An aquaculture disease risk assessment prediction method and system

Abstract

The application discloses an aquaculture disease risk assessment and prediction method and system, and particularly relates to the technical field of intelligent management of aquaculture. The application builds a three-layer progressive disease risk assessment framework of individuals, groups and regions, and is matched with hierarchical data collection and gradient risk operation, realizes all-around monitoring and research of the whole-scene disease risk of aquaculture, and breaks through the defects of the prior art that only analyzes a single assessment object. The health hidden danger of a single aquaculture object, the disease transmission risk of a single aquaculture unit and the disease diffusion risk of a continuous aquaculture region can be captured in turn, the whole-process risk nodes of aquaculture are comprehensively covered, and the integrity of the aquaculture disease risk monitoring is significantly improved.

Description

Technical Field

[0001] This invention relates to the field of intelligent management technology for aquaculture, and more specifically, to a method and system for assessing and predicting the risk of aquaculture diseases. Background Technology

[0002] Currently, China's aquaculture industry continues to develop towards large-scale and intensive development. Independent aquaculture units such as factory-style aquaculture ponds and flowing water aquaculture tanks are widely used. Most contiguous aquaculture parks rely on natural water systems or artificial waterways to form interconnected aquatic environments. Diseases are a key hidden danger affecting the stable production and income of aquaculture. Pathogens in the water can spread rapidly through individual contact and water flow. Sporadic diseases can easily evolve into group and regional epidemics, causing significant economic losses to the aquaculture industry. However, current technologies for disease risk assessment and prediction in aquaculture still have the following problems: First, the existing risk assessment system is relatively singular in its dimensions. Most schemes only conduct monitoring and analysis on individual aquaculture or single aquaculture units, and have not constructed a three-tiered, progressive, comprehensive assessment framework of individuals, groups, and regions. This makes it impossible to simultaneously identify sporadic disease-carrying individuals, potential disease outbreaks in single-unit groups, and the risk of pathogen spread across water systems, resulting in significant blind spots in the assessment coverage. Secondly, the existing risk quantification methods are relatively crude, mostly using single water quality index threshold comparison or manual experience scoring mode, without combining multiple coupling factors such as pathogen tolerance characteristics of aquaculture species, hypoxic environmental stress, behavioral stress of aquaculture individuals, and temporal accumulation of pathogens to carry out modeling and calculation. At the same time, they also fail to combine hydrodynamic laws to quantify the directional diffusion ability of pathogens between water systems, resulting in insufficient objectivity and accuracy of the assessment results. Furthermore, existing technologies can only output basic risk levels, lack risk level tracing logic, and do not have corresponding differentiated prevention and control plans for different scenarios. The prevention and control measures are highly homogenized and cannot be targeted at core risk sources, resulting in poor disease prevention and control effects. Therefore, a method and system for risk assessment and prediction of aquaculture diseases are proposed to solve the above problems. Summary of the Invention

[0003] To overcome the above-mentioned deficiencies of the prior art, embodiments of the present invention provide a method and system for risk assessment and prediction of aquaculture diseases.

[0004] To achieve the above objectives, the present invention provides the following technical solution: A method for risk assessment and prediction of aquaculture diseases includes the following steps: Data collection: Data collection is carried out in layers, with collection dimensions divided into individual microenvironment, group water body, and regional whole area. The corresponding data collection includes local pathogen concentration, local dissolved oxygen concentration, individual swimming speed, stocking density, average pathogen concentration of the whole pond, water flow direction between units, and distance between units. Individual risk assessment: The cumulative pathogenic attack power is calculated by combining pathogen concentration and dissolved oxygen status, and the effective defense power is calculated by combining individual swimming status. The ratio of the two is used as the individual risk value and the risk level is determined. Population risk assessment: The average risk value of high-risk individuals within a unit is selected as the internal risk benchmark. The population transmission risk value is obtained by combining the two components of contact transmission and water transmission. The population risk value is obtained by superimposing the internal risk benchmark. The population risk level is determined according to the preset rules. Regional risk assessment: Calculate the directional diffusion coefficient between aquaculture units and construct a matrix. Add the diffusion risk of upstream units to obtain the net risk value of each unit. Calculate the overall regional risk value by weighting the water volume percentage and complete the level determination. Dominant risk level determination and tiered prevention and control: The dominant risk level is determined according to the priority of region, group, and individual, the source of risk is located according to the risk composition, and corresponding prevention and control measures are matched.

[0005] Specifically, the process for determining an individual's risk level is as follows: Pathogens and median lethal doses (LD50) are pre-defined for each cultured species. Pathogen concentrations in the surrounding water are measured, and the concentrations are compared to the LD50 to obtain the pathogenic pressure value. ; Set suitable dissolved oxygen ranges for each species and test local dissolved oxygen concentrations: if the concentration is not lower than the lower limit of the range, the dissolved oxygen stress value is recorded as 0; if it is lower than the lower limit, the concentration difference is used as the stress value, which is then multiplied by the stress amplification coefficient to obtain the stress amplification value. ; Using formula Get attack increment value ; The analysis period is pre-defined, and the cumulative pathogenic attack power of the previous moment in the analysis period is extracted and marked as follows. Where n is the current time; Using formula Gain the current cumulative pathogenic attack power.

[0006] Specifically, the process of determining an individual's risk level also includes: The swimming speed of the cultured individuals is collected as the measured swimming speed. The swimming speed is compared with the preset normal swimming speed. If the measured swimming speed is greater than or equal to the normal swimming speed, the deviation is 0. If the measured swimming speed is less than the normal swimming speed, calculate the difference between the normal swimming speed and the measured swimming speed, and then calculate the deviation value by comparing the difference with the normal swimming speed. The stress attenuation coefficients for different farmed individuals are pre-set, and the stress attenuation amount is obtained by multiplying the deviation amplitude value by the stress attenuation coefficient. The basic disease resistance of different farmed individuals is pre-set, and the effective defense is obtained by calculating the difference between the basic disease resistance and the emergency weakening amount. The individual risk value corresponding to different farmed individuals is obtained by dividing the cumulative pathogenic attack power by the effective defense power; Three sets of individual risk value intervals are pre-defined, and each set of risk value intervals corresponds to an individual risk level. The individual risk level is determined by matching the individual risk value with the corresponding individual risk value interval.

[0007] Specifically, the process for determining the risk level of a group is as follows: Sort the risk values ​​of all individuals in the breeding unit from largest to smallest, extract the risk values ​​of individuals within a preset percentage range after sorting, and calculate the arithmetic mean of the risk values ​​of each individual as the risk benchmark within the group. The stocking density is calculated by the ratio of the total number of individuals in the stocking unit to the total water volume of the stocking unit. The contact propagation component is obtained by multiplying the stocking density by a pre-set contact propagation coefficient. Multiple water sampling points are set up in a grid with equal spacing within the aquaculture unit. The water samples collected from each point are mixed in equal amounts, and the concentration of the target pathogen in the mixed sample is measured and the mean value is calculated as the mean pathogen concentration. The mean pathogen concentration is multiplied by a pre-set water propagation coefficient to obtain the water propagation component.

[0008] Specifically, the process of determining the risk level of a group also includes: After normalizing the contact propagation component and the water propagation component respectively, the formula is used. The population transmission risk value is obtained after weighted calculation. ,in , These are the corresponding preset weighting factors; After normalizing the population transmission risk value and the internal risk benchmark, the formula was used. The group risk value is obtained after weighted calculation. ,in , These are the corresponding preset weighting factors; Three groups of group risk value intervals are preset, and each group of group risk value intervals corresponds to a group risk level. The group risk level is determined by matching the group risk value with the corresponding group risk value interval. The group risk level includes high group risk, medium group risk, and low group risk.

[0009] Specifically, the process for determining the risk level of a region is as follows: Independent aquaculture units with direct or indirect water system connections are designated as aquaculture production areas; The tracer concentration was continuously monitored over time at preset monitoring points; the longitudinal diffusion coefficient of the region was calculated based on the peak concentration time, peak concentration, and diffusion width. ; Statistically analyze historical disease spread event data, determine the ratio of actual pathogen transmission efficiency under downstream and upstream conditions, and calibrate accordingly: Flow coefficient: The diffusion efficiency coefficient when the water flow direction is consistent with the diffusion direction; Countercurrent coefficient: The diffusion efficiency coefficient when the water flow direction is opposite to the diffusion direction; For any two farming units A and B: When water flows from A to B, the direction factor =Coefficient of flow; When water flows from B to A, the direction factor = Countercurrent coefficient; When there is no direct water flow connection between A and B, the direction factor =0; A unified baseline distance is preset. The actual distance along the water flow path from the outlet of unit A to the inlet of unit B is obtained through the GIS system. The distance attenuation factor is calculated by comparing the baseline distance with the actual distance, and this factor is marked as follows. .

[0010] Specifically, the process of determining the risk level of a region also includes: For any two aquaculture units A and B within the region, use the formula Obtain the directional diffusion coefficient from A to B; By traversing all pairs of aquaculture units within the region, all directed diffusion coefficients are calculated, and an asymmetric directed diffusion coefficient matrix is ​​constructed. Identify the population risk value corresponding to the breeding unit and mark it as Based on the regional water system flow direction, determine the set of upstream aquaculture units where all water flow directions point to the current unit B. ; For each upstream unit, the risk contribution it transmits to unit B is equal to the product of the group risk value of unit A and the directional diffusion coefficient from A to B. Using formula The net risk value of the unit is calculated; Statistical analysis of water volume in aquaculture unit B and the total number of aquaculture units in the region Using the formula Obtain the unit volume weight ; The regional risk value is obtained by weighted summation using the formula: ; Three sets of regional risk value intervals are pre-defined, and each set of regional risk value intervals corresponds to a regional risk level. The regional risk level is determined by matching the regional risk value with the corresponding regional risk value interval.

[0011] Specifically, the process for determining the dominant risk level is as follows: Following the top-down judgment principle of prioritizing regional risk, followed by group risk, and finally individual risk, the three risk levels are compared step by step to determine the dominant risk level of this disease. First, verify the risk level of the area, then verify the risk level of each breeding unit group, and finally verify the risk level of the individual: If the regional risk level is medium or high, the dominant risk level is determined to be the regional level. If the area is low-risk, but any aquaculture unit group has a medium or high risk, the dominant risk level is determined to be the group level. If the region and all groups are low-risk, and only some high-risk individuals exist, the dominant risk level is determined to be the individual level.

[0012] A disease risk assessment and prediction system for aquaculture includes: Data acquisition module: Data acquisition is completed in layers, with acquisition dimensions divided into individual microenvironment, group water body, and regional whole area, corresponding to the acquisition of local pathogen concentration, local dissolved oxygen concentration, individual swimming speed, stocking density, average pathogen concentration of the whole pond, water flow direction between units and distance between units; Individual risk assessment module: Calculates the cumulative pathogenic attack power by combining pathogen concentration and dissolved oxygen status, and calculates the effective defense power by combining individual swimming status. The ratio of the two is used as the individual risk value and the risk level is determined. The population risk accounting module selects the average risk value of high-risk individuals within the unit as the internal risk benchmark, combines the two components of contact transmission and water transmission to obtain the population transmission risk value, and superimposes the internal risk benchmark to obtain the population risk value. The population risk level is then determined according to preset rules. Regional risk accounting module: Calculates the directional diffusion coefficient between aquaculture units and constructs a matrix, superimposes the diffusion risk of upstream units to obtain the net risk value of each unit; calculates the overall regional risk value and completes the level determination by weighting the water volume ratio; The module for determining the dominant risk level and implementing graded prevention and control measures determines the dominant risk level according to the priority of region, group, and individual, locates the source of risk based on the risk composition, and matches corresponding prevention and control measures.

[0013] The technical effects and advantages of this invention are as follows: This invention establishes a three-tiered, progressive disease risk assessment framework encompassing individuals, groups, and regions, and incorporates layered data collection and gradient risk calculation. This enables comprehensive monitoring and analysis of disease risks across the entire aquaculture process. It overcomes the limitations of existing technologies that only analyze a single assessment object, and can sequentially capture health risks of individual aquaculture objects, disease transmission risks of single aquaculture units, and disease spread risks of contiguous aquaculture areas. This comprehensively covers risk nodes throughout the entire aquaculture process and significantly improves the completeness of aquaculture disease risk monitoring. This invention conducts quantitative analysis by introducing biological characteristic parameters, water propagation rules, and multi-dimensional mathematical models. It combines professional parameters such as pathogen threshold, environmental stress coefficient, dynamic attenuation coefficient, and water diffusion coefficient to complete risk calculation step by step. It replaces the traditional manual experience-based judgment mode with standardized and digital calculation methods, realizes the quantitative output of aquaculture risks, effectively solves the problems of extensive assessment methods, weak data correlation, and large result deviation in existing technologies, and greatly improves the scientificity and objectivity of risk assessment results. This invention identifies primary risks by setting hierarchical sorting rules and matches specific treatment strategies to different risk levels, achieving risk tracing and targeted prevention and control. It overcomes the shortcomings of existing technologies, such as the inability to accurately locate the source of risk and the homogeneity of prevention and control solutions. It allows for targeted control measures to be taken based on whether the risk originates from an individual, a group, or a region, effectively blocking disease transmission chains, reducing the probability of large-scale outbreaks of livestock diseases, and improving the effectiveness of livestock safety management. Attached Figure Description

[0014] Figure 1 This is a flowchart of a method for risk assessment and prediction of aquaculture diseases according to the present invention.

[0015] Figure 2 This is a schematic diagram of a disease risk assessment and prediction system for aquaculture according to the present invention. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] Example 1 like Figure 1 As shown, the steps of a method for risk assessment and prediction of aquaculture diseases are as follows: Data collection: Data on individual microenvironments, water bodies, and the entire region are collected in layers according to the scale of individual microenvironments, water bodies, and the entire region. Individual microenvironment data includes local pathogen concentration, local dissolved oxygen concentration, and individual swimming speed; group water body data includes stocking density and average pathogen concentration of the entire pond; regional environmental data includes water flow direction between units and distance between units. Individual risk assessment: For each individual, the pathogenic pressure is calculated based on the local pathogen concentration and the median lethal dose of the corresponding pathogen of the species. The stress amplification value is generated by amplifying the deviation of local dissolved oxygen from the suitable range through the environmental stress amplification coefficient. The two are combined to obtain the attack increment and the attenuated cumulative attack force to obtain the pathogenic cumulative attack force. At the same time, the effective defense is obtained by subtracting the stress weakening amount, which is converted from the deviation of swimming speed by the stress weakening coefficient, from the basic disease resistance; The ratio of cumulative pathogenic attack power to effective defense power is the individual risk value, which determines the individual's risk level. Specifically: Different species of cultured individuals are pre-set to correspond to a standard pathogen and a median lethal dose (LD50) for the pathogen. Water samples are collected from the water surrounding each individual using a micro-sampling device, and the corresponding pathogen concentration is extracted as the local pathogen concentration. The pathogenic pressure value is calculated by comparing the local pathogen concentration value with the corresponding LD50. ; Different species of cultured individuals are pre-defined to correspond to suitable dissolved oxygen (DO) ranges. Samples of the water surrounding each individual are collected using a miniature dissolved oxygen sensor, and the corresponding local dissolved oxygen concentration is extracted. This local DOA concentration is compared to the lower limit of the suitable DOA range. If the local DOA concentration is greater than or equal to the lower limit, the corresponding DOA stress value is 0. If the local DOA concentration is less than the lower limit, the difference between the lower limit and the local DOA concentration is calculated to obtain the DOA stress value. This stress value is then multiplied by a pre-defined stress amplification coefficient to obtain the stress amplification value. ; Additional explanation: The stress enhancement coefficient was set by technicians based on different varieties, stemming from the different tolerances to hypoxia and the intensity of stress responses among varieties. This is reflected in the following: varieties with strong hypoxia tolerance produce a weaker stress response and a smaller degree of immunosuppression under the same dissolved oxygen concentration, resulting in a lower coefficient value; varieties with weak hypoxia tolerance are more sensitive to hypoxia, have a stronger stress response, a larger degree of immunosuppression, resulting in a higher coefficient value. Using formula Get attack increment value ; The analysis period is pre-defined, and the cumulative pathogenic attack power of the previous moment in the analysis period is extracted and marked as follows. Where n is the current time; Using formula Get the current cumulative pathogenic attack power ,in The attenuation rate for different varieties is preset by technicians; Additional explanation, This represents the residual attack power accumulated in the previous moment after being cleared by the machine itself. The decay rate ranges from 0 to 1, indicating the machine's ability to clear pathogens in each time step. The closer the decay rate is to 0, the stronger the clearing ability, and the attack power from the previous moment is almost completely cleared; the closer the decay rate is to 1, the weaker the clearing ability, and the attack power from the previous moment is almost entirely retained. The swimming speed of the cultured individuals is collected by high-definition camera equipment as the actual swimming speed. The swimming speed is compared with the preset normal swimming speed. If the actual swimming speed is greater than or equal to the normal swimming speed, the deviation is 0. If the measured swimming speed is less than the normal swimming speed, calculate the difference between the normal swimming speed and the measured swimming speed, and then calculate the deviation value by comparing the difference with the normal swimming speed. The stress attenuation coefficients for different farmed individuals are pre-set, and the stress attenuation amount is obtained by multiplying the deviation amplitude value by the stress attenuation coefficient. Additional explanation: The stress weakening coefficient refers to the extent to which the disease resistance of a farmed individual is weakened due to stress behavior. For stress-sensitive breeds, the extent to which behavioral deviation causes immunosuppression is large, and the stress weakening coefficient value is high; for stress-tolerant breeds, the extent to which behavioral deviation causes immunosuppression is small, and the stress weakening coefficient value is low. The basic disease resistance of different farmed individuals is pre-set. The effective defense is calculated by the difference between the basic disease resistance and the emergency weakening amount. When the effective defense is less than or equal to 0, the minimum positive defense value is taken by default. The individual risk value corresponding to different farmed individuals is obtained by dividing the cumulative pathogenic attack power by the effective defense power; Three sets of individual risk value intervals are pre-defined, and each set of risk value intervals corresponds to an individual risk level. The individual risk level is determined by matching the individual risk value with the corresponding individual risk value interval. The individual risk level includes high risk, medium risk, and low risk. Group risk assessment: First, sort all individual risk values ​​within the breeding unit in descending order. The individual risk level is then calculated as the arithmetic mean of the risk values ​​of the top-preset percentage of high-risk individuals, serving as the internal risk benchmark. ; The contact transmission component, obtained by multiplying the stocking density by the contact transmission coefficient, and the water transmission component, obtained by multiplying the average pathogen concentration in the whole pond by the water transmission coefficient, are calculated separately. The two components are then added together to obtain the population transmission risk value. The population risk value is obtained by adding the internal risk benchmark to the population propagation risk value, and the corresponding population risk level is matched according to the pre-built mapping rules. Specifically: The aquaculture units will be defined by independent water bodies, whether natural or artificial, including individual ponds, individual net cages, individual factory aquaculture ponds, and individual flow-through aquaculture tanks. Sort the risk values ​​of all individuals in the breeding unit from largest to smallest, extract the risk values ​​of individuals within a preset percentage range after sorting, and calculate the arithmetic mean of the risk values ​​of each individual as the risk benchmark within the group. Additional notes: The preset percentage is determined based on the corresponding aquaculture species, and is typically set at 5%-15%, representing the minimum proportion of high-risk individuals that can initiate group transmission. Example: A pond has a total of 1000 fish. The preset percentage is 10%. The risk value of the top 100 fish after sorting is averaged to obtain the internal risk benchmark of the pond. The stocking density is calculated by dividing the total number of individuals in the stocking unit by the total water volume of the unit. The contact propagation component is then obtained by multiplying the stocking density by a pre-set contact propagation coefficient. ; Additional explanation: The contact transmission coefficient represents the percentage increase in effective contact rate between individuals for every unit increase in stocking density. It is set by technicians based on different density gradients. Multiple water sampling points were arranged in a grid with equal spacing within the aquaculture unit. Equal volumes of water samples were mixed from each point, and the concentration of the target pathogen in the mixed sample was measured and the mean value was calculated as the pathogen concentration average. The pathogen concentration average was then multiplied by a pre-set water propagation coefficient to obtain the water propagation component. ; To clarify, the waterborne transmission coefficient represents the contribution efficiency of a unit pathogen concentration in water to the transmission risk. It is characterized by the reciprocal of the natural decay rate of the pathogen in water. The slower the pathogen decays and the longer its survival time, the larger the coefficient value. After normalizing the contact propagation component and the water propagation component respectively, the formula is used. The population transmission risk value is obtained after weighted calculation. ,in , These are the corresponding preset weighting factors; After normalizing the population transmission risk value and the internal risk benchmark, the formula was used. The group risk value is obtained after weighted calculation. ,in , These are the corresponding preset weighting factors; Three groups of group risk value intervals are preset, and each group of group risk value intervals corresponds to a group risk level. The group risk level is determined by matching the group risk value with the corresponding group risk value interval. The group risk level includes high group risk, medium group risk, and low group risk. Regional risk accounting establishes an asymmetric diffusion coefficient matrix by solving the directional diffusion coefficient between each pair of aquaculture units within the region; based on the risk of each aquaculture unit itself, the risk contribution from water diffusion from all upstream aquaculture units is superimposed to obtain the net risk value of each unit. The net risk values ​​of all units are weighted and aggregated based on the proportion of water volume of each aquaculture unit in the total water volume of the region. The overall risk value of the region is obtained by solving the weighted aggregation, and the final regional risk level is determined by combining the preset risk interval mapping rules. Specifically: Independent aquaculture units with direct or indirect water system connections are designated as aquaculture production areas; The tracer concentration was continuously monitored over time at pre-set monitoring points using a tracer test method. Based on the peak concentration time, peak concentration, and diffusion width, the longitudinal diffusion coefficient of the region was calculated using standard hydrodynamic methods. ; Statistically analyze historical disease spread event data, determine the ratio of actual pathogen transmission efficiency under downstream and upstream conditions, and calibrate accordingly: Flow coefficient: The diffusion efficiency coefficient when the water flow direction is consistent with the diffusion direction; Countercurrent coefficient: The diffusion efficiency coefficient when the water flow direction is opposite to the diffusion direction; For any two farming units A and B: When water flows from A to B, the direction factor =Coefficient of flow; When water flows from B to A, the direction factor = Countercurrent coefficient; When there is no direct water flow connection between A and B, the direction factor =0; A unified baseline distance is preset. The actual distance along the water flow path from the outlet of unit A to the inlet of unit B is obtained through the GIS system. The distance attenuation factor is calculated by comparing the baseline distance with the actual distance, and this factor is marked as follows. ; Additional notes: The greater the actual distance, the higher the degree to which the pathogen is diluted by the water, and the smaller the distance attenuation factor. For any two aquaculture units A and B within the region, use the formula Obtain the directional diffusion coefficient from A to B; By traversing all pairs of aquaculture units within the region, all directed diffusion coefficients are calculated, and an asymmetric directed diffusion coefficient matrix is ​​constructed. Identify the population risk value corresponding to the breeding unit and mark it as Based on the regional water system flow direction, determine the set of upstream aquaculture units where all water flow directions point to the current unit B. ; For each upstream unit, the risk contribution it transmits to unit B is equal to the product of the group risk value of unit A and the directional diffusion coefficient from A to B. Using formula The net risk value of the unit is calculated when When the value is 0, cell A has no risk contribution to cell B and does not participate in the summation calculation; Statistical analysis of water volume in aquaculture unit B and the total number of aquaculture units in the region Using the formula Obtain the unit volume weight ; The regional risk value is obtained by weighted summation using the formula: ; Three sets of regional risk value intervals are pre-defined for each regional risk value, and each set of regional risk value intervals corresponds to a regional risk level. The regional risk level is determined by matching the regional risk value with the corresponding regional risk value interval. The regional risk level includes high regional risk, medium medium risk, and low regional risk. Dominant risk level determination and tiered prevention and control: Based on the three-tiered risk levels already obtained, the dominant risk level for this assessment is identified according to the priority order of region, group, and individual; the source of risk is determined based on the constituent components of the risk value of the corresponding level, and prevention and control measures recommendations for the corresponding level are given; Following the top-down judgment principle of prioritizing regional risk, followed by group risk, and finally individual risk, the three risk levels are compared step by step to determine the dominant risk level of this disease. First, verify the risk level of the area, then verify the risk level of each breeding unit group, and finally verify the risk level of the individual: If the regional risk level is medium or high, the dominant risk level is determined to be the regional level. If the area is low-risk, but any aquaculture unit group has a medium or high risk, the dominant risk level is determined to be the group level. If the region and all groups are low-risk, and only some high-risk individuals exist, the dominant risk level is determined to be the individual level. For a given dominant risk level, retrieve the constituent parameters of the risk value for that level as the source of risk; Based on the determined dominant level, implement corresponding prevention and control measures: Regional-level prevention and control: Focusing on blocking the spread of pathogens through waterways and controlling water quality across the entire region, we will carry out disinfection of incoming water in designated areas, control of waterway connectivity, and isolation and treatment of upstream risk units to inhibit the spread of pathogens across units; Group-level prevention and control: The main focus is on controlling the spread in single ponds and reducing the probability of outbreaks. This is achieved by reducing the stocking density, adjusting and disinfecting the water in the entire pond, and reducing the concentration of pathogens in the pond, thereby blocking the path of group contact and waterborne transmission. Individual-level prevention and control: The main focus is on eliminating infected individuals and restoring the individual microenvironment, screening and isolating high-risk individuals, optimizing the local dissolved oxygen environment, reducing the pathogenic pressure and stress damage of individuals, and preventing the further spread of risk from sporadic individuals.

[0018] The above formulas are all dimensionless calculations. Dimensionless calculations can be performed using various methods such as standardization, which will not be elaborated here. The formulas are derived from software simulations based on a large amount of collected data, and the preset parameters in the formulas can be set by those skilled in the art according to the actual situation.

[0019] Example 2 Please see Figure 2 As shown, based on the aquaculture disease risk assessment and prediction method provided in Embodiment 1 of this application, Embodiment 2 of this application proposes an aquaculture disease risk assessment and prediction system. Embodiment 2 is merely a preferred embodiment of Embodiment 1, and the implementation of Embodiment 2 will not affect the individual implementation of Embodiment 1.

[0020] Specifically, the difference in the aquaculture disease risk assessment and prediction system provided in Embodiment 2 of this application lies in that it includes: Data acquisition module: Data acquisition is completed in layers, with acquisition dimensions divided into individual microenvironment, group water body, and regional whole area, corresponding to the acquisition of local pathogen concentration, local dissolved oxygen concentration, individual swimming speed, stocking density, average pathogen concentration of the whole pond, water flow direction between units and distance between units; Individual risk assessment module: Calculates the cumulative pathogenic attack power by combining pathogen concentration and dissolved oxygen status, and calculates the effective defense power by combining individual swimming status. The ratio of the two is used as the individual risk value and the risk level is determined. The population risk accounting module selects the average risk value of high-risk individuals within the unit as the internal risk benchmark, combines the two components of contact transmission and water transmission to obtain the population transmission risk value, and superimposes the internal risk benchmark to obtain the population risk value. The population risk level is then determined according to preset rules. Regional risk accounting module: Calculates the directional diffusion coefficient between aquaculture units and constructs a matrix, superimposes the diffusion risk of upstream units to obtain the net risk value of each unit; calculates the overall regional risk value and completes the level determination by weighting the water volume ratio; The module for determining the dominant risk level and implementing graded prevention and control measures determines the dominant risk level according to the priority of region, group, and individual, locates the source of risk based on the risk composition, and matches corresponding prevention and control measures.

[0021] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, ATA hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium can be a solid-state ATA hard disk.

[0022] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0023] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0024] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0025] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0026] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0027] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable ATA hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0028] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for risk assessment and prediction of aquaculture diseases, characterized in that, Includes the following steps: Data collection: Data collection is carried out in layers, with collection dimensions divided into individual microenvironment, group water body, and regional whole area. The corresponding data collection includes local pathogen concentration, local dissolved oxygen concentration, individual swimming speed, stocking density, average pathogen concentration of the whole pond, water flow direction between units, and distance between units. Individual risk assessment: The cumulative pathogenic attack power is calculated by combining pathogen concentration and dissolved oxygen status, and the effective defense power is calculated by combining individual swimming status. The ratio of the two is used as the individual risk value and the risk level is determined. Population risk assessment: The average risk value of high-risk individuals within a unit is selected as the internal risk benchmark. The population transmission risk value is obtained by combining the two components of contact transmission and water transmission. The population risk value is obtained by superimposing the internal risk benchmark. The population risk level is determined according to the preset rules. Regional risk assessment: Calculate the directional diffusion coefficient between aquaculture units and construct a matrix, then superimpose the diffusion risk of upstream units to obtain the net risk value of each unit; The overall risk value of the region is obtained by weighting the proportion of water volume and then determining the risk level. Dominant risk level determination and tiered prevention and control: The dominant risk level is determined according to the priority of region, group, and individual, the source of risk is located according to the risk composition, and corresponding prevention and control measures are matched.

2. The method for risk assessment and prediction of aquaculture diseases according to claim 1, characterized in that, The specific process for determining an individual's risk level is as follows: Pathogens and median lethal doses (LD50) are pre-defined for each cultured species. Pathogen concentrations in the surrounding water are measured, and the concentrations are compared to the LD50 to obtain the pathogenic pressure value. ; Set suitable dissolved oxygen ranges for each species and test local dissolved oxygen concentrations: if the concentration is not lower than the lower limit of the range, the dissolved oxygen stress value is recorded as 0; if it is lower than the lower limit, the concentration difference is used as the stress value, which is then multiplied by the stress amplification coefficient to obtain the stress amplification value. ; Using formula Get attack increment value ; Pre-set the analysis period, extract the cumulative pathogenic attack power of the previous moment in the analysis period, and mark it as... Where n is the current time; Using formula Gain the current cumulative pathogenic attack power.

3. The method for risk assessment and prediction of aquaculture diseases according to claim 1, characterized in that, The specific process of determining an individual's risk level also includes: The swimming speed of the cultured individuals is collected as the measured swimming speed. The swimming speed is compared with the preset normal swimming speed. If the measured swimming speed is greater than or equal to the normal swimming speed, the deviation is 0. If the measured swimming speed is less than the normal swimming speed, calculate the difference between the normal swimming speed and the measured swimming speed, and then calculate the deviation value by comparing the difference with the normal swimming speed. The stress attenuation coefficients for different farmed individuals are pre-set, and the stress attenuation amount is obtained by multiplying the deviation amplitude value by the stress attenuation coefficient. The basic disease resistance of different farmed individuals is pre-set, and the effective defense is obtained by calculating the difference between the basic disease resistance and the emergency weakening amount. The individual risk value corresponding to different farmed individuals is obtained by dividing the cumulative pathogenic attack power by the effective defense power; Three sets of individual risk value intervals are pre-defined, and each set of risk value intervals corresponds to an individual risk level. The individual risk level is determined by matching the individual risk value with the corresponding individual risk value interval.

4. The method for risk assessment and prediction of aquaculture diseases according to claim 1, characterized in that, The specific process for determining the risk level of a group is as follows: Sort the risk values ​​of all individuals in the breeding unit from largest to smallest, extract the risk values ​​of individuals within a preset percentage range after sorting, and calculate the arithmetic mean of the risk values ​​of each individual as the risk benchmark within the group. The stocking density is calculated by the ratio of the total number of individuals in the stocking unit to the total water volume of the stocking unit. The contact propagation component is obtained by multiplying the stocking density by a pre-set contact propagation coefficient. Multiple water sampling points are set up in a grid with equal spacing within the aquaculture unit. The water samples collected from each point are mixed in equal amounts, and the concentration of the target pathogen in the mixed sample is measured and the mean value is calculated as the mean pathogen concentration. The mean pathogen concentration is multiplied by a pre-set water propagation coefficient to obtain the water propagation component.

5. The method for risk assessment and prediction of aquaculture diseases according to claim 1, characterized in that, The specific process of determining the risk level of a group also includes: After normalizing the contact propagation component and the water propagation component respectively, the formula is used. The population transmission risk value is obtained after weighted calculation. ,in , These are the corresponding preset weighting factors; After normalizing the population transmission risk value and the internal risk benchmark, the formula was used. The group risk value is obtained after weighted calculation. ,in , These are the corresponding preset weighting factors; Three groups of group risk value intervals are preset, and each group of group risk value intervals corresponds to a group risk level. The group risk level is determined by matching the group risk value with the corresponding group risk value interval. The group risk level includes high group risk, medium group risk, and low group risk.

6. The method for risk assessment and prediction of aquaculture diseases according to claim 1, characterized in that, The specific process for determining the risk level of a region is as follows: Independent aquaculture units with direct or indirect water system connections are designated as aquaculture production areas; The tracer concentration was continuously monitored over time at preset monitoring points; the longitudinal diffusion coefficient of the region was calculated based on the peak concentration time, peak concentration, and diffusion width. ; Statistically analyze historical disease spread event data, determine the ratio of actual pathogen transmission efficiency under downstream and upstream conditions, and calibrate accordingly: Flow coefficient: The diffusion efficiency coefficient when the water flow direction is consistent with the diffusion direction; Countercurrent coefficient: The diffusion efficiency coefficient when the water flow direction is opposite to the diffusion direction; For any two farming units A and B: When water flows from A to B, the direction factor =Coefficient of flow; When water flows from B to A, the direction factor =Reverse flow coefficient; When there is no direct water flow connection between A and B, the direction factor =0; A unified baseline distance is preset. The actual distance along the water flow path from the outlet of unit A to the inlet of unit B is obtained through the GIS system. The distance attenuation factor is calculated by comparing the baseline distance with the actual distance, and this factor is marked as follows. .

7. The method for risk assessment and prediction of aquaculture diseases according to claim 1, characterized in that, The specific process for determining the risk level of a region also includes: For any two aquaculture units A and B within the region, use the formula Obtain the directional diffusion coefficient from A to B; By traversing all pairs of aquaculture units within the region, all directed diffusion coefficients are calculated, and an asymmetric directed diffusion coefficient matrix is ​​constructed. Identify the population risk value corresponding to the breeding unit and mark it as Based on the regional water system flow direction, determine the set of upstream aquaculture units where all water flow directions point to the current unit B. ; For each upstream unit, the risk contribution it transmits to unit B is equal to the product of the group risk value of unit A and the directional diffusion coefficient from A to B. Using formula The net risk value of the unit is calculated; Statistical analysis of water volume in aquaculture unit B and the total number of aquaculture units in the region Using the formula Obtain the unit volume weight ; The regional risk value is obtained by weighted summation using the formula: ; Three sets of regional risk value intervals are pre-defined, and each set of regional risk value intervals corresponds to a regional risk level. The regional risk level is determined by matching the regional risk value with the corresponding regional risk value interval.

8. The method for risk assessment and prediction of aquaculture diseases according to claim 1, characterized in that, The specific process for determining the dominant risk level is as follows: Following the top-down judgment principle of prioritizing regional risk, followed by group risk, and finally individual risk, the three risk levels are compared step by step to determine the dominant risk level of this disease. First, verify the risk level of the area, then verify the risk level of each breeding unit group, and finally verify the risk level of the individual: If the regional risk level is medium or high, the dominant risk level is determined to be the regional level. If the area is low-risk, but any aquaculture unit group has a medium or high risk, the dominant risk level is determined to be the group level. If the region and all groups are low-risk, and only some high-risk individuals exist, the dominant risk level is determined to be the individual level.

9. A disease risk assessment and prediction system for aquaculture, applied to the disease risk assessment and prediction method for aquaculture proposed in any one of claims 1-8, characterized in that, include: Data acquisition module: Data acquisition is completed in layers, with acquisition dimensions divided into individual microenvironment, group water body, and regional whole area, corresponding to the acquisition of local pathogen concentration, local dissolved oxygen concentration, individual swimming speed, stocking density, average pathogen concentration of the whole pond, water flow direction between units and distance between units; Individual risk assessment module: Calculates the cumulative pathogenic attack power by combining pathogen concentration and dissolved oxygen status, and calculates the effective defense power by combining individual swimming status. The ratio of the two is used as the individual risk value and the risk level is determined. The population risk accounting module selects the average risk value of high-risk individuals within the unit as the internal risk benchmark, combines the two components of contact transmission and water transmission to obtain the population transmission risk value, and superimposes the internal risk benchmark to obtain the population risk value. The population risk level is then determined according to preset rules. Regional risk accounting module: Calculates the directional diffusion coefficient between aquaculture units and constructs a matrix, and superimposes the diffusion risk of upstream units to obtain the net risk value of each unit; The overall risk value of the region is obtained by weighting the proportion of water volume and then determining the risk level. The module for determining the dominant risk level and implementing graded prevention and control measures determines the dominant risk level according to the priority of region, group, and individual, locates the source of risk based on the risk composition, and matches corresponding prevention and control measures.

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