Infectious disease whole-process tracking intervention method and system, server and storage medium

Abstract

The invention discloses an infectious disease whole-process tracking intervention method and system, a server and a storage medium. The tracking intervention method comprises the following steps: S1, acquiring clinical data of a patient; s2, establishing an infectious disease monitoring closed loop; s3, constructing a time-space relationship model, and generating a patient relationship network; s4, establishing an individual case of the infectious disease patient, and storing a space-time route of the infectious disease patient; inputting information of infectious disease patients, positioning spatial positions of the infectious disease patients, tracing associated patients according to the spatial positions, and screening high-risk patients; and S5, the early warning information and the intervention plan are pushed to the risk node terminal, and the infectious disease patient is intervened. According to the tracking intervention method, the calculated amount is relatively small, positioning is more accurate, the tracking intervention system can be integrated with an existing hospital information management system, a dynamic monitoring network covering the diagnosis and treatment process of a patient is constructed, real-time tracking, real-time early warning and real-time intervention are conducted, and further transmission of infectious diseases is effectively prevented.

Description

Technical Field

[0001] The present invention belongs to the field of data processing technology, and in particular relates to a method, system, server and storage medium for tracking and intervening in the entire process of infectious diseases. Background Art

[0002] Infectious diseases spread quickly, and infectious disease monitoring and early warning are important basic tasks for disease prevention and control.

[0003] In the existing hospital infectious disease prevention and control work, there are often reasons such as incomplete patient reserved information, unclear movement routes of infectious disease patients, and insufficiently sensitive early warning of the monitoring system, which lead to the inability to report and intervene in infectious disease patients in a timely and effective manner, thus missing the golden period for preventing the spread of infectious diseases and may cause large-scale outbreaks of infectious diseases. Summary of the Invention

[0004] The purpose of the present invention is to solve the above-mentioned technical problems existing in the prior art, and to provide a method, system, server and storage medium for tracking and intervening in the entire process of infectious diseases. When tracking and tracing the source of infectious diseases, the tracking and intervention method has a relatively smaller computational load and more accurate positioning, which can solve the problems of large computational load and inaccurate positioning in existing methods for tracking and tracing the source of infectious diseases. The tracking and intervention system can be integrated with the existing hospital information management system to build a dynamic monitoring network covering the patient's diagnosis and treatment process, and perform real-time tracking, real-time warning, and real-time intervention to effectively prevent the further spread of infectious diseases.

[0005] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0006] A method for tracking and intervening in the entire process of an infectious disease, characterized by comprising the following steps:

[0007] S1. Obtain patient clinical data;

[0008] S2. Set up prevention and control nodes and early warning windows to establish a closed loop for infectious disease monitoring;

[0009] S3, constructing a spatiotemporal relationship model based on the patient clinical data obtained in step S1, wherein the spatiotemporal relationship model generates a patient relationship network based on the spatiotemporal relationship between patients;

[0010] S4. Create individual cases of infectious disease patients and store their spatiotemporal routes;

[0011] Input the information of infectious disease patients, locate their spatial position in the patient relationship network, and trace related patients based on this information to screen high-risk patients;

[0012] S5. Push the early warning information and intervention plan to the risk node terminal, and intervene on the infectious disease patients according to the intervention plan.

[0013] Furthermore, the specific method of step S1 is: obtaining the patient's clinical data from the hospital information management system, and converting the patient's clinical data into a unified data format through a data cleaning module.

[0014] Furthermore, the specific method of step S2 is: setting the prevention and control nodes corresponding to the patient's visit to the hospital, immediately collecting, recording, analyzing, and judging the patient's infectious disease situation at each prevention and control node, setting an early warning window in the hospital information management system for early warning, and establishing a real-time tracking and real-time intervention infectious disease monitoring closed loop.

[0015] Furthermore, the specific method for constructing the spatiotemporal relationship model in step S3 is: using all prevention and control nodes as data anchor points, the patient clinical data obtained in step S1 are cleaned and saved; outpatient treatment information data, hospitalization information data, and discharge information data are obtained from the cleaned patient clinical data; outpatient treatment information data, hospitalization information data, and discharge information data are analyzed, and patients with spatiotemporal clustering are recorded as associated patients to generate a patient relationship network.

[0016] Furthermore, the specific method of step S4 is: when abnormal infectious disease case data appears, an infectious disease patient case is established, the diagnosis and treatment data of the infectious disease patient from outpatient to discharge are retrieved, the entire process of the infectious disease patient is tracked, a time-space route is generated, and the data is collected, recorded, and analyzed to locate the spatial position of the infectious disease patient in the patient relationship network, and to determine whether the infectious disease patient's associated patients have infectious disease patients, whether the diagnosis issued by the doctor for the associated patient is related to the infectious disease, whether the test application issued by the doctor for the associated patient is related to the infectious disease, and whether the current infectious disease-related test result report determines that the associated patient is positive for the infectious disease.

[0017] Furthermore, if there is already a patient with such an infectious disease among the associated patients of the infectious disease patient, the infectious disease patient who is closest to the infectious disease patient is judged to be the transmitter, and the infectious disease patient is the latest patient in this transmission path. The latest transmission path is generated, and the associated patients are continued to be traced until the associated patients of the latest transmission path do not meet the infectious disease screening conditions.

[0018] Furthermore, the specific method of step S5 is: configure an early warning intervention module for the terminal device corresponding to each prevention and control node, locate the position of the infectious disease patient in all prevention and control nodes, and push the early warning information to the next node terminal, and intervene in the infectious disease patient according to the intervention plan.

[0019] An infectious disease full-process tracking and intervention system, characterized by comprising:

[0020] Data acquisition module, used to obtain patient clinical data from the hospital information management system;

[0021] The data cleaning module is used to convert the patient clinical data obtained by the data acquisition module into a unified data format and remove redundant data;

[0022] The data monitoring module embedded in the hospital information management system is used to monitor the patient clinical data obtained by the data acquisition module in real time;

[0023] The spatiotemporal relationship module is used to construct a spatiotemporal relationship model based on the patient clinical data obtained by the data acquisition module. The spatiotemporal relationship model generates a patient relationship network based on the spatiotemporal relationship between patients. The spatiotemporal relationship model generates a transmission path map based on the spatiotemporal trajectory of the patients and outputs the transmission path map to the early warning intervention module.

[0024] The early warning intervention module is used to locate the terminal equipment that needs intervention based on the propagation path diagram input by the spatiotemporal relationship module, push the early warning information to the risk node terminal for intervention, and then feed back the intervention results to the spatiotemporal relationship module. The spatiotemporal relationship module optimizes the spatiotemporal relationship model based on the intervention results.

[0025] A server, characterized in that the server includes: one or more processors; a memory for storing one or more programs, which, when executed by one or more processors, enables the one or more processors to implement the above-mentioned full-process infectious disease tracking and intervention method.

[0026] A storage medium, characterized in that a computer program is stored in the storage medium, and when the computer program is executed by a processor, the above-mentioned infectious disease full-process tracking and intervention method is implemented.

[0027] The present invention has the following beneficial effects due to the adoption of the above technical solution:

[0028] 1. The tracking and intervention system in the present invention can be integrated with the existing hospital information management system to build a dynamic monitoring network covering the patient's diagnosis and treatment process, conduct real-time tracking, real-time warning, and real-time intervention, effectively prevent the further spread of infectious diseases, and help clinicians promptly and effectively handle reports of infectious diseases, deaths, and other suspected hospital-acquired cases and clustered infectious events in the hospital, guide clinical medical staff to implement intervention measures, achieve early detection, early reporting, early isolation, and early treatment of infectious diseases, prevent cross-infection in the hospital, and solve the problem that the existing methods of tracking and tracing infectious diseases are relatively backward and prone to late reporting or missed reporting by medical staff.

[0029] 2. The tracking and intervention method of the present invention is used to track and trace the source of infectious diseases. Its calculation amount is relatively small and the positioning is more accurate, which can solve the problems of large calculation amount and inaccurate positioning in existing methods of tracking and tracing the source of infectious diseases. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The present invention will be further described below in conjunction with the accompanying drawings:

[0031] Figure 1 Schematic diagram of the process of the tracking intervention method of the present invention;

[0032] Figure 2 This is a schematic diagram of the process of a patient visiting a hospital for treatment in the present invention;

[0033] Figure 3 Schematic diagram of the infectious disease full-process tracking and intervention system of the present invention. DETAILED DESCRIPTION

[0034] like Figure 3 As shown, a full-process tracking and intervention system for infectious diseases includes: a data acquisition module for acquiring patient clinical data from a hospital information management system; a data cleaning module for converting the patient clinical data acquired by the data acquisition module into a unified data format and removing redundant data; and a data monitoring module embedded in the hospital information management system for real-time monitoring of the patient clinical data acquired by the data acquisition module.

[0035] The spatiotemporal relationship module is used to construct a spatiotemporal relationship model based on the patient clinical data obtained by the data acquisition module. The spatiotemporal relationship model generates a patient relationship network based on the spatiotemporal relationship between patients. The spatiotemporal relationship model generates a propagation path map based on the patient's spatiotemporal trajectory and outputs the propagation path map to the early warning intervention module.

[0036] The early warning intervention module is used to locate the terminal equipment that needs intervention based on the propagation path diagram input by the spatiotemporal relationship module, push the early warning information to the risk node terminal for intervention, and then feed back the intervention results to the spatiotemporal relationship module. The spatiotemporal relationship module optimizes the spatiotemporal relationship model based on the intervention results.

[0037] like Figure 1 As shown, a method for tracking and intervening in the entire process of an infectious disease includes the following steps:

[0038] S1. The data acquisition module obtains patient clinical data in real time from multiple data sources in the hospital information management system through various forms of interfaces, and converts the patient clinical data into a unified data format through the data cleaning module to form a consistent data structure, which is convenient for subsequent data processing and analysis.

[0039] Hospital information management systems include hospital information systems (HIS), laboratory information management systems (LIS), imaging information systems (RIS), electronic medical records (EMR), and picture archiving and communication systems (PACS). Patient clinical data includes personal information, medical records, diagnoses, prescriptions, medications, and test results. Various interfaces can be used, including direct database connections, medical standard protocol interfaces, service-oriented interfaces, and message-based middleware interfaces.

[0040] The data cleaning module builds a data standardization pipeline through ETL middleware, which specifically includes the following technologies: (1) Extraction layer:

[0041] (1.1) Dynamic adapter: Automatically identify different data source protocols, such as HL7 message header parsing and MQ message routing;

[0042] (1.2) Incremental capture module: obtains HIS system data changes through timestamp comparison or triggers; (2) Conversion layer:

[0043] (2.1) Structured cleaning engine:

[0044] Missing value processing: For patients who have not filled in their contact information, historical medical records will be automatically linked to complete the missing value;

[0045] Terminology standardization: mapping local diagnostic codes of each system to ICD-11 standards;

[0046] (2.2) Spatiotemporal alignment module:

[0047] Timeline calibration: unify the time zone settings of each system, such as converting the specimen receipt time in the LIS system to standard UTC time;

[0048] Location trajectory reconstruction: Generate a heat map of patients' movement within the hospital based on access card swipe records and medical treatment events;

[0049] (2.3) Relationship Network Builder:

[0050] Node link analysis: Identify high-risk contact paths through the medical department association algorithm;

[0051] (3) Loading layer:

[0052] Use dynamic sharding technology to write processed data into the infectious disease database;

[0053] Establish a spatiotemporal joint index, such as a three-dimensional index of patient ID, timestamp, and geographic coordinates, to accelerate spatiotemporal trajectory queries.

[0054] This ETL middleware integrates Apache Camel to implement protocol conversion and uses Flink for stream and batch processing. It ultimately generates a data format that meets the requirements of the spatiotemporal relationship model. Its data structure includes:

[0055] Ⅰ Patient master data area: patient ID, demographic attributes, contact information;

[0056] II. Space-time trajectory area: time series of diagnosis and treatment nodes, department coordinate positioning;

[0057] III Relationship network area: contact intensity weight matrix, propagation path tree structure.

[0058] S2. Set up 21 prevention and control nodes corresponding to patients' visits to the hospital, and immediately collect, record, analyze, and judge the infectious disease status of patients at each prevention and control node. Set up an early warning window in the hospital information management system for early warning, and establish a closed loop of infectious disease monitoring with real-time tracking and real-time intervention.

[0059] Among them, patients include but are not limited to outpatients and inpatients, etc. The 21 prevention and control nodes include outpatient visits, outpatient diagnosis, outpatient test application, outpatient culture application, outpatient examination application, outpatient test results report, outpatient culture test results report, outpatient examination results report, outpatient medical orders, hospital admission, hospital diagnosis, hospital transfer, hospital discharge, hospital test application, hospital culture application, hospital examination application, hospital test results report, hospital culture test results report, hospital examination results report, hospital medical orders, and hospital medical record writing. Figure 2 shown.

[0060] When a patient encounters a situation that requires treatment during diagnosis and treatment, intervene immediately:

[0061] The hospital's outpatient and inpatient medical staff mainly use the hospital information management system to enter patient diagnoses, applications, cases, etc. The inspection result data of 21 prevention and control nodes (outpatient visit data, outpatient diagnosis data, outpatient test application data, outpatient culture application data, outpatient examination application data, outpatient report test result data, outpatient report culture test result data, outpatient report examination result data, outpatient medical order data, inpatient admission data, inpatient diagnosis data, inpatient transfer data, inpatient discharge data, inpatient test application data, inpatient culture application data, inpatient examination application data, inpatient report test result data, inpatient report culture test result data, inpatient report examination result data, inpatient medical order data, inpatient written medical record data) can be obtained in real time by collecting data from the hospital information management system. Other diagnosis and treatment data need to be entered into the hospital information management system by medical staff for identification. In order to assist doctors in timely identifying suspected infectious disease cases, when the doctor enters the patient's diagnosis and treatment data and saves the action, the system used by the doctor's workstation will send key information to the infectious disease monitoring system in the background for identification. The infectious disease monitoring system will feed back the identification results to the system used by the doctor's workstation. If the identification result is that the patient is a suspected infectious disease patient, a pop-up window will pop up to remind the doctor to retain the patient in time and enter key basic patient information to facilitate subsequent intervention; if the identification result is that the patient is a suspected non-infectious disease patient, no response will be taken.

[0062] S3. Construct a spatiotemporal relationship model based on the patient clinical data obtained in step S1. The spatiotemporal relationship model generates a patient relationship network based on the spatiotemporal relationship between patients. Specifically:

[0063] ① Taking all prevention and control nodes as data anchor points, clean and save the patient clinical data obtained in step S1 to obtain the inspection result data of each prevention and control node;

[0064] ② Obtain outpatient visit information data, hospitalization information data, and discharge information data from the cleaned patient clinical data. Outpatient visit information data includes patient visit time, visit department, visit clinic, outpatient test information, outpatient culture information, outpatient examination information, and outpatient medical order information. Hospitalization information data includes hospitalization time, hospitalization department, hospitalization ward, hospitalization diagnosis, hospitalization transfer information, hospitalization test information, hospitalization culture information, and hospitalization examination information. Discharge information data includes discharge time, discharge department, discharge ward, medical order, and hospitalization medical records.

[0065] Among them, the test information issued in outpatient clinics and inpatient clinics include the patient's medical record number, the department where the test is sent, the test items, the sampling time, and the test results. The inpatient transfer information includes the patient's medical record number, the inpatient department, the admission time, the discharge time, and the ward number.

[0066] ③Analyze outpatient treatment information data, hospitalization information data, and discharge information data, mark the patient treatment data that meets the outpatient association conditions and hospitalization association conditions, record patients who are clustered in time and space as associated patients, and generate a patient relationship network.

[0067] Among them, the outpatient association conditions are specifically as follows: patients who visit the same outpatient department, the same clinic, and within the same time period. The specific time screening conditions are preset according to the different types of infectious diseases. The hospitalization association conditions are specifically as follows: patients who visit the same hospital department, the same ward, and within the same time period. The specific time screening conditions are preset according to the different types of infectious diseases.

[0068] Spatiotemporal clustering refers to a group of patients who have contact behaviors within a specific spatiotemporal threshold. Its technical implementation includes the following:

[0069] Dynamic time window: set according to different infectious diseases;

[0070] Spatial map: satisfies spatial association conditions;

[0071] Aggregation determination rules: Time and space meet the thresholds at the same time, such as a group of patients staying in the same ward for no less than 15 minutes.

[0072] S4. When abnormal infectious disease case data appears, the data collection module establishes an infectious disease patient case, retrieves the diagnosis and treatment data of the infectious disease patient from outpatient to discharge, tracks the entire process of the infectious disease patient, generates a time-space route, and collects, records, and analyzes it to locate the spatial position of the infectious disease patient in the patient relationship network, and determines whether the infectious disease patient's associated patients have infectious disease patients, whether the diagnosis issued by the doctor for the associated patient is related to the infectious disease, whether the test application issued by the doctor for the associated patient is related to the infectious disease, and whether the current infectious disease-related test result report determines that the associated patient is positive for the infectious disease, thereby screening out high-risk patients.

[0073] High-risk patients are temporally and spatially associated with confirmed infectious disease patients and meet any of the following conditions:

[0074] ① Direct contact risk: The time a high-risk patient and a confirmed infectious disease patient spend together at the same prevention and control node should not be less than the minimum transmission time of the infectious disease;

[0075] ② Indirect transmission risk: Sharing medical equipment or space used by patients diagnosed with infectious diseases without completing terminal disinfection;

[0076] ③Symptom relevance: Identify keywords containing specific symptoms in medical records or diagnoses through natural language processing.

[0077] If there are already patients with such infectious diseases among the associated patients of the infectious disease patient, the infectious disease patient who is closest to the infectious disease patient is judged to be the carrier, and the infectious disease patient is the latest patient in this transmission path. The latest transmission path is generated, and the associated patients are continued to be traced until the associated patients of the latest transmission path do not meet the infectious disease screening conditions.

[0078] S5. Push the early warning information and intervention plan to the risk node terminal, and intervene in the infectious disease patients according to the intervention plan, specifically:

[0079] An early warning intervention module is configured for the terminal device corresponding to each prevention and control node to accurately locate the position of infectious disease patients in all prevention and control nodes, and push the early warning information to the next node terminal, so as to intervene in infectious disease patients in a timely manner according to the intervention plan and effectively prevent the further spread of infectious diseases.

[0080] Among them, the risk node terminal includes the current node terminal and the next node terminal. The current node terminal is the terminal device corresponding to the prevention and control node where the infectious disease exposure has occurred, such as the doctor's workstation in the clinic where the confirmed patient is located; the next node terminal is the terminal device corresponding to the prevention and control node terminal where the transmission risk is predicted to occur, such as the doctor's workstation in the ward where the patient plans to go.

[0081] The next node terminal belongs to the subset of risk node terminals, and the judgment criteria are:

[0082] Spatial relevance: nodes located on the patient's predicted movement path;

[0083] Time sensitivity: Interventions need to be implemented within a specific time window, such as completing environmental disinfection before the patient arrives.

[0084] A server includes: one or more processors; a memory for storing one or more programs, which, when executed by the one or more processors, enables the one or more processors to implement the above-mentioned full-process infectious disease tracking and intervention method.

[0085] A storage medium stores a computer program, which, when executed by a processor, implements the above-mentioned method for tracking and intervening in the entire process of infectious diseases.

[0086] 1. The tracking and intervention system in the present invention can be integrated with the existing hospital information management system to build a dynamic monitoring network covering the patient's diagnosis and treatment process, conduct real-time tracking, real-time warning, and real-time intervention, effectively prevent the further spread of infectious diseases, and help clinicians promptly and effectively handle reports of infectious diseases, deaths, and other suspected hospital-acquired cases and clustered infectious events in the hospital, guide clinical medical staff to implement intervention measures, achieve early detection, early reporting, early isolation, and early treatment of infectious diseases, prevent cross-infection in the hospital, and solve the problem that the existing methods of tracking and tracing infectious diseases are relatively backward and prone to late reporting or missed reporting by medical staff.

[0087] 2. The tracking and intervention method of the present invention is used to track and trace the source of infectious diseases. Its calculation amount is relatively small and the positioning is more accurate, which can solve the problems of large calculation amount and inaccurate positioning in existing methods of tracking and tracing the source of infectious diseases.

[0088] The above are only specific embodiments of the present invention, but the technical features of the present invention are not limited thereto. Any simple changes, equivalent substitutions, or modifications based on the present invention to solve substantially the same technical problems and achieve substantially the same technical effects are all included in the scope of protection of the present invention.

Claims

1. A method for tracking and intervening in the whole process of infectious diseases, characterized by The steps include: S1. Obtain patient clinical data; S2. Set up prevention and control nodes and early warning windows to establish a closed loop for infectious disease monitoring; S3, constructing a spatiotemporal relationship model based on the patient clinical data obtained in step S1, wherein the spatiotemporal relationship model generates a patient relationship network based on the spatiotemporal relationship between patients; S4. Create individual cases of infectious disease patients and store their spatiotemporal routes; Input the information of infectious disease patients, locate their spatial position in the patient relationship network, and trace related patients based on this information to screen high-risk patients; S5. Push the early warning information and intervention plan to the risk node terminal, and intervene on the infectious disease patients according to the intervention plan.

2. The method for tracking and intervening in the whole process of infectious diseases according to claim 1, characterized in that: The specific method of step S1 is: obtaining the patient's clinical data from the hospital information management system, and converting the patient's clinical data into a unified data format through a data cleaning module.

3. The method for tracking and intervening in the whole process of infectious diseases according to claim 1, characterized in that: The specific method of step S2 is: set the prevention and control nodes corresponding to the patient's visit to the hospital, immediately collect, record, analyze and judge the patient's infectious disease situation at each prevention and control node, set up an early warning window in the hospital information management system for early warning, and establish a real-time tracking and real-time intervention infectious disease monitoring closed loop.

4. The method for tracking and intervening in the entire infectious disease process according to claim 1, characterized in that: The specific method for constructing the spatiotemporal relationship model in step S3 is: using all prevention and control nodes as data anchor points, the patient clinical data obtained in step S1 are cleaned and saved; outpatient treatment information data, hospitalization information data, and discharge information data are obtained from the cleaned patient clinical data; outpatient treatment information data, hospitalization information data, and discharge information data are analyzed, and patients with spatiotemporal clustering are recorded as associated patients to generate a patient relationship network.

5. The method for tracking and intervening in the whole process of infectious diseases according to claim 1, characterized in that: The specific method of step S4 is: when abnormal infectious disease case data appears, establish an infectious disease patient case, retrieve the diagnosis and treatment data of the infectious disease patient from outpatient to discharge, track the entire process of the infectious disease patient, generate a time-space route, and collect, record, and analyze it to locate the spatial position of the infectious disease patient in the patient relationship network, and judge whether the infectious disease patient's associated patients have infectious disease patients, whether the diagnosis issued by the doctor for the associated patient is related to the infectious disease, whether the test application issued by the doctor for the associated patient is related to the infectious disease, and whether the current infectious disease-related test result report determines that the associated patient is positive for the infectious disease.

6. The method for tracking and intervening in the entire infectious disease process according to claim 5, characterized in that: If there are already patients with such infectious diseases among the associated patients of the infectious disease patient, the infectious disease patient who is closest to the infectious disease patient is judged to be the carrier, and the infectious disease patient is the latest patient in this transmission path. The latest transmission path is generated, and the associated patients are continued to be traced until the associated patients of the latest transmission path do not meet the infectious disease screening conditions.

7. The method for tracking and intervening in the whole process of infectious diseases according to claim 1, characterized in that: The specific method of step S5 is: configure an early warning intervention module for the terminal device corresponding to each prevention and control node, locate the position of infectious disease patients in all prevention and control nodes, and push the early warning information to the next node terminal, and intervene in the infectious disease patients according to the intervention plan.

8. A full-process tracking and intervention system for infectious diseases, characterized by: include: Data acquisition module, used to obtain patient clinical data from the hospital information management system; A data cleaning module, used to convert the patient clinical data acquired by the data acquisition module into a unified data format and remove redundant data; A data monitoring module embedded in the hospital information management system is used to monitor the patient clinical data acquired by the data acquisition module in real time; a spatiotemporal relationship module, configured to construct a spatiotemporal relationship model based on the patient clinical data acquired by the data acquisition module, the spatiotemporal relationship model generating a patient relationship network based on the spatiotemporal relationships between patients, the spatiotemporal relationship model generating a propagation path map based on the spatiotemporal trajectories of the patients, and outputting the propagation path map to the early warning intervention module; The early warning intervention module is used to locate the terminal equipment that needs intervention based on the propagation path diagram input by the spatiotemporal relationship module, push the early warning information to the risk node terminal for intervention, and then feed back the intervention results to the spatiotemporal relationship module. The spatiotemporal relationship module optimizes the spatiotemporal relationship model based on the intervention results.

9. A server, characterized in that: The server includes: one or more processors; A memory for storing one or more programs, which, when executed by the one or more processors, enables the one or more processors to implement the infectious disease full-process tracking and intervention method as described in any one of claims 1-7.

10. A storage medium, characterized in that: The storage medium stores a computer program, which, when executed by a processor, implements the infectious disease full-process tracking and intervention method as described in any one of claims 1 to 7.

Images