CN111403049A - Epidemic disease prediction early warning management system - Google Patents
Epidemic disease prediction early warning management system Download PDFInfo
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- CN111403049A CN111403049A CN202010223427.3A CN202010223427A CN111403049A CN 111403049 A CN111403049 A CN 111403049A CN 202010223427 A CN202010223427 A CN 202010223427A CN 111403049 A CN111403049 A CN 111403049A
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- 201000010099 disease Diseases 0.000 title abstract description 7
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 title abstract description 7
- 238000004458 analytical method Methods 0.000 claims abstract description 15
- 238000012544 monitoring process Methods 0.000 claims abstract description 15
- 238000013075 data extraction Methods 0.000 claims abstract description 4
- 238000012545 processing Methods 0.000 claims abstract description 4
- 210000002966 serum Anatomy 0.000 claims abstract description 4
- 238000000034 method Methods 0.000 claims description 42
- 241000700605 Viruses Species 0.000 claims description 28
- 239000000427 antigen Substances 0.000 claims description 17
- 102000036639 antigens Human genes 0.000 claims description 17
- 108091007433 antigens Proteins 0.000 claims description 17
- 206010022000 influenza Diseases 0.000 claims description 14
- 229960005486 vaccine Drugs 0.000 claims description 14
- 238000010276 construction Methods 0.000 claims description 5
- 238000011161 development Methods 0.000 claims description 4
- 230000002776 aggregation Effects 0.000 claims description 3
- 238000004220 aggregation Methods 0.000 claims description 3
- 230000007613 environmental effect Effects 0.000 claims description 2
- 238000007619 statistical method Methods 0.000 claims description 2
- 238000013480 data collection Methods 0.000 claims 1
- 230000002265 prevention Effects 0.000 description 6
- 208000035473 Communicable disease Diseases 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 3
- 230000007246 mechanism Effects 0.000 description 3
- 108090000623 proteins and genes Proteins 0.000 description 3
- 102000004169 proteins and genes Human genes 0.000 description 3
- 108010061514 sialic acid receptor Proteins 0.000 description 3
- 238000004088 simulation Methods 0.000 description 3
- 208000024891 symptom Diseases 0.000 description 3
- 230000027645 antigenic variation Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000002708 enhancing effect Effects 0.000 description 2
- 206010003757 Atypical pneumonia Diseases 0.000 description 1
- 241000315672 SARS coronavirus Species 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 208000015181 infectious disease Diseases 0.000 description 1
- 230000005180 public health Effects 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 241000712461 unidentified influenza virus Species 0.000 description 1
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/80—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for detecting, monitoring or modelling epidemics or pandemics, e.g. flu
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/25—Integrating or interfacing systems involving database management systems
- G06F16/254—Extract, transform and load [ETL] procedures, e.g. ETL data flows in data warehouses
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
- G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
- G16B40/00—ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
Abstract
The invention discloses an epidemic prediction early warning management system, which comprises a data layer, a platform layer, a service layer and a display layer, wherein the data layer comprises data acquisition, data processing, data loading, data sending, ET L data extraction, etiology and monitoring information data, epidemic disease epidemic analysis data, laboratory data, environment and serum monitoring data and sequence data.
Description
Technical Field
The invention relates to the technical field of epidemic disease early warning, in particular to an epidemic disease prediction early warning management system.
Background
Since the 21 st century, epidemic situations of infectious diseases, public health emergencies, natural disasters and the like continuously appear in various countries in the world. Large-scale atypical pneumonia which erupts in the world in 2003 brings great panic to people, and because corresponding detection, prevention and early warning means for novel SARS virus are lacked, the information collection of cases lacks sufficient timeliness, and first-hand information cannot be provided for governments and various monitoring departments comprehensively and rapidly, thereby causing serious lag in prevention, control and prevention decision. The A-type H1N1 outbreak in 2009 and the H7N9 avian influenza virus outbreak in 2013 bring serious influence on the daily life of people.
The prior art has the defects of high epidemic situation misstatement rate and inaccurate prediction effect: the factors influencing the epidemic trend of the infectious diseases are complex and changeable, and most of the factors use the data of the legal infectious disease report system, and the data using factors such as weather, environment and the like are few, so that the problems of integrity and reliability exist, and intelligent screening of vaccine strains is lacked.
Disclosure of Invention
The invention aims to provide an epidemic disease prediction and early warning management system to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme: the utility model provides a epidemic prediction early warning management system, includes data layer, platform layer, service layer and show layer, the output on data layer and the input signal connection on platform layer, the output on platform layer and the input signal connection on service layer, the output on service layer and the input signal connection on show layer.
Preferably, the data layer comprises data acquisition, data processing, data loading, data sending, ET L data extraction, etiology and monitoring information data, epidemiological analysis data, laboratory data, environmental and serum monitoring data and sequence data.
Preferably, the platform layer includes unified user management, unified authority management, unified component management, unified data call, business process management, unified log management, unified interface service, and unified monitoring management.
Preferably, the service layer internally comprises a method library, a model library, data query and a thematic application.
Preferably, the method library comprises an open source tool method and an autonomous development tool, the open source tool method comprises a sequence comparison method, a sequence clustering method, a construction evolutionary tree method, a statistical analysis method and an epidemic analysis method, and the autonomous development tool comprises a structure model construction method, an epitope site analysis method, an antigen distance prediction method, an antigen class analysis method and a virus hazard prediction method.
Preferably, the model library comprises an antigen variation relation prediction model, a quantitative antigen relation prediction model, a vaccine strain recommendation model, a virus hazard prediction model and a strain receptor and nature prediction model.
Preferably, the data query comprises report query and topic query, and the topic application comprises influenza epidemiology analysis, influenza epidemiology prediction early warning and automatic vaccine recommendation.
Preferably, the inside of the display layer comprises login authentication, aggregation display, personalized customization, a cockpit, graphic display and report forms.
Compared with the prior art, the invention has the beneficial effects that:
(1) according to the method, a series of potential vaccine strains are recommended in real time through prediction of antigen variation conditions of new viruses and epidemic conditions of the new viruses in a group by a vaccine strain recommendation model, and through a virus hazard prediction model: the potential hazard under the virus epidemic situation is predicted from a strain sequence, and a calculation model of the binding capacity between the strain HA protein and different host sialic acid receptors is established through a strain receptor affinity prediction model to predict the receptor affinity of the strain;
(2) the invention enhances the emergency treatment and comprehensive prevention and control capability of new outbreak epidemic virus through etiology and monitoring information data and epidemiological analysis data, integrates advanced prediction models and algorithms, and realizes epidemic molecular variation simulation and epidemic vaccine strain full-line automatic recommendation;
(3) the invention builds a complete business theme model by covering eight themes of virus, environment, host, mechanism, symptom, measure, event and project, thereby ensuring the accuracy of prediction and early warning.
Drawings
FIG. 1 is a system architecture diagram of the present invention;
fig. 2 is a service model diagram of the present invention.
In the figure: 1 data layer, 2 platform layer, 3 service layer and 4 display layer.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. 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.
The invention provides a technical scheme that the epidemic prediction early warning management system comprises a data layer 1, a platform layer 2, a service layer 3 and a display layer 4, wherein the display layer 4 comprises login authentication, aggregation display, personalized customization, a cockpit, graph display and a report form format, the output end of the data layer 1 is in signal connection with the input end of the platform layer 2, the data layer 1 comprises data acquisition, data processing, data loading, data sending, ET L data extraction, etiology and monitoring information data, epidemic disease epidemic analysis data, laboratory data, environment and serum monitoring data and sequence data, the output end of the platform layer 2 is in signal connection with the input end of the service layer 3, the platform layer 2 comprises unified user management, unified authority management, unified assembly management, unified data calling, business process management, unified log management, unified interface service and monitoring management, the output end of the service layer 3 is in signal connection with the input end of the display layer 4, the service layer 3 comprises a method library, a model library, a data query and application method for unified data, a service library, a method comprises an antigen sequence prediction and a virus classification prediction model, an antigen sequence prediction and a virus classification prediction model, an antigen classification and an antigen classification prediction model, an influenza prediction method, an antigen classification and an influenza prediction model construction method, an influenza classification method, an antigen classification and an influenza prediction method, an influenza classification method, an influenza prediction method, an antigen classification method, an influenza prediction model, an influenza prediction method, a method and an influenza classification method are included a method, a method are included in an influenza classification method, a method for.
The working principle is as follows: when the method is used, the vaccine strain recommendation model can recommend a series of potential vaccine strains in real time for predicting the antigenic variation condition of a new virus and the epidemic condition of the new virus in a group, and the virus hazard prediction model is used for: the method is characterized by starting from a strain sequence, predicting potential hazard under the virus epidemic condition, establishing a calculation model of the binding capacity between strain HA protein and different host sialic acid receptors through a strain receptor affinity prediction model, predicting the receptor affinity of the strain, enhancing the emergency treatment and comprehensive prevention and control capacity of new emergent epidemic virus through etiology and monitoring information data and epidemiology analysis data, integrating advanced prediction models and algorithms, realizing epidemic molecular variation simulation and epidemic vaccine strain full-line automatic recommendation, covering eight subjects of virus, environment, host, mechanism, symptom, measure, event and project, building a complete business subject model, and ensuring the accuracy of prediction and early warning.
In conclusion, the invention recommends a series of potential vaccine strains in real time for predicting the antigenic variation condition of a new virus and the epidemic condition of the new virus in a group through a vaccine strain recommendation model, and through a virus hazard prediction model: the method is characterized by comprising the steps of predicting potential hazard under the virus epidemic situation from a virus strain sequence, establishing a calculation model of the binding capacity between a virus strain HA protein and different host sialic acid receptors through a virus strain receptor affinity prediction model, predicting the receptor affinity of the virus strain, enhancing the emergency treatment and comprehensive prevention and control capacity of new emergent epidemic viruses through etiology and monitoring information data and epidemiological analysis data, integrating advanced prediction models and algorithms, realizing epidemic molecular variation simulation and epidemic vaccine strain full-line automatic recommendation, and building a complete business topic model by covering eight topics of viruses, environments, hosts, mechanisms, symptoms, measures, events and projects to ensure the accuracy of prediction and early warning.
Claims (8)
1. An epidemic prediction early warning management system is characterized in that: including data layer (1), platform layer (2), service layer (3) and show layer (4), the output of data layer (1) and the input signal connection of platform layer (2), the output of platform layer (2) and the input signal connection of service layer (3), the output of service layer (3) and the input signal connection of show layer (4).
2. The epidemic prediction early warning management system according to claim 1, wherein the data layer (1) comprises data collection, data processing, data loading, data sending, ET L data extraction, etiology and monitoring information data, epidemic analysis data, laboratory data, environmental and serum monitoring data and sequence data.
3. The epidemic prediction alert management system of claim 1, wherein: the platform layer (2) comprises unified user management, unified authority management, unified component management, unified data calling, business process management, unified log management, unified interface service and unified monitoring management.
4. The epidemic prediction alert management system of claim 1, wherein: the service layer (3) internally comprises a method library, a model library, data query and thematic application.
5. The epidemic prediction alert management system of claim 4, wherein: the method library comprises an open source tool method and an independent development tool, wherein the open source tool method comprises a sequence comparison method, a sequence clustering method, an evolutionary tree construction method, a statistical analysis method and an epidemic analysis method, and the independent development tool comprises a structure model construction method, an antigen epitope site analysis method, an antigen distance prediction method, an antigen class analysis method and a virus hazard prediction method.
6. The epidemic prediction alert management system of claim 4, wherein: the model library comprises an antigen variation relation prediction model, a quantitative antigen relation prediction model, a vaccine strain recommendation model, a virus hazard prediction model and a strain receptor and nature prediction model.
7. The epidemic prediction alert management system of claim 4, wherein: the data query comprises report query and topic query, and the topic application comprises influenza epidemic analysis, influenza epidemic prediction early warning and automatic vaccine recommendation.
8. The epidemic prediction alert management system of claim 1, wherein: the display layer (4) comprises login authentication, aggregation display, personalized customization, a cockpit, graphic display and a report form.
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| CN202010223427.3A CN111403049A (en) | 2020-03-26 | 2020-03-26 | Epidemic disease prediction early warning management system |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111899893A (en) * | 2020-09-29 | 2020-11-06 | 南京汉卫公共卫生研究院有限公司 | Infectious disease early warning decision platform system |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1881227A (en) * | 2006-05-16 | 2006-12-20 | 中国人民解放军第三军医大学 | Intelligent analytical model technology for diagnosing epidemic situation and classifying harmfulness degree of contagious disease |
| CN101847179A (en) * | 2010-04-13 | 2010-09-29 | 中国疾病预防控制中心病毒病预防控制所 | Method for predicting flu antigen through model and application thereof |
| CN102713914A (en) * | 2009-10-19 | 2012-10-03 | 提拉诺斯公司 | Integrated health data capture and analysis system |
| CN106709252A (en) * | 2016-12-26 | 2017-05-24 | 重庆星空云医疗科技有限公司 | Intelligent decision-making assistance system for predicting, diagnosing, treating and controlling hospital infection |
-
2020
- 2020-03-26 CN CN202010223427.3A patent/CN111403049A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1881227A (en) * | 2006-05-16 | 2006-12-20 | 中国人民解放军第三军医大学 | Intelligent analytical model technology for diagnosing epidemic situation and classifying harmfulness degree of contagious disease |
| CN102713914A (en) * | 2009-10-19 | 2012-10-03 | 提拉诺斯公司 | Integrated health data capture and analysis system |
| CN101847179A (en) * | 2010-04-13 | 2010-09-29 | 中国疾病预防控制中心病毒病预防控制所 | Method for predicting flu antigen through model and application thereof |
| CN106709252A (en) * | 2016-12-26 | 2017-05-24 | 重庆星空云医疗科技有限公司 | Intelligent decision-making assistance system for predicting, diagnosing, treating and controlling hospital infection |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111899893A (en) * | 2020-09-29 | 2020-11-06 | 南京汉卫公共卫生研究院有限公司 | Infectious disease early warning decision platform system |
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