0.000 claims description 10
- 230000006854 communication Effects 0.000 claims description 8
- 238000004891 communication Methods 0.000 claims description 7
- 238000004590 computer program Methods 0.000 claims description 3
- 239000002245 particle Substances 0.000 claims description 3
- 238000010586 diagram Methods 0.000 description 5
- 201000010099 disease Diseases 0.000 description 5
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 5
- 230000006870 function Effects 0.000 description 5
- 241001465754 Metazoa Species 0.000 description 3
- 244000052769 pathogen Species 0.000 description 3
- 238000012549 training Methods 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 210000001124 body fluid Anatomy 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000000644 propagated effect Effects 0.000 description 2
- 201000006082 Chickenpox Diseases 0.000 description 1
- 208000005647 Mumps Diseases 0.000 description 1
- 206010046980 Varicella Diseases 0.000 description 1
- 239000010839 body fluid Substances 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000003745 diagnosis Methods 0.000 description 1
- 230000005560 droplet transmission Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000005567 fecaloral disease transmission Effects 0.000 description 1
- 230000036039 immunity Effects 0.000 description 1
- 206010022000 influenza Diseases 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 208000010805 mumps infectious disease Diseases 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000001932 seasonal effect Effects 0.000 description 1
- 239000002689 soil Substances 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000002747 voluntary effect Effects 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Classifications
-
- 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
-
- 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
Definitions
- Embodiments of the present invention relate to the technical field of disease control, and in particular, to a method, device, computer equipment, and storage medium for preventing and controlling infectious diseases.
- Infectious diseases are a class of diseases caused by various pathogens that can be transmitted from person to person, from animals to animals, or from humans to animals. Usually the disease is spread by direct contact with infected individuals, bodily fluids of infected persons, excrement of infected persons, and objects contaminated by infected persons, and can be transmitted through air, water, food, contact, soil, body fluids, and fecal-oral transmission.
- infectious diseases include contagiousness and epidemics, often with immunity after infection, and some infectious diseases are also seasonal or endemic.
- Common infectious diseases include chickenpox, mumps and influenza, etc. These diseases usually spread in a small or large area around after a case. If measures are not taken in time, it is likely to cause the continuous expansion of the infected area.
- Embodiments of the present invention provide a method, device, computer equipment and storage medium for preventing and controlling infectious diseases, so that users can know the required infectious disease risk value in time, so as to realize timely prevention and control of infectious diseases, and provide users with more intuitive valid data for reference.
- an embodiment of the present invention provides a method for preventing and controlling an infectious disease, the method comprising:
- an embodiment of the present invention also provides an infectious disease prevention and control device, the device comprising:
- the information acquisition module is used to acquire the information on the factors affecting the spread of infectious diseases in the preset area and the information of the confirmed users;
- a risk value prediction module configured to input the information on the infectious disease transmission influencing factors and the confirmed user information into the trained prediction model, and output the predicted infectious disease risk value of the preset area.
- an embodiment of the present invention further provides a computer device, the computer device comprising:
- processors one or more processors
- memory for storing one or more programs
- the one or more processors When the one or more programs are executed by the one or more processors, the one or more processors implement the infectious disease prevention and control method provided by any embodiment of the present invention.
- an embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, implements the infectious disease prevention and control method provided by any embodiment of the present invention.
- the embodiment of the present invention provides a method for preventing and controlling an infectious disease. First, obtain information on factors affecting the spread of infectious diseases and information on confirmed users in a preset area, and then input the information on factors affecting the spread of infectious diseases and information on confirmed users into a post-training prediction model. , so as to predict the infectious disease risk value of the preset area.
- the infectious disease prevention and control method provided by the embodiment of the present invention predicts the infectious disease risk value by taking into account the factors affecting the spread of infectious diseases in the required prediction area, and combining with the actual local incidence situation, and then using the trained prediction model to predict the infectious disease risk value.
- the intelligent prevention and control of infectious diseases is realized, without manual statistics and publicity, so that users can know the required infectious disease risk value in time, so as to prevent and control infectious diseases in a timely manner, and provide users with more intuitive and effective information.
- the risk data is used as a reference, so that users can decide travel plans at any time according to the current risk values of infectious diseases in various regions.
- Embodiment 1 is a flowchart of a method for preventing and controlling an infectious disease provided in Embodiment 1 of the present invention
- Embodiment 2 is a schematic structural diagram of an infectious disease prevention and control device provided in Embodiment 2 of the present invention.
- FIG. 3 is a schematic structural diagram of a computer device according to Embodiment 3 of the present invention.
- FIG. 1 is a flowchart of a method for preventing and controlling an infectious disease according to Embodiment 1 of the present invention.
- This embodiment can be applied to the situation of predicting the currently required infectious disease risk value in any set area.
- the method can be executed by the infectious disease prevention and control device provided by the embodiment of the present invention, and the device can be implemented by hardware and/or It can be implemented by means of software or software, and can generally be integrated into computer equipment, which can be, but is not limited to, various personal computers, servers, notebook computers, smart phones, tablet computers, and the like. As shown in Figure 1, it specifically includes the following steps:
- the initial preset area may be an area determined by simply dividing in the form of a provincial level, a municipal level, or a district level, or an area determined by customizing according to requirements.
- the information on factors affecting the spread of infectious diseases is an indicator of various factors that may affect the spread of infectious diseases, and may specifically include one or more of temperature, humidity, particle concentration in the air, light intensity, and population density in a preset area.
- droplet transmission and air transmission account for a large proportion, and these two transmission routes are largely affected by the above factors.
- the pathogens when the air is relatively humid and/or the temperature is relatively suitable, the pathogens will float and survive in the air for a relatively long time, so that there is a greater probability of transmission, and in the case of a larger population density, the transmission of pathogens Efficiency will also be higher than in a sparsely populated situation. That is to say, when the information on the influencing factors of infectious disease transmission is different, the risk value of infectious diseases is also different. Therefore, the information on the influencing factors of infectious disease transmission needs to be taken into account and used as the input of the prediction model to predict the risk value of infectious diseases.
- Diagnosed user information can include any relevant information of all currently diagnosed users in the preset area. Every time the infectious disease risk value needs to be predicted, all confirmed users in the preset area can be determined first, and then the currently required diagnosis can be obtained.
- User Info Specifically, it can be implemented through crowdsourcing. Crowdsourcing refers to a method in which a company or institution outsources work tasks performed by employees in the past to a non-specific public network in a free and voluntary form. In this embodiment, it can be The confirmed users are determined among the users of the crowdsourcing application in the preset area, and the mobile terminals used by the confirmed users can obtain and upload the information of the confirmed users by themselves. Specifically, it can be uploaded to the server, and the server can obtain the information in the preset area All confirmed user information.
- the diagnosed user information includes: user contact data of the diagnosed user; correspondingly, acquiring the diagnosed user information in a preset area includes: communicating between mobile terminals used by the user based on Bluetooth broadcast to generate each user information.
- User contact record of the user if the user becomes a confirmed user, the user contact record uploaded by the mobile terminal used by the confirmed user is received as the user contact data of the confirmed user.
- the user contact data may be within a preset time range, such as user contact records within the last month, and the user contact records of the diagnosed user may include identity information, contact timestamps, and contact locations of other users who are in contact with the diagnosed user. Wait. Communication between users' mobile terminals can be based on Bluetooth broadcast, and a user contact record can be generated after each communication is completed.
- the Bluetooth broadcast Since the Bluetooth broadcast has a certain distance limit, it can be determined that users on both sides of the communication have entered a contact distance that may be infected when communication occurs.
- the user contact records generated by each user can be stored locally, and only when the user is diagnosed, upload the currently required user contact data of the diagnosed user to the server, while normal users do not need to upload data, so as to protect the privacy of users as much as possible .
- the latest user contact data can also be uploaded at preset time intervals, and the uploading will be stopped after the user recovers, so that the infectious disease risk value can be predicted based on the latest situation.
- communication between mobile terminals used by users based on Bluetooth broadcast to generate a user contact record of each user includes: sending a broadcast signal to the surroundings every preset time period through the mobile terminal, and every After completing the transmission, switch back to the receiving mode to receive the surrounding broadcast signals; after each receiving the surrounding broadcast signals through the mobile terminal, a user contact record is generated and saved locally.
- the communication process between mobile terminals may be as follows: each mobile terminal sends a broadcast signal to the surroundings every preset time period, and switches back to the receiving mode after each transmission is completed to receive broadcast signals sent by other surrounding mobile terminals.
- the mobile terminal sending the signal can broadcast the local user identifier as the user's user information through low-power bluetooth broadcast, and the mobile terminal receiving the signal can generate a contact time stamp and contact position when receiving the broadcast signal, and according to the received The received user information, the generated contact timestamp and contact location and other information generate a user contact record and save it locally.
- the confirmed user information also includes: user contact data of the confirmed user who is in close contact with the user; correspondingly, if the user becomes the confirmed user, the user contact record uploaded by the mobile terminal used by the confirmed user is received as the confirmed user's contact record.
- the user contact data it also includes: determining the close contact user according to the user contact data of the confirmed user; informing the close contact user to upload the user contact record as the user contact data of the close contact user.
- the user contact data of the close contact users with the confirmed users can also be taken into account. Since the onset of infectious diseases may have a certain lag, the monitoring of the close contact users can improve the predictability.
- close contact users can be defined as users who have contact with confirmed users for more than a preset number of times within a certain period of time. Specifically, after receiving the user contact data of the confirmed user, the close contact users of the confirmed user can be determined according to the user contact data, and then a notification can be sent to the close contact user, so that the close contact user uploads his user contact data.
- the diagnosed user information further includes: the number of diagnosed users in the preset area and/or the location of the diagnosed users.
- the server can determine the number of confirmed users according to the received confirmed user information, and the confirmed users can obtain their own locations and upload them while uploading user contact data each time, so that the server can obtain the confirmed diagnoses in the current preset area. User's location.
- the number and location distribution of confirmed users are also factors that increase the risk of infectious diseases, so that more accurate predictions of infectious disease risk values can be achieved according to the number and location distribution of confirmed users.
- the prediction model may be any model that can predict the risk value of infectious diseases, which is not limited in this embodiment. Specifically, a model with better effect may be selected according to the comparison result between the actual prediction result and the real situation. After obtaining the information on the factors influencing the spread of infectious diseases and the information on the confirmed users in the preset area, the information on the influencing factors on the spread of infectious diseases and the information on the confirmed users can be input into the trained prediction model to predict the infectious diseases in the preset area. value at risk. Before using the prediction model, the historical information on infectious disease transmission factors and confirmed user information can be used as the input of the prediction model, and the corresponding historical real infectious disease risk value, that is, the actual statistical probability of being infected, can be used as the input of the prediction model.
- the output is trained on the predictive model, thereby obtaining a trained predictive model.
- the infectious disease risk value can be sent to the mobile terminal used by each user, so that the user can know the probability of being infected in a certain area at any time, so as to decide whether to go to this area. region, which can provide users with more intuitive and effective data for travel and avoidance planning.
- the preset area can be more finely adjusted according to the infectious disease risk value and the distribution of confirmed users, so as to better reflect the infectious disease in an area. disease development.
- the method further includes: The infectious disease risk value is adjusted for the preset time period. Specifically, when the risk value of infectious diseases is high, the preset area can be determined as a high-risk area. At this time, it is necessary to monitor the high-risk area more closely, that is, the preset time can be shortened to ensure more complete user contact records. It is more sufficient, so as to avoid missing the contact of the confirmed user and make the prediction of the risk value of infectious diseases more accurate. When the infectious disease risk value is low, the preset area can be determined as a low-risk area, and the storage of user contact records and the communication between mobile terminals can be reduced by extending the preset time period, thereby reducing the corresponding waste of resources.
- the technical solution provided by the embodiment of the present invention first obtains the information on the influencing factors of infectious disease transmission and the information of the confirmed users in the preset area, and then inputs the information on the influencing factors of the infectious disease transmission and the information of the confirmed users into the post-training prediction model, so as to obtain the prediction result.
- the infectious disease risk value of the preset area By considering the factors affecting the spread of infectious diseases in the required prediction area, combined with the actual local incidence, and then using the trained prediction model to predict the risk value of infectious diseases, the intelligent prevention and control of infectious diseases is realized, and no manual work is required. Statistics and publicity allow users to know the required infectious disease risk value in time, so as to prevent and control infectious diseases in a timely manner, and provide users with more intuitive and effective risk data as a reference, so that users can The communicable disease risk value determines travel planning.
- FIG. 2 is a schematic structural diagram of an infectious disease prevention and control device provided in Embodiment 2 of the present invention.
- the device may be implemented by hardware and/or software, and may generally be integrated into computer equipment for executing any of the embodiments of the present invention.
- the computer equipment can be, but is not limited to, various personal computers, servers, notebook computers, smart phones, tablet computers, and the like.
- the device includes:
- the information acquisition module 21 is used to acquire the information on the influencing factors of the spread of infectious diseases and the information of the confirmed users in the preset area;
- the risk value prediction module 22 is used for inputting the information on the influencing factors of the spread of infectious diseases and the information of the confirmed users into the trained prediction model, and outputting the predicted infectious disease risk value of the preset area.
- the technical solution provided by the embodiment of the present invention first obtains the information on the influencing factors of infectious disease transmission and the information of the confirmed users in the preset area, and then inputs the information on the influencing factors of the infectious disease transmission and the information of the confirmed users into the post-training prediction model, so as to obtain the prediction result.
- the infectious disease risk value of the preset area By considering the factors affecting the spread of infectious diseases in the required prediction area, combined with the actual local incidence, and then using the trained prediction model to predict the risk value of infectious diseases, the intelligent prevention and control of infectious diseases is realized, and no manual work is required. Statistics and publicity allow users to know the required infectious disease risk value in time, so as to prevent and control infectious diseases in a timely manner, and provide users with more intuitive and effective risk data as a reference, so that users can The communicable disease risk value determines travel planning.
- the diagnosed user information includes: user contact data of the diagnosed user;
- the information acquisition module 21 includes:
- a user contact record generating unit configured to communicate between mobile terminals used by users based on Bluetooth broadcast, to generate a user contact record of each user;
- the user contact data uploading unit is configured to, if the user becomes a confirmed user, receive the user contact record uploaded by the mobile terminal used by the confirmed user as the user contact data of the confirmed user.
- the user contact record generating unit includes:
- the signal sending subunit is used to send a broadcast signal to the surrounding every preset time period through the mobile terminal, and switch back to the receiving mode after each transmission is completed to receive the surrounding broadcast signal;
- the user contact record generating subunit is used to generate a user contact record and save it locally after each time the mobile terminal receives surrounding broadcast signals.
- the infectious disease prevention and control device further includes:
- the preset duration adjustment module is used to input the information on the influencing factors of infectious disease transmission and the information of confirmed users into the trained prediction model, and output the predicted infectious disease risk value of the preset area, and adjust the preset according to the infectious disease risk value. time to adjust.
- the diagnosed user information further includes: user contact data of the close contact user of the diagnosed user;
- the information acquisition module 21 also includes:
- the close contact user determination unit is used to determine the close contact user according to the user contact data of the confirmed user after receiving the user contact record uploaded by the mobile terminal used by the confirmed user as the user contact data of the confirmed user if the user becomes the confirmed user;
- the notification uploading unit is used to notify the close contact user to upload the user contact record as the user contact data of the close contact user.
- the diagnosed user information further includes: the number of the diagnosed users and/or the location of the diagnosed users in the preset area.
- the information on factors affecting the spread of infectious diseases includes one or more of temperature, humidity, particle concentration in the air, light intensity, and population density in a preset area.
- the infectious disease prevention and control device provided by the embodiment of the present invention can execute the infectious disease prevention and control method provided by any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method.
- the included units and modules are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be realized;
- the specific names of the functional units are only for the convenience of distinguishing from each other, and are not used to limit the protection scope of the present invention.
- FIG. 3 is a schematic structural diagram of a computer device according to Embodiment 3 of the present invention, and shows a block diagram of an exemplary computer device suitable for implementing the embodiments of the present invention.
- the computer device shown in FIG. 3 is only an example, and should not impose any limitation on the function and scope of use of the embodiments of the present invention.
- the computer device includes a processor 31, a memory 32, an input device 33 and an output device 34; the number of processors 31 in the computer device may be one or more, and one processor 31 is taken as an example in FIG. 3 , the processor 31 , the memory 32 , the input device 33 and the output device 34 in the computer equipment may be connected through a bus or other means, and the connection through a bus is taken as an example in FIG. 3 .
- the memory 32 can be used to store software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the infectious disease prevention and control method in the embodiment of the present invention (for example, an infectious disease prevention and control device).
- the processor 31 executes various functional applications and data processing of the computer equipment by running the software programs, instructions, and modules stored in the memory 32, ie, implements the above-mentioned infectious disease prevention and control method.
- the memory 32 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the computer equipment, and the like. Additionally, memory 32 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, or other non-volatile solid state storage device. In some instances, memory 32 may further include memory located remotely from processor 31, which may be connected to the computer device through a network. Examples of such networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.
- the input device 33 can be used to obtain information on factors affecting the spread of infectious diseases and confirmed user information in a preset area, and to generate key signal inputs related to user settings and function control of computer equipment, and the like.
- the output device 34 may include a display screen or the like, which may be used to display the predicted infectious disease risk value data to the user.
- Embodiment 4 of the present invention further provides a storage medium containing computer-executable instructions, where the computer-executable instructions are used to execute a method for preventing and controlling infectious diseases when executed by a computer processor, and the method includes:
- the storage medium may be any of various types of memory devices or storage devices.
- the term "storage medium” is intended to include: installation media such as CD-ROM, floppy disk or tape devices; computer system memory or random access memory such as DRAM, DDR RAM, SRAM, EDO RAM, Rambus RAM, etc.; non-volatile memory such as flash memory, magnetic media (eg, hard disk or optical storage); registers or other similar types of memory elements, and the like.
- the storage medium may also include other types of memory or combinations thereof.
- the storage medium may be located in the computer system in which the program is executed, or may be located in a different second computer system connected to the computer system through a network such as the Internet.
- the second computer system may provide program instructions to the computer for execution.
- storage medium may include two or more storage media that may reside in different locations (eg, in different computer systems connected by a network).
- the storage medium may store program instructions (eg, embodied as a computer program) executable by one or more processors.
- a storage medium containing computer-executable instructions provided by the embodiments of the present invention, the computer-executable instructions of which are not limited to the above method operations, and can also execute the infectious disease prevention and control method provided by any embodiment of the present invention. related operations in .
- a computer-readable signal medium may include a propagated data signal in baseband or as part of a carrier wave, with computer-readable program code embodied thereon. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing.
- a computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device .
- Program code embodied on a computer readable medium may be transmitted using any suitable medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
- the present invention can be realized by software and necessary general-purpose hardware, and of course can also be realized by hardware, but in many cases the former is a better embodiment .
- the technical solutions of the present invention can be embodied in the form of software products in essence or the parts that make contributions to the prior art, and the computer software products can be stored in a computer-readable storage medium, such as a floppy disk of a computer , Read-Only Memory (ROM), Random Access Memory (RAM), Flash Memory (FLASH), hard disk or CD, etc., including several instructions to make a computer device (which can be a personal computer) , server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.
- ROM Read-Only Memory
- RAM Random Access Memory
- FLASH Flash Memory
Landscapes
- Health & Medical Sciences (AREA)
- Public Health (AREA)
- Engineering & Computer Science (AREA)
- Medical Informatics (AREA)
- Biomedical Technology (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- Pathology (AREA)
- Epidemiology (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Medical Treatment And Welfare Office Work (AREA)
Abstract
Sont divulgués dans les modes de réalisation de la présente invention un procédé et un appareil de prévention et de commande de maladie infectieuse, un dispositif informatique et un support de stockage. Le procédé consiste à : acquérir des informations de facteur d'influence de propagation de maladie infectieuse et des informations d'utilisateurs diagnostiqués dans une région prédéfinie ; et entrer les informations de facteur d'influence de propagation de maladie infectieuse et les informations d'utilisateurs diagnostiqués dans un modèle de prédiction entraîné, et délivrer une valeur de risque prédite de maladie infectieuse de la région prédéfinie. Au moyen de la solution technique fournie dans les modes de réalisation de la présente invention, des facteurs influençant la propagation de maladies infectieuses dans une région nécessitant une prédiction sont pris en considération, puis une valeur de risque de maladie infectieuse est prédite en utilisant un modèle de prédiction entraîné en combinaison avec une condition d'incidence locale réelle, de manière à réaliser une intégration d'intelligence de prévention et de lutte contre des maladies infectieuses, de telle sorte qu'un utilisateur peut trouver une valeur de risque de maladie infectieuse requise d'une manière opportune, et ainsi la prévention et le contrôle peuvent être effectués sur les maladies infectieuses de manière opportune. De plus, des données de risque plus intuitives et efficaces sont fournies à l'utilisateur comme référence, de telle sorte que l'utilisateur peut déterminer un plan de déplacement à tout moment en fonction de valeurs de risque de maladie infectieuse actuelles de diverses régions.
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110410104.XA CN113113154A (zh) | 2021-04-16 | 2021-04-16 | 一种传染病防控方法、装置、计算机设备及存储介质 |
CN202110410104.X | 2021-04-16 |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2022217829A1 true WO2022217829A1 (fr) | 2022-10-20 |
Family
ID=76717933
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/CN2021/118521 WO2022217829A1 (fr) | 2021-04-16 | 2021-09-15 | Procédé et appareil de prévention et de commande de maladie infectieuse, dispositif informatique et support de stockage |
Country Status (2)
Country | Link |
---|---|
CN (1) | CN113113154A (fr) |
WO (1) | WO2022217829A1 (fr) |
Families Citing this family (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113113154A (zh) * | 2021-04-16 | 2021-07-13 | 南方科技大学 | 一种传染病防控方法、装置、计算机设备及存储介质 |
CN113470836B (zh) * | 2021-07-28 | 2024-09-03 | 联通(广东)产业互联网有限公司 | 一种传染病趋势预测方法、系统、装置及存储介质 |
CN113707338B (zh) * | 2021-10-28 | 2022-08-30 | 南方科技大学 | 景区疫情风险预测与限流方法、装置、设备和存储介质 |
CN114613518A (zh) * | 2022-03-31 | 2022-06-10 | 医渡云(北京)技术有限公司 | 基于空间信息的传染病预测方法、装置、存储介质及设备 |
CN116721781B (zh) * | 2023-07-11 | 2024-08-20 | 中国科学院地理科学与资源研究所 | 虫媒传染病传播风险的预测方法、装置、电子设备及介质 |
CN116644869B (zh) * | 2023-07-27 | 2023-11-10 | 中南大学湘雅医院 | 一种实时数据分析与公共卫生事件预测系统 |
CN117457231B (zh) * | 2023-10-27 | 2024-06-11 | 中山大学 | 一种基于马尔可夫链模型的病毒传播风险计算方法及装置 |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111128399A (zh) * | 2020-03-30 | 2020-05-08 | 广州地理研究所 | 一种基于人流密度的流行病疫情风险等级评估方法 |
US20200294680A1 (en) * | 2017-05-01 | 2020-09-17 | Health Solutions Research, Inc. | Advanced smart pandemic and infectious disease response engine |
CN111918215A (zh) * | 2020-06-30 | 2020-11-10 | 王云峰 | 通过蓝牙对传染病密切接触者进行追踪的方法与系统 |
CN112652403A (zh) * | 2020-12-25 | 2021-04-13 | 中国科学技术大学 | 疫情预测方法及装置 |
CN113113154A (zh) * | 2021-04-16 | 2021-07-13 | 南方科技大学 | 一种传染病防控方法、装置、计算机设备及存储介质 |
Family Cites Families (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US11238989B2 (en) * | 2017-11-08 | 2022-02-01 | International Business Machines Corporation | Personalized risk prediction based on intrinsic and extrinsic factors |
CN111640515A (zh) * | 2020-05-26 | 2020-09-08 | 深圳市通用互联科技有限责任公司 | 区域的疫情风险确定方法、装置、计算机设备和存储介质 |
CN111653358A (zh) * | 2020-05-29 | 2020-09-11 | 鹏城实验室 | 感染风险评估方法、第一终端及计算机存储介质 |
CN111785380B (zh) * | 2020-07-01 | 2022-12-02 | 医渡云(北京)技术有限公司 | 传染性疾病患病风险等级的预测方法及装置、介质、设备 |
CN112382407A (zh) * | 2020-11-12 | 2021-02-19 | 平安科技(深圳)有限公司 | 一种风险管控方法、装置、电子设备和存储介质 |
-
2021
- 2021-04-16 CN CN202110410104.XA patent/CN113113154A/zh active Pending
- 2021-09-15 WO PCT/CN2021/118521 patent/WO2022217829A1/fr active Application Filing
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20200294680A1 (en) * | 2017-05-01 | 2020-09-17 | Health Solutions Research, Inc. | Advanced smart pandemic and infectious disease response engine |
CN111128399A (zh) * | 2020-03-30 | 2020-05-08 | 广州地理研究所 | 一种基于人流密度的流行病疫情风险等级评估方法 |
CN111918215A (zh) * | 2020-06-30 | 2020-11-10 | 王云峰 | 通过蓝牙对传染病密切接触者进行追踪的方法与系统 |
CN112652403A (zh) * | 2020-12-25 | 2021-04-13 | 中国科学技术大学 | 疫情预测方法及装置 |
CN113113154A (zh) * | 2021-04-16 | 2021-07-13 | 南方科技大学 | 一种传染病防控方法、装置、计算机设备及存储介质 |
Also Published As
Publication number | Publication date |
---|---|
CN113113154A (zh) | 2021-07-13 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
WO2022217829A1 (fr) | Procédé et appareil de prévention et de commande de maladie infectieuse, dispositif informatique et support de stockage | |
Kaplan | OM Forum—COVID-19 scratch models to support local decisions | |
US11503434B2 (en) | Method and system for connectivity between a personal area network and an internet protocol network via low power wide area network wearable electronic device | |
CN104782103B (zh) | 使用低功率警报传感器的聚集框架 | |
US8995624B2 (en) | Remote virtual supervision system | |
CN107209540A (zh) | 对计算设备上的热修复进行管理 | |
CN104685532A (zh) | 人身安全和应急服务 | |
CN111815104A (zh) | 一种用于进行应急响应资源调度的方法与设备 | |
Strickling et al. | Simulation of containment and wireless emergency alerts within targeted pressure zones for water contamination management | |
US12039856B2 (en) | Incident response system | |
CN111681771A (zh) | 一种疫情信息协管系统及疫情信息协管方法 | |
US11030884B1 (en) | Real-time prevention and emergency management system and respective method of operation | |
KR100937525B1 (ko) | 음향 센서를 이용한 치안 유지 usn 시스템 및 이를이용한 치안 유지 방법 | |
Abusalama et al. | Multi-agents system for early disaster detection, evacuation and rescuing | |
CN115909657A (zh) | 安全预警的方法、装置、设备和计算机可读介质 | |
Božić | Applications of fog computing for smart sensors | |
KR20220140229A (ko) | 스마트 중재 서버, 층간소음을 중재하는 스마트 중재 방법 및 컴퓨터 프로그램 | |
Sultana et al. | An IoT Prototype for Monitoring Covid19 Patients Using Real Time Data from Wearable Sensor Through Android App | |
CAO et al. | An os for internet of everything: Early experience from a smart home prototype | |
Nam et al. | Intelligent context-aware energy management using the incremental simultaneous method in future wireless sensor networks and computing systems | |
US12072677B2 (en) | System and method for preemptive shutdown of utilities, facilities or systems in smart cities | |
CN114183898B (zh) | 新风机系统预约方法、装置、系统、电子设备及存储介质 | |
KR102543932B1 (ko) | 재난재해시 환경기초시설의 피해를 조기에 복구하기 위한 방법, 애플리케이션 및 단말 | |
Egwuche et al. | A Conceptual Model for the Prediction of Coronavirus (Covid-19) Spread in Nigeria | |
Abdulameer et al. | The Impact of IOT on Real-World Decisions in the next Stage |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 21936699 Country of ref document: EP Kind code of ref document: A1 |
|
NENP | Non-entry into the national phase |
Ref country code: DE |
|
122 | Ep: pct application non-entry in european phase |
Ref document number: 21936699 Country of ref document: EP Kind code of ref document: A1 |