Animal epidemic prevention and control flow regulation system and method in big data scene

Abstract

The invention is applied to the technical field of animal epidemic prevention and control, and particularly discloses an animal epidemic prevention and control flow scheduling system and method in a big data scene, and the system comprises a central computer, a data collection module, a data processing module, a flow scheduling traceability module and an analysis and evaluation module. According to the animal epidemic prevention and control flow regulation system and method in the big data scene, the central computer is connected with the farm, the veterinarian, the animal transaction market and the epidemic prevention department through the network, the central computer is used as a data interaction center, all nodes can share information in real time, the working efficiency of the system is improved, and the workload of the system is reduced. Data of animal body temperature, feed intake, water intake, historical treatment, epidemic disease history and the like are respectively acquired through data acquisition sub-modules arranged in a livestock farm, a veterinary clinic, an animal trading market and an epidemic prevention department, and are quickly transmitted to a central computer for processing through a network.

Description

Technical Field

[0001] The present invention relates to the technical field of animal epidemic prevention and control, and specifically to an animal epidemic prevention and control epidemiological investigation system and method in the big data scenario. Background Art

[0002] Animal epidemic prevention and control refers to a series of measures taken to prevent, control and eradicate the occurrence, transmission and prevalence of animal infectious diseases, parasitic diseases and other epidemics, to ensure animal health and the safety of livestock production, and to maintain public health safety and ecological balance. Among them, the use of epidemiological investigation can provide a scientific basis for animal epidemic prevention and control strategies. Epidemiological investigation refers to the use of epidemiological methods for investigation and research, mainly used to study the distribution of diseases, health and health events and their determining factors.

[0003] At present, traditional animal epidemic epidemiological investigation methods mainly rely on manual operations, mainly paper records and manual statistical analysis. Therefore, the information collection efficiency is low, and it is often impossible to obtain comprehensive and accurate epidemic-related information in a timely manner. The accuracy of the data is easily affected by human factors, resulting in recording errors or omissions, and it is difficult to quickly mine key information from massive data for epidemic tracing and prevention and control decision-making. Summary of the Invention

[0004] The purpose of the present invention is to provide an animal epidemic prevention and control epidemiological investigation system and method in the big data scenario to solve the problems raised in the above background art that the epidemiological investigation of animal epidemic prevention and control relies on manual operations with low information collection efficiency and the data accuracy is easily affected by human factors.

[0005] To achieve the above purpose, the present invention provides the following technical solutions: an animal epidemic prevention and control epidemiological investigation system and method in the big data scenario, including a central computer, a data collection module, a data processing module, an epidemiological investigation and tracing module, and an analysis and evaluation module. The central computer is respectively connected to the data collection module, the data processing module, the epidemiological investigation and tracing module, and the analysis and evaluation module. The central computer is connected bidirectionally with the computers of farms, veterinarians, animal trading markets, and epidemic prevention departments through the network, forming a network connection relationship centered on the central computer with farms, veterinarians, animal trading markets, and epidemic prevention departments interconnected; Preferably, the data collection module is respectively provided with data collection sub-modules in farms, veterinary clinics, animal trading markets and epidemic prevention departments. The data collection sub-modules are connected to the data collection module through a network. The data collection sub-module in the farm is provided with sensors, and the sensors in the farm conduct real-time monitoring on the animals in the farm to collect the body temperature data, feed intake data and drinking water data of the animals. The data collection sub-module in the veterinary clinic is connected to the electronic medical record system of the clinic, and the data collection sub-module in the veterinary clinic collects the historical medical treatment data of animals, the sources and destinations of the treated animals. The data collection sub-module in the animal trading market collects the species quantity data of the traded animals, the source data of the traded animals and the destination data of the traded animals. The data collection sub-module in the epidemic prevention department is connected to the file management system to collect the data information of historical animal epidemics, including the name types of the epidemics, the time and place of the occurrence of the epidemics, and the spread range of the epidemics.

[0006] By adopting the above technical solution, the data collection module can be used to collect various animal data.

[0007] Preferably, the data processing module includes a data storage part and a data analysis part. The data storage part receives a large amount of data from the data collection module for storage. The data analysis part analyzes and processes the data, and inputs the data for further analysis into the flow investigation and traceability module after preliminary processing.

[0008] By adopting the above technical solution, the data processing module receives the data from the data collection module for storage and analysis.

[0009] Preferably, based on a large amount of animal data in the data processing module, the flow investigation and traceability module extracts animal trading information and animal transportation information, generates the transportation tracks of animals and the intersection points between the animal transportation tracks, and combines big data analysis technology to comprehensively trace the farms, transportation routes and trading information around the place where the animal epidemic occurs to determine the source of the epidemic spread.

[0010] By adopting the above technical solution, the flow investigation and traceability module can comprehensively trace the animal epidemic according to the animal data information to determine the source of the epidemic spread.

[0011] Preferably, the analysis and evaluation module includes a risk assessment model and an epidemic prevention measure output part. The construction process of the risk assessment model is as follows: Extract the occurrence records of historical epidemics from the data collected by the data collection module, including epidemic data and animal information data. The epidemic data includes the onset time, location, animal species, number of diseased animals and number of dead animals; the animal information data includes animal breeding density, animal trading data and animal movement data; Based on the principles of infectious disease transmission dynamics and using the decision tree model as the basis, a risk assessment model for animal diseases is constructed; The disease data and animal information data are input into the risk assessment model for animal diseases, and the risk assessment model is trained and the parameters are corrected.

[0012] Adopting the above technical solution, the risk assessment model constructed in the analysis and evaluation module can be used to analyze the risk of animal diseases.

[0013] Preferably, the epidemic prevention measure output part generates epidemic prevention measures according to the output result of the risk assessment model, including determining the scope of the epidemic area, the number of diseased animals to be culled, and the disinfected area. The epidemic prevention measures are output to the receiving terminals of the farms, veterinarians, animal trading markets, and epidemic prevention departments respectively through the central computer.

[0014] Adopting the above technical solution, the epidemic prevention measure output part can generate epidemic prevention measures according to the output result of the risk assessment model and according to the output result of the model.

[0015] Preferably, Step 1: Use the data collection module to collect data from farms, veterinarians, trading markets, and epidemic prevention departments to obtain the physiological status of animals, environmental parameters, and animal location movement information, etc.; Step 2: Use the data storage part in the data processing module to store the collected animal information and analyze the animal data information; Step 3: Use the data analysis part in the data processing module to analyze the data. According to the trading information and animal transportation information in the trading market, analyze the contact relationship between animals, the intersection points of transportation trajectories, conduct epidemiological investigation and traceability of animals, and find out possible epidemic transmission chains and potential risk factors through association analysis; Step 4: According to the results of the epidemiological investigation and traceability of animals, combine the geographic information system (GIS) technology and the principles of infectious disease transmission to construct an animal epidemic risk assessment model, use the model to generate the risk assessment results of animal epidemics, and output suggestions for animal prevention and control measures.

[0016] Adopting the above technical solution, based on the collection and processing of animal data, a risk assessment model can be constructed to assess the risk of animal epidemics.

[0017] Compared with the prior art, the beneficial effects of the present invention are: the animal epidemic prevention and control epidemiological investigation system and method in the big data scenario: 1. In the present invention, the central computer is interconnected with farms, veterinarians, animal trading markets, and epidemic prevention departments through the network. Taking the central computer as the center of data interaction enables each node to share information in real time, improving the working efficiency of the system. Through the data acquisition sub-modules set in farms, veterinary clinics, animal trading markets, and epidemic prevention departments, data such as animal body temperature, food intake, water intake, historical medical treatment, and disease history are collected respectively, and quickly transmitted to the central computer through the network for processing, enhancing the speed and comprehensiveness of information collection. Compared with traditional manual statistics, it avoids recording errors and omissions caused by human factors, ensuring the accuracy and reliability of data; 2. In the present invention, based on a large amount of animal data information collected, the flow investigation and traceability module is used to extract animal trading information and animal transportation information, generate animal transportation trajectories and intersection point data. It can comprehensively trace relevant information around the epidemic occurrence area in combination with big data analysis technology, accurately lock the source of the epidemic spread. At the same time, the analysis and evaluation module can be used to construct a risk assessment model. After inputting the collected data into the risk assessment model for training and correcting the model, scientific epidemic prevention measures including determining the scope of the epidemic area, the number of culled infected animals, and the disinfected area are generated according to the output results, and timely output to each relevant department, providing data support for animal epidemic prevention and control. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a schematic diagram of the system composition structure of the present invention; Figure 2 It is a schematic diagram of the computer connection structure of the present invention; Figure 3 It is a schematic diagram of the animal transportation trajectory structure of the present invention; Figure 4 It is a schematic diagram of the method flow structure of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0020] Please refer to Figures 1 - 4 , the present invention provides a technical solution: an animal epidemic prevention and control flow investigation system and method in a big data scenario.

[0021] The central computer is respectively connected to the data acquisition module, the data processing module, the epidemiological investigation and tracing module, and the analysis and evaluation module. The central computer is connected bidirectionally to the computers of the farms, veterinarians, animal trading markets, and epidemic prevention departments through the network, forming a network connection relationship centered on the central computer, with the farms, veterinarians, animal trading markets, and epidemic prevention departments interconnected with each other; As Figure 2 shown, during the use of this system, the farms, veterinarians, animal trading markets, and epidemic prevention departments are respectively connected to the central computer through the network. Each node uses the central computer as the center of interaction, enabling each node to share information in real time and promoting collaborative work among the nodes.

[0022] The data acquisition module sets data acquisition sub-modules in the farms, veterinary clinics, animal trading markets, and epidemic prevention departments respectively. The data acquisition sub-modules are connected to the data acquisition module through the network. The data acquisition sub-module in the farm sets sensors, and the sensors in the farm monitor the animals in the farm in real time to collect the body temperature data, feed intake data, and water intake data of the animals. The data acquisition sub-module in the veterinary clinic is connected to the electronic medical record system of the clinic, and the data acquisition sub-module in the veterinary clinic collects the historical medical treatment data of the animals, the sources and destinations of the treated animals. The data acquisition sub-module in the animal trading market collects the species quantity data of the traded animals, the source data of the traded animals, and the destination data of the traded animals. The data acquisition sub-module in the epidemic prevention department is connected to the file management system to collect the data information of historical animal diseases, including the name types of the diseases, the time and location of the disease occurrence, and the spread range of the diseases; As Figure 1 shown, during the use of the system, the data acquisition module at the central computer sets data acquisition sub-modules in the farms, veterinary clinics, animal trading markets, and epidemic prevention departments respectively to collect different data information. Among them, the farm collects the body temperature data, feed intake data, and water intake data of the animals, so as to monitor in real time whether there are abnormal data in the animals, and thus monitor the disease situation of the animals. The veterinary clinic collects the historical medical treatment data of the animals and the sources and destinations of the treated animals, so as to understand the health history and disease history of the animals. When the animal has health problems again, the historical medical treatment data of the animal can be referred to to quickly understand the past disease situation of the animal, which helps to accurately diagnose the current disease, avoid misdiagnosis and missed diagnosis, and can also quickly match the disease situation according to the medical treatment situation of the animal. Thus, in the case of the recurrence of diseases, it can be quickly discovered. The animal trading market can collect the species quantity data of the traded animals, the source data of the traded animals, and the destination data of the traded animals. When an animal epidemic occurs, the source of the animal can be traced through the data of the animal trading market, and whether there are risk factors for the spread of the epidemic at the source, and the flowing areas of the animals can be notified in time for epidemic monitoring and prevention and control to prevent the further spread of the epidemic.

[0023] The data processing module includes a data storage part and a data analysis part. The data storage part receives a large amount of data from the data acquisition module for storage. The data analysis part analyzes and processes the data. After preliminary processing of the data, it is input into the epidemiological investigation and traceability module for further analysis. Based on a large amount of animal data in the data processing module, the epidemiological investigation and traceability module extracts animal trading information and animal transportation information, generates the transportation tracks of animals and the intersection points between animal transportation tracks, and combines big data analysis technology to comprehensively trace the farms, transportation routes, and trading information around the animal epidemic occurrence area to determine the source of the epidemic spread. As Figure 1 and Figure 3 shown, the animal data collected by the data acquisition module is input into the data processing module for storage, and the data analysis part is used to analyze and process the data. The data analysis part extracts the animal trading information and animal transportation information in the animal data, and generates the transportation tracks of animals and the intersection points between animal transportation tracks based on this data. Combining big data analysis technology, when an epidemic occurs, the farms, transportation routes, trading and other information around the epidemic occurrence area are comprehensively traced to determine the source of the epidemic spread, so as to accurately control the source of the epidemic.

[0024] The analysis and evaluation module includes a risk assessment model and an epidemic prevention measure output part. The construction process of the risk assessment model is as follows: Extract the occurrence records of historical animal diseases from the data collected by the data acquisition module, including disease data and animal information data. The disease data includes the onset time, location, animal species, number of diseased animals, and number of deaths; the animal information data includes animal breeding density, animal trading data, and animal movement data. Based on the principles of infectious disease transmission dynamics and using the decision tree model as the basis, construct a risk assessment model for animal diseases. Input the disease data and animal information data into the risk assessment model for animal diseases, train the risk assessment model and correct the parameters. The epidemic prevention measure output part generates epidemic prevention measures according to the output results of the risk assessment model, including determining the scope of the epidemic area, the number of diseased animals to be culled, and the disinfected area. The epidemic prevention measures are output to the receiving terminals of farms, veterinarians, animal trading markets, and epidemic prevention departments respectively through the central computer. As Figure 1 and Figure 4As shown, the data processed by the data analysis part is input into the analysis and evaluation module for constructing a risk assessment model and outputting epidemic prevention measures. During the construction of the risk assessment model, based on the principles of infectious disease transmission dynamics and taking the decision tree model as the basis, a risk assessment model for animal diseases is constructed. After inputting the collected disease data and animal information data into the risk assessment model, the risk assessment model is trained and the parameters are corrected to improve the accuracy of the risk assessment model. After inputting the real-time data collected by the data collection module into the risk assessment model, the risk of animal diseases can be output according to the risk assessment model, and the output results are transmitted to the receiving terminals of the farms, veterinarians, trading markets, and epidemic prevention departments through the central computer respectively, so that each region can formulate corresponding epidemic prevention policies according to the risk prediction results.

[0025] Working principle: Data collection sub-modules are respectively set up in farms, veterinarians, trading markets, and epidemic prevention departments to obtain the physiological status of animals, environmental parameters, and the position movement information of animals, etc. The collected data is input into the data processing module for storage and analysis. The transportation trajectory of animals and the intersection points of the transportation trajectory are analyzed, the animals are traced and investigated, and possible epidemic transmission chains and potential risk factors are found through correlation analysis. According to the results of the tracing and investigation of animals, combined with GIS technology and the principles of infectious disease transmission, an animal epidemic risk assessment model is constructed, and the risk assessment results of animal epidemics are generated by using the model, and suggestions for prevention and control measures for animals are output.

[0026] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention.

Claims

1. An animal epidemic prevention and control epidemiological survey system in a big data scenario, characterized by: It includes a central computer, a data acquisition module, a data processing module, an epidemic investigation and tracing module and an analysis and evaluation module. The central computer is respectively connected to the data acquisition module, the data processing module, the epidemic investigation and tracing module and the analysis and evaluation module. The central computer is bidirectionally connected to the computers of the farms, veterinarians, animal trading markets and epidemic prevention departments through the network, forming a network connection relationship with the central computer as the center and the farms, veterinarians, animal trading markets and epidemic prevention departments interconnected.

2. According to the animal epidemic prevention and control epidemiological survey system in a big data scenario of claim 1, it is characterized by: The data acquisition module is respectively provided with data acquisition submodules in the breeding farm, veterinary clinic, animal trading market and epidemic prevention department, and the data acquisition submodule is connected with the data acquisition module through the network. The data acquisition submodule of the breeding farm is provided with sensors, and the sensors of the breeding farm monitor the animals in the breeding farm in real time to collect the body temperature data, feed intake data and water intake data of the animals. The data acquisition submodule of the veterinary clinic is connected with the electronic medical record system of the clinic, and the data acquisition submodule of the veterinary clinic collects the historical medical data of the animals, the source and destination of the medical animals. The data acquisition submodule of the animal trading market collects the type and quantity data of the traded animals, the source data of the traded animals and the destination data of the traded animals. The data acquisition submodule of the epidemic prevention department is connected with the archive management system to collect the data information of the historical animal epidemics, including the name and type of the epidemic, the time and place of the occurrence of the epidemic and the spread range of the epidemic.

3. According to the animal epidemic prevention and control epidemiological survey system in a big data scenario of claim 1, it is characterized by: The data processing module includes a data storage part and a data analysis part. The data storage part receives a large amount of data from the data acquisition module for storage, and the data analysis part analyzes and processes the data. After preliminary processing of the data, the data is input into the flow investigation and tracing module for further analysis.

4. According to the animal epidemic prevention and control epidemiological survey system in a big data scenario of claim 1, it is characterized by: The epidemiological investigation and tracing module extracts animal trading information and animal transportation information based on the large amount of animal data in the data processing module, generates animal transportation trajectories and the intersection points between animal transportation trajectories based on the animal trading information and animal transportation information, and combines big data analysis technology to comprehensively trace the farms, transportation routes, and trading information around the animal epidemic site to determine the source of the epidemic.

5. According to the animal epidemic prevention and control epidemiological survey system in a big data scenario of claim 1, it is characterized by: The analysis and evaluation module includes a risk assessment model and an epidemic prevention measures output part. The construction process of the risk assessment model is as follows: Extracting historical records of epidemics from the data collected by the data collection module, including epidemic data and animal information data, wherein the epidemic data includes the time, location, animal species, number of cases and number of deaths; the animal information data includes animal breeding density, animal trading data and animal flow data; Based on the principle of infectious disease transmission dynamics and the decision tree model, a risk assessment model for animal diseases is constructed; The disease data and animal information data are input into the risk assessment model of animal diseases, and the risk assessment model is trained and the parameters are corrected.

6. According to the animal epidemic prevention and control epidemiological survey system in a big data scenario of claim 5, it is characterized by: The epidemic prevention measures output part generates epidemic prevention measures according to the output results of the risk assessment model, including determining the scope of the epidemic area, the number of infected animals to be killed, and the disinfection area. The epidemic prevention measures are output to the receiving terminals of the farms, veterinary medicine, animal trading markets and epidemic prevention departments through the central computer.

7. A method for epidemiological investigation of animal epidemic prevention and control in a big data scenario, characterized in that: Using an animal epidemic prevention and control epidemiological investigation system in a big data scenario according to any one of claims 1 to 6 for animal epidemic prevention and control epidemiological investigation, the steps of the method are as follows: Step 1: Use the data collection module to collect data from farms, veterinarians, trading markets, and epidemic prevention departments to obtain the physiological status of animals, environmental parameters, and animal location and movement information; Step 2: Using the data storage part in the data processing module to store the collected animal information and analyze the animal data information; Step 3: Use the data analysis part in the data processing module to analyze the data. According to the transaction information of the trading market and the animal transportation information, analyze the contact relationship between animals and the intersection of the transportation trajectory, conduct epidemiological investigation and trace the source of the animals, and find out the possible epidemic transmission chain and potential risk factors through association analysis; Step 4: Based on the results of animal epidemiological investigation and tracing, combined with geographic information system (GIS) technology and the principles of infectious disease transmission, build an animal epidemic transmission model, use the model to generate risk assessment results for animal epidemics, and output recommendations for animal prevention and control measures.

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