CN115240869A - Intelligent infectious disease monitoring and early warning system - Google Patents
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Abstract
The invention discloses an intelligent infectious disease monitoring and early warning system, which comprises: the multi-source heterogeneous data acquisition module is used for dynamically acquiring information data of multiple sources related to infectious diseases and performing data conversion; the data processing and analyzing module is used for performing fusion analysis and processing on the obtained multi-source heterogeneous data and generating a future risk prediction result; and the early warning prompting module is used for carrying out early warning prompting according to the generated future risk prediction result and providing corresponding emergency response measures. The system has the advantages of synchronous dynamic monitoring and real-time early warning, diversified data sources, high reliability of data, strong timeliness, strong system function, high intelligent degree, multi-scale intelligent early warning and prompting and the like.
Description
Technical Field
The invention relates to the technical field of Internet, in particular to an intelligent infectious disease monitoring and early warning system.
Background
The outbreak and the prevalence of infectious diseases bring great threat to human health for a long time, and early discovery, early warning and early response are the keys of infectious disease prevention and control work, are the premise of effectively guaranteeing the physical health and life safety of people, and are also important challenges facing the public health field of each country. The existing infectious disease related monitoring and management system comprises an infectious disease network direct reporting system, an infectious disease data monitoring and processing method and a system, and the specific contents are as follows:
1.1 infectious disease network direct reporting system
According to the regulation of infectious disease prevention and treatment law of the people's republic of China, after first-diagnosis doctors of hospitals in various places receive and diagnose infectious diseases or suspected cases, an infectious disease report card is filled in seriously and reported through a network direct reporting system within a specified time, wherein class A or part of class B infectious diseases are reported within 2 hours, and other class B or class C infectious diseases are reported within 6 or 24 hours.
The system has the advantages that: the infectious disease reporting process is simple and convenient, the channel is unblocked, the speed is high, and the efficiency is high.
Defects and deficiencies: 1) The early warning capability is insufficient. Only the occurrence of an infectious case can be intuitively judged through reported information, but the system does not have the early warning function and capability on problems such as an outbreak source, risk degree, diffusion tendency and the like. 2) The degree of intelligence is not good enough. After the first or a plurality of infectious disease cases appear, experts are required to manually study and judge the development trend, risk degree and the like of the epidemic situation and decide to start an emergency plan of a corresponding grade. The human judgment and decision, if there is a mistake, may cause the risk of "insufficient prevention and control" or "excessive prevention and control". 3) The infectious disease information (data) recorded by the system is limited, and other lots of relevant or valuable information and data need to be acquired manually.
1.2 infectious disease data monitoring and processing method and system
On the basis of acquiring specific infectious disease data information including the health file, relevant data are processed and analyzed, and a set early warning value is combined to send out early warning of specific infectious diseases.
The system has the advantages that: theoretically, the method has certain infectious disease prediction function and effect.
Defects and deficiencies: 1) The prediction is only based on hospital health record data, and the coverage and prediction capability of the population are limited; 2) The outbreak source and the transmission path of the infectious diseases are complicated, the problems of the outbreak source, the diffusion situation, the risk level and the like of the infectious diseases cannot be effectively judged only by analyzing the health file data, and the early warning capability is greatly limited.
Disclosure of Invention
Therefore, the invention provides an infectious disease intelligent monitoring and early warning system, which aims to solve the problems of limited input data, insufficient early warning capability and low intelligent degree of the existing infectious disease monitoring and management system.
In order to achieve the above purpose, the invention provides the following technical scheme: an intelligent infectious disease monitoring and early warning system, comprising:
the multi-source heterogeneous data acquisition module is used for dynamically acquiring information data of multiple sources related to infectious diseases and performing data conversion;
the data processing and analyzing module is used for performing fusion analysis and processing on the obtained multi-source heterogeneous data and generating a future risk prediction result;
and the early warning prompting module is used for carrying out early warning prompting according to the generated future risk prediction result and providing corresponding emergency response measures.
Further, the multi-source heterogeneous data acquisition module is specifically configured to:
the method comprises the steps of linking an infectious disease network direct reporting system in the field of medical treatment and health through a data interface, and acquiring diagnosis information including first diagnosis time, symptoms and detection results of patients with confirmed diagnosis of infectious diseases, suspected and asymptomatic infectors, and personal information including basic medical history, age, residence place, work units, identity cards and mobile phone numbers;
the method comprises the steps that hospital management information systems at all levels are linked through data interfaces, diagnosis data containing common symptoms at the early stage of infectious diseases are obtained, networking is conducted with infectious disease prevention and control departments at all levels, and symptoms, time, space and personal information of confirmed or suspected cases of the early infectious diseases are captured in real time;
the method comprises the steps of obtaining information data which are derived from big data and comprise geography, weather, traffic, communication and environment real-time monitoring, collecting infectious disease related information data from internet activity data and reporting related suspicious information of the infectious diseases around the persons by individuals, and obtaining information data which can represent the latent diseases in the early stage.
Further, the system further comprises an app application, specifically configured to:
the method includes the steps that individual information including identity card numbers, names, sexes, ages, family member information and the like is directly collected through matched app application, and addresses which are visited in the past period of time are directly marked on an electronic map nested in the app.
Further, the data processing and analyzing module is specifically configured to:
disease outbreak rule analysis: the method carries out space and space-time clustering analysis based on the address information of the real-time case data, judges the increase of cases in which time and which places is more concentrated and more obvious than other areas, and is also helpful to divide the infectious disease occurrence and development process into different stages in time, thereby knowing the space-time aggregation characteristics of the cases in each stage.
Further, the data processing and analyzing module is specifically configured to:
and (3) dividing different levels of risk groups: establishing a contact relationship network between people by utilizing social network analysis, wherein each node represents an epidemic person, each edge represents the mutual contact relationship between two people, and the weight of each edge represents the contact mode, so that the probability of infection is presumed; analyzing a data model of the social network by using a plurality of indexes; and drawing the social network relationship graph on a map according to the address information of the epidemic people, so as to reflect the social connection among the regions.
Further, the data processing and analyzing module is specifically configured to:
and (3) defining different levels of risk areas: the infectious disease detection scheme integrating the spatial information and the nucleic acid detection technology discovers the time-space tracks of confirmed diagnoses and suspected cases of infectious diseases in real time by analyzing the signaling data of the mobile phone, can more quickly and accurately judge the potential infectious disease prevalence of each street community and divide the universe into areas with different risk levels on the basis of the time-space tracks, and therefore, the nucleic acid detection strategy is implemented according to local conditions; and associating the space-time trajectory information of the individual with the infectious disease detection result in the system according to the identification card number information, and more accurately studying and judging the infection risk of the individual.
Further, the data processing and analyzing module is specifically configured to:
identifying influence factors: and (3) integrating epidemiological survey data of the multi-source heterogeneous data individuals, and analyzing the relation between the multi-dimensional variable and the occurrence of the case.
Further, the data processing and analyzing module is specifically configured to:
predicting the future risk: by utilizing the obtained relation between the multidimensional variable and the occurrence of the case, machine learning algorithms such as a support vector machine and a random forest and deep learning algorithms such as a long-term and short-term memory neural network and a cyclic neural network are integrated, integrated multi-source heterogeneous big data are comprehensively analyzed and processed, and an analysis result including potential outbreak sources and risk factors, risk levels, development situations and countermeasures is generated through automatic operation of the system, so that early risks are effectively identified, and epidemic situation research and judgment and multi-point triggering early warning capability are comprehensively improved.
Further, the early warning prompt module is specifically configured to:
generating an electronic map containing each cell and village boundary by combining a map platform, urban interest points and user address data from a location-based service app, wherein the electronic map is used as a basic unit for prediction and early warning;
early warning lead S = S b －S a Wherein: s a The date of infection for the patient with infectious disease, S b The difference between the two days is the theoretical early warning day for the correct diagnosis date.
Further, the early warning prompt module is specifically configured to:
the adopted early warning and prompting modes comprise: carrying out acousto-optic early warning on epidemic situations; light color early warning of an electronic map of a risk area; prompting epidemic situation development situation curves in different regions; and comprehensively prompting the epidemic outbreak source, the risk level and the development trend of the global or local area, the required countermeasures and the like by a text mode.
The invention has the following advantages:
the intelligent infectious disease monitoring and early warning system provided by the invention has the following advantages:
and the dynamic monitoring and the real-time early warning are synchronous. The method comprises the steps of dynamically monitoring case information of the infectious diseases, judging risk groups, risk areas and the development situation of the infectious diseases in time, carrying out risk (area and group) early warning on local areas or universes in a monitoring range in real time, and simultaneously automatically prompting coping strategies.
2) And diversifying data sources. The collected data and information come from multiple fields, and besides health record data, the collected data and information also comprise diagnosis data and personal information of infectious disease patients, and multi-field multi-source heterogeneous data related to infection, transmission, detection, prevention and control of infectious diseases, such as geography, weather, traffic, communication and the like.
3) The data has high reliability and strong timeliness. All data are from government or industry official networks, and are real-time or up-to-date.
4) The system has stronger functions. The system has the function of networking and paralleling with the existing infectious disease network direct reporting system and the smart city platform in China, and is suitable for running in multi-stage disease prevention and control departments.
5) The intelligent degree is high. The method realizes full-intelligent operation without substantial human intervention from information acquisition, information conversion, data fusion and data processing to the output of a processing result.
6) And multi-scale intelligent early warning and prompting are realized. The information of confirmed cases, suspected cases and asymptomatic infectors is taken as breakthrough and entry points, and the information and data related to other fields are combined, so that risk groups, risk areas, risk levels, development situations and the like are intelligently predicted, early warning and prompting are automatically sent out, and effective reference is provided for the precise prevention and control work of infectious diseases and the solid and ordered promotion.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It should be apparent that the drawings in the following description are merely exemplary, and that other embodiments can be derived from the drawings provided by those of ordinary skill in the art without inventive effort.
Fig. 1 is a schematic diagram illustrating a module configuration of an infectious disease intelligent monitoring and early warning system according to embodiment 1 of the present invention;
fig. 2 is a schematic diagram of a network architecture of an infectious disease intelligent monitoring and early warning system according to embodiment 1 of the present invention;
fig. 3 is a space-time cluster diagram of cases of infectious diseases in the intelligent infectious disease monitoring and early warning system provided in embodiment 1 of the present invention;
fig. 4 is a social network relationship diagram of an epidemic involved person in the intelligent infectious disease monitoring and early warning system according to embodiment 1 of the present invention;
fig. 5 is a social network relationship map of an epidemic involved person in the intelligent infectious disease monitoring and early warning system provided in embodiment 1 of the present invention.
Detailed Description
The present invention is described in terms of particular embodiments, other advantages and features of the invention will become apparent to those skilled in the art from the following disclosure, and it is to be understood that the described embodiments are merely exemplary of the invention and that it is not intended to limit the invention to the particular embodiments disclosed. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
As shown in fig. 1 and fig. 2, the present embodiment provides an infectious disease intelligent monitoring and early warning system, which includes:
the multi-source heterogeneous data acquisition module 100 is used for dynamically acquiring information data of multiple sources related to infectious diseases and performing data conversion;
the data processing and analyzing module 200 is used for performing fusion analysis and processing on the acquired multi-source heterogeneous data and generating a future risk prediction result;
and the early warning prompting module 300 is configured to perform early warning prompting according to the generated future risk prediction result, and provide corresponding emergency response measures.
1 System data Source
The data source of the system mainly has five aspects, one is the infectious disease network direct reporting system in the medical and health field, and the related information and data comprise: diagnosis information such as first diagnosis time, symptoms and detection results of patients with confirmed infectious diseases, suspected and asymptomatic infections, and personal information such as basic medical history, age, residence, working units, identity cards and mobile phone numbers; second, the management information system of each level of hospitals contains the data of the doctor seeing a doctor of the common symptoms at the early stage of infectious diseases; thirdly, infectious disease suspicious information directly reported by app of a volunteer geographic information system; fourthly, information data such as space (geography), weather, traffic, communication, real-time detection and the like from big data; and fifthly, internet activity data (such as intensive search of related infectious disease keywords by multiple people online in a short time).
2 operating conditions of production
The method is suitable for being put into operation in multistage disease prevention and control departments, has no special requirements on environment, has the operation conditions of common electronic equipment, and only needs to have a stable 4G or 5G network.
3 government action premise
All levels of disease prevention and control departments can make the best of duty and responsibility, and measures such as effective control, medical treatment, treatment and the like are continuously taken for each infectious disease confirmed, suspected patient and asymptomatic infected person, so that the disease prevention and control departments are prevented from being used as pathogen hosts to continuously participate in virus transmission.
4 suitable for infectious diseases
The system is more suitable for dynamic monitoring and early warning of infectious diseases taking respiratory tracts and contact as main transmission ways.
The specific implementation content is as follows:
1 early warning unit setting
And combining the OpenStreetMap, the urban interest points and user address data from the location-based service app to generate an electronic map containing each cell and village boundary as a basic unit for later prediction and early warning.
2 flow reconciliation detection information acquisition
The app matched with the system can directly collect individual information such as identity card numbers, names, sexes, ages, family member information and the like through options and fill-in, and addresses which are visited within a period of time in the past are directly marked on an electronic map nested in the app, so that the problems of natural language processing in the traditional epidemiological survey report, such as non-standard address information format, invalid address information and the like, are solved.
3 analysis of disease outbreak rule
The method carries out space and space-time clustering analysis based on the address information of the real-time case data, judges the time and the local case increase more concentrated and more obvious than other regions (figure 3), and is also helpful for dividing the infectious disease occurrence and development process into different stages in time, thereby knowing the space-time aggregation characteristics of the cases in each stage.
4 different levels of risk group demarcation
The probability of infection can be inferred by constructing a contact relationship network (figure 4) between people by using social network analysis, wherein each node represents one person (epidemic person), each edge represents the mutual contact relationship between two people, and the weight of the edge represents the contact mode. The data model of the social network may be analyzed using the following, among other things: degree (1): the number of edges connected with nodes in the network is defined as a measure of the activity of the nodes, and the larger the degree of the nodes in the network is, the more people the person contacts are represented, and the more important the analysis of the infection chain is; (2) density and central potential: the overall cohesion level of the graph and how much such cohesion is organized around certain points are described separately. If the density and the central potential are high, it is indicated that the close contact or the sub-close contact of the epidemic people in the area is caused by a few people, and it is indicated that the activity of the people or the insides of the area is strong, so that support is provided for the subsequent sealing and controlling measures; (3) Defining and calculating the influence of the nodes, and further analyzing the basic characteristics of the people with larger influence, such as summarizing the occupational characteristics and frequent activity range of the people, so as to provide guidance for key attention personnel in epidemic prevention and control and provide support for accurate prevention and control; (4) identification of the coacervate subgroup: the community detection in network analysis is to identify individual communities in a complex and huge network, and people in the communities have relatively strong, direct, close, frequent or positive relationships; (5) average shortest path: the average shortest path in the network can be used for measuring the degree of closeness of interconnection between nodes in the network, and the smaller the shortest path is, the easier the association between every two nodes in the community is generated, otherwise, the harder the association is generated, so that guidance is provided for evaluating the mobility of personnel in the community and the like, and the scale (such as house isolation, building isolation or community isolation and the like) of decision-making isolation is facilitated.
In addition, the social network relationship graph can be drawn on a map according to the address information of the epidemic people, so that social connections among regions are reflected (fig. 5).
5 different grade risk area demarcation
The infectious disease detection scheme integrating the spatial information and the nucleic acid detection technology discovers the time-space tracks of confirmed and suspected cases of infectious diseases in real time by analyzing the signaling data of the mobile phone, can more quickly and accurately judge the potential infectious disease prevalence of each street community and divide the universe into areas with different risk levels based on the time-space tracks, and accordingly implements a nucleic acid detection strategy according to local conditions (for example, a single sample or mixed sample method is adopted for nucleic acid detection, the number of samples of each group of mixed samples and the like). In addition, the space-time trajectory information and the nucleic acid detection result of the individual are related in the system according to the identification number information, so that the infection risk of the individual can be accurately judged. If the result of nucleic acid detection of a certain person is positive and the recent history of close connection (secondary close), the probability of true positive is high, otherwise, the probability of false positive is high; if the result of nucleic acid detection is negative, but the close connection (secondary close connection) history exists in the recent time, the detection method needs to be replaced as appropriate for re-detection, or the detection method needs to be isolated for a short time and then the nucleic acid detection needs to be carried out again, so that the social epidemic prevention cost is reduced, and the accurate prevention and control capability is improved.
6 influence factor identification
The system can dynamically acquire data such as geography, weather, communication, traffic (railway, highway and aviation), real-time environment monitoring and the like through the data interface, acquire other early information (such as scientific literature, real-time traffic and environment monitoring, internet activity data and the like) capable of embodying latent diseases according to needs, integrate multi-source heterogeneous data, combine with individual epidemiological survey data, and analyze the relation between multi-dimensional variables and case occurrence.
7 future risk prediction
The system can be communicated with a hospital management information system, can monitor common symptoms in the early stage of infectious diseases in real time through hospital diagnosis data, can be networked with infectious disease prevention and control departments at all levels, can capture symptoms, time, space and personal information of confirmed or suspected cases of early infectious diseases in real time, and can also receive that individuals directly report related suspicious information of the infectious diseases around the individuals through a volunteer geographic information system (app). By utilizing the obtained relation between the multidimensional variables and the occurrence of the cases, machine learning algorithms such as a support vector machine and a random forest and deep learning algorithms such as a long-short term memory neural network and a cyclic neural network are integrated, the multi-source heterogeneous big data are comprehensively analyzed and processed, and an analysis result (a potential outbreak source and risk factors, a risk level, a development situation, countermeasures and the like) is generated by automatic operation of a system, so that the early risk is effectively identified, and the epidemic situation research and judgment and multi-point triggering early warning capability are comprehensively improved.
8 early warning and prompting mode selection
1. Carrying out acousto-optic early warning on epidemic situations;
2. light color early warning of an electronic map of a risk area;
3. prompting epidemic situation development situation curves in different regions;
4. and comprehensively prompting the epidemic outbreak source, the risk level and the development trend of the global or local area, the required countermeasures and the like by a text mode.
The functional advantages of the present system are as follows:
1) And the dynamic monitoring and the real-time early warning are synchronous. The method comprises the steps of dynamically monitoring case information of the infectious diseases, judging risk groups, risk areas and the development situation of the infectious diseases in time, carrying out risk (area and group) early warning on local areas or universes in a monitoring range in real time, and simultaneously automatically prompting coping strategies.
2) And diversifying data sources. The collected data and information come from multiple fields, and besides health record data, the collected data and information also comprise diagnosis data and personal information of infectious disease patients, and multi-field multi-source heterogeneous data related to infection, transmission, detection, prevention and control of infectious diseases, such as geography, weather, traffic, communication and the like.
3) The reliability of the data is high, and the timeliness is strong. All data are from government or industry official networks, and are real-time or up-to-date.
4) The system has stronger functions. The system has the function of networking and paralleling with the existing infectious disease network direct reporting system and the smart city platform in China, and is suitable for running in multi-stage disease prevention and control departments.
5) The intelligent degree is high. The full-intelligent operation is realized from information acquisition, information conversion, data fusion, data processing and processing result output without substantial human intervention.
6) And multi-scale intelligent early warning and prompting are realized. The information of confirmed cases, suspected cases and asymptomatic infectors is taken as breakthrough and entry points, and the information and data related to other fields are combined, so that risk groups, risk areas, risk levels, development situations and the like are intelligently predicted, early warning and prompting are automatically sent out, and effective reference is provided for the precise prevention and control work of infectious diseases and the solid and ordered promotion.
The system follows the concept of 'dynamic monitoring and synchronous early warning', and as long as the information of newly added confirmed cases, suspected cases and asymptomatic infectors is monitored, the system intelligently processes, analyzes, inspects, identifies and pre-judges new risk units and risk groups, synchronously sends out early warning and prompts, and provides reference and support for proper strategy and accurate prevention and control.
Early warning lead (expressed by S, unit: day), S = S b －S a Wherein: s. the a The date of infection for the patient with infectious disease, S b The difference between the two days is the theoretical early warning day for the correct diagnosis date. The early warning value lies in prediction in advance, accurate strategy, high-efficient prevention and control, effectively ensures the health and life safety of people, and obtains the maximum benefit with the minimum cost.
Through infectious disease early warning and risk prompt, remind people to obey prevention and control regulations, strengthen self-protection, prevent infection, block transmission, have great significance too.
Although the invention has been described in detail above with reference to a general description and specific examples, it will be apparent to one skilled in the art that modifications or improvements may be made thereto based on the invention. Accordingly, it is intended that all such modifications and alterations be included within the scope of this invention as defined in the appended claims.
Claims (10)
1. An intelligent infectious disease monitoring and early warning system, which is characterized by comprising:
the multi-source heterogeneous data acquisition module is used for dynamically acquiring information data of multiple sources related to infectious diseases and performing data conversion;
the data processing and analyzing module is used for performing fusion analysis and processing on the obtained multi-source heterogeneous data and generating a future risk prediction result;
and the early warning prompting module is used for carrying out early warning prompting according to the generated future risk prediction result and providing corresponding emergency response measures.
2. An intelligent infectious disease monitoring and early warning system according to claim 1, wherein the multi-source heterogeneous data acquisition module is specifically configured to:
the method comprises the steps of linking an infectious disease network direct reporting system in the field of medical treatment and health through a data interface, and acquiring diagnosis information including first diagnosis time, symptoms and detection results of patients with confirmed diagnosis of infectious diseases, suspected and asymptomatic infectors, and personal information including basic medical history, age, residence place, work units, identity cards and mobile phone numbers;
the method comprises the steps that hospital management information systems at all levels are linked through data interfaces, diagnosis data containing common symptoms at the early stage of infectious diseases are obtained, networking is conducted with infectious disease prevention and control departments at all levels, and symptoms, time, space and personal information of confirmed or suspected cases of the early infectious diseases are captured in real time;
the method comprises the steps of obtaining information data which are from big data and comprise geography, weather, traffic, communication and environment real-time monitoring, collecting information data related to infectious diseases from internet activity data, reporting suspicious information related to the infectious diseases around the persons by the persons, and obtaining information data which can reflect the latent diseases in the early stage.
3. An intelligent infectious disease monitoring and warning system as claimed in claim 1, wherein the system further comprises an app application, specifically configured to:
the method includes the steps that individual information including identity numbers, names, sexes, ages, family member information and the like is directly collected through a matched app application, and addresses which are visited in the past period of time are directly marked on an electronic map nested in the app.
4. An intelligent infectious disease monitoring and warning system as claimed in claim 1, wherein the data processing and analyzing module is specifically configured to:
disease outbreak rule analysis: the method carries out space and space-time clustering analysis based on the address information of the real-time case data, judges the increase of cases in which time and which places is more concentrated and more obvious than other areas, and is also helpful to divide the infectious disease occurrence and development process into different stages in time, thereby knowing the space-time aggregation characteristics of the cases in each stage.
5. An intelligent infectious disease monitoring and warning system as claimed in claim 1, wherein the data processing and analyzing module is specifically configured to:
and (3) dividing different levels of risk groups: establishing a contact relationship network between people by utilizing social network analysis, wherein each node represents an epidemic person, each edge represents the mutual contact relationship between two people, and the weight of each edge represents the contact mode, so that the probability of infection is presumed; analyzing a data model of the social network by using a plurality of indexes; and drawing the social network relationship graph on a map according to the address information of the epidemic people, so as to reflect the social connection among the regions.
6. An intelligent infectious disease monitoring and warning system as claimed in claim 1, wherein the data processing and analyzing module is specifically configured to:
and (3) defining different levels of risk areas: the infectious disease detection scheme integrating the spatial information and the nucleic acid detection technology discovers the time-space tracks of confirmed diagnoses and suspected cases of infectious diseases in real time by analyzing the signaling data of the mobile phone, can more quickly and accurately judge the potential infectious disease prevalence of each street community and divide the universe into areas with different risk levels on the basis of the time-space tracks, and therefore, the nucleic acid detection strategy is implemented according to local conditions; and associating the space-time trajectory information of the individual with the infectious disease detection result in the system according to the identification card number information, and more accurately studying and judging the infection risk of the individual.
7. An intelligent infectious disease monitoring and warning system as claimed in claim 1, wherein the data processing and analyzing module is specifically configured to:
identifying influence factors: and (3) integrating epidemiological survey data of the multi-source heterogeneous data individuals, and analyzing the relation between the multi-dimensional variable and the occurrence of the case.
8. An intelligent infectious disease monitoring and pre-warning system as claimed in claim 7, wherein the data processing and analyzing module is specifically configured to:
predicting the future risk: by utilizing the obtained relation between the multidimensional variable and the occurrence of the case, machine learning algorithms such as a support vector machine and a random forest and deep learning algorithms such as a long-term and short-term memory neural network and a cyclic neural network are integrated, integrated multi-source heterogeneous big data are comprehensively analyzed and processed, and an analysis result including potential outbreak sources and risk factors, risk levels, development situations and countermeasures is generated through automatic operation of the system, so that early risks are effectively identified, and epidemic situation research and judgment and multi-point triggering early warning capability are comprehensively improved.
9. An intelligent infectious disease monitoring and warning system as claimed in claim 1, wherein the warning module is specifically configured to:
generating an electronic map containing each cell and village boundary by combining a map platform, urban interest points and user address data from a location-based service app, wherein the electronic map is used as a basic unit for prediction and early warning;
early warning lead S = S b －S a Wherein: s a The date of infection for the patient with infectious disease, S b The difference between the two days is the theoretical early warning days for the confirmed diagnosis date.
10. An intelligent infectious disease monitoring and early warning system as claimed in claim 1, wherein the early warning prompt module is specifically configured to:
the adopted early warning and prompting modes comprise: carrying out acousto-optic early warning on epidemic situations; light color early warning of an electronic map of a risk area; prompting epidemic situation development situation curves in different regions; and comprehensively prompting the epidemic outbreak source, the risk level and the development trend of the global or local area, the required countermeasures and the like by a text mode.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115631869A (en) * | 2022-11-28 | 2023-01-20 | 北京理工大学 | Construction method of infectious disease prediction model |
| CN116705340A (en) * | 2023-04-07 | 2023-09-05 | 中南大学湘雅三医院 | Public health intelligent monitoring system and method based on blockchain |
| CN117174332A (en) * | 2023-05-25 | 2023-12-05 | 江苏瀚云医疗信息技术有限公司 | Infectious disease monitoring and early warning system and method based on multi-source data |
| CN117877753A (en) * | 2024-03-12 | 2024-04-12 | 江南大学附属医院 | Pandemic monitoring method, system, equipment and medium based on multivariate data |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115631869A (en) * | 2022-11-28 | 2023-01-20 | 北京理工大学 | Construction method of infectious disease prediction model |
| CN115631869B (en) * | 2022-11-28 | 2023-05-05 | 北京理工大学 | Method for constructing infectious disease prediction model |
| CN116705340A (en) * | 2023-04-07 | 2023-09-05 | 中南大学湘雅三医院 | Public health intelligent monitoring system and method based on blockchain |
| CN116705340B (en) * | 2023-04-07 | 2024-02-02 | 中南大学湘雅三医院 | Public health intelligent monitoring system and method based on blockchain |
| CN117174332A (en) * | 2023-05-25 | 2023-12-05 | 江苏瀚云医疗信息技术有限公司 | Infectious disease monitoring and early warning system and method based on multi-source data |
| CN117877753A (en) * | 2024-03-12 | 2024-04-12 | 江南大学附属医院 | Pandemic monitoring method, system, equipment and medium based on multivariate data |
| CN117877753B (en) * | 2024-03-12 | 2024-05-17 | 江南大学附属医院 | Pandemic monitoring method, system, equipment and medium based on multivariate data |
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