Method and device for evaluating effectiveness of antibacterial drug use reduction, and storage medium

Abstract

The present application relates to a kind of antibacterial drug use reduction effect evaluation method, device and storage medium, applied to livestock and poultry breeding technical field, comprising: by obtaining the basic effect data of farm animals or animal products, risk control effect data and detection effect data, then each evaluation index is calculated, then according to the standard data of each evaluation index, the score of each evaluation index is calculated, the weight of each index is determined by analytic hierarchy process, and the comprehensive evaluation score of antibacterial drug reduction effect is obtained according to the weight of each index, in the calculation process of antibacterial drug reduction effect comprehensive evaluation score, the data obtained are determined, quantized data, compared with each evaluation item in the prior art, subjective influence is thrown away, and in the process of calculating antibacterial drug reduction effect comprehensive evaluation score, consider from multiple dimensions of data, compared with prior art, evaluation dimension is more comprehensive.

Description

Technical Field

[0001] This invention relates to the field of livestock and poultry breeding technology, specifically to a method, apparatus, and storage medium for evaluating the effectiveness of reducing the use of antibacterial drugs. Background Technology

[0002] Currently, the Ministry of Agriculture and Rural Affairs is promoting the reduction of veterinary antibiotic use and encouraging local governments to establish and improve local evaluation index systems for antibiotic reduction in livestock farming, and to organize evaluations of the effectiveness of antibiotic reduction. The Zhejiang Provincial Department of Agriculture and Rural Affairs has proposed the "Evaluation Standards for Livestock Farms that Meet the Standards for Reducing the Use of Veterinary Antibiotics in Zhejiang Province." This standard evaluates livestock farms from four perspectives: basic conditions of the farm, basic systems of the farm, relevant records, and the effectiveness of reduction actions. Farms that meet the relevant standards are recommended as "Livestock Farms that Meet the Standards for Reducing the Use of Veterinary Antibiotics in Zhejiang Province." This evaluation method, which relies on checking and scoring according to the evaluation criteria, is relatively simplistic and the evaluation items have a certain degree of subjectivity. Summary of the Invention

[0003] In view of this, the purpose of the present invention is to provide a method, device and storage medium for evaluating the effectiveness of reducing the amount of veterinary antimicrobial drugs used, so as to solve the problem that in the prior art, there are relatively few evaluation indicators for evaluating the reduction of veterinary antimicrobial drugs, and the evaluation items have a certain degree of subjectivity, and there is no unified quantitative standard to measure the effectiveness of reducing the amount of veterinary antimicrobial drugs.

[0004] According to a first aspect of the present invention, a method for evaluating the effectiveness of reducing the use of antibacterial drugs is provided, comprising:

[0005] Acquire basic performance data, risk control performance data, and testing performance data of animals or animal products from farms within a preset time unit;

[0006] Basic performance indicators are calculated based on basic performance data, risk control performance indicators are calculated based on risk control performance data, and detection performance data is used as detection performance indicators.

[0007] Scores for basic performance indicators, risk control performance indicators, and detection performance indicators are obtained based on the standard data of the preset indicators.

[0008] The weights of each indicator are determined by the analytic hierarchy process (AHP). Based on the weights and scores of each indicator, a comprehensive evaluation score for the effectiveness of reducing antibiotic dosage is obtained.

[0009] Preferably,

[0010] The acquisition of basic performance data of farm animals or animal products within a preset time unit includes:

[0011] Get the total amount of antibiotics used on animals within a preset time unit, get the total weight of animals slaughtered or the total amount of animal products within a preset time unit, and get the amount of antibiotics used on animals or animal products within the previous preset time unit.

[0012] Preferably,

[0013] The basic performance indicators include: the amount of antibiotics used per unit of animal or animal product and the month-on-month growth rate of the amount of antibiotics used per unit of animal or animal product.

[0014] The calculation of basic performance indicators based on basic performance data includes:

[0015] The total amount of antibiotics used on animals within a preset time unit is divided by the total weight of animals slaughtered or the total amount of animal products within the preset time unit to obtain the amount of antibiotics used per animal or animal product.

[0016] The month-on-month increase in antibiotic usage per animal or animal product is obtained by subtracting 1 from the amount of antibiotic usage per animal or animal product in the previous preset time unit.

[0017] Preferably,

[0018] The acquisition of risk control effectiveness data for farm animals or animal products within a preset time unit includes:

[0019] Based on the antibiotic classification standards, the total amount of antibiotics used by animals at each level within a preset time unit was obtained, as well as the total amount of antibiotic alternative products used by animals within the preset time unit and the total amount of drugs used.

[0020] Preferably,

[0021] The risk control effectiveness indicators include: drug risk coefficient and the proportion of alternative antibiotics;

[0022] The calculation of risk control effectiveness indicators based on risk control effectiveness data includes:

[0023] The proportion of each grade of antibiotic used was obtained by dividing the amount of each antibiotic used by the total amount of antibiotics used.

[0024] The risk coefficients of each level of antimicrobial drug are preset. The proportion of each level of antimicrobial drug used in the total amount of antimicrobial drugs is multiplied by the risk coefficient of each level of antimicrobial drug and then added together to obtain the drug risk coefficient.

[0025] The percentage of antibiotic alternatives is calculated by dividing the total amount of antibiotic alternatives used by animals within a preset time period by the total amount of drugs used.

[0026] Preferably,

[0027] The acquisition of test results data for farm animals or animal products within a preset time unit includes:

[0028] Obtain the average pass rate of third-party testing institutions or government agencies for animals or animal products within a preset time unit, and obtain the number of tests conducted by third-party testing institutions or government agencies within a preset time unit;

[0029] The use of detection performance data as an indicator of detection performance includes:

[0030] The average pass rate of third-party testing institutions or government agencies for animals or animal products within a preset time unit is used as the average pass rate indicator, and the number of tests conducted by third-party testing institutions or government agencies within a preset time unit is used as the number of tests indicator.

[0031] Preferably,

[0032] The determination of the weights of each indicator using the analytic hierarchy process includes:

[0033] The basic performance indicators, risk control performance indicators, and detection performance indicators are used as the criteria layer.

[0034] The dosage of antibiotics per unit animal or animal product, the month-on-month growth rate of antibiotics per unit animal or animal product, the drug risk coefficient, the proportion of antibiotic alternatives, the average pass rate, and the number of tests are used as the scheme layers under each corresponding criterion layer.

[0035] The importance of any two indicators in the criterion layer is measured using a relative scale to obtain the scale values ​​of any two indicators. A criterion layer judgment matrix is ​​then established based on the scale values ​​of any two indicators.

[0036] The importance of the two scheme-level indicators under the basic performance indicators is measured by relative scale to obtain the scale value between the two scheme-level indicators. The first scheme-level judgment matrix is ​​established based on the scale value between the two scheme-level indicators. The above steps are repeated to establish the second scheme-level judgment matrix of the risk control performance indicators and the third scheme-level judgment matrix of the detection performance indicators in turn.

[0037] The columns of the criterion-level judgment matrix are summed, and the sum of each column is normalized. Then the sum of each row is summed, and the sum of each row is normalized. The normalized values ​​of each row are used as the weight values ​​of the basic performance indicator, the risk control performance indicator, and the detection performance indicator, respectively.

[0038] The columns of the first scheme layer judgment matrix are summed, and the sums of the columns are normalized. Then, the sums of the rows are summed, and the rows are normalized. The normalized values ​​of each row are used as the scheme layer weights for the amount of antibiotics used per unit animal or animal product and the month-on-month increase in the amount of antibiotics used per unit animal or animal product. The above steps are repeated to obtain the scheme layer weights for the drug risk coefficient and the proportion of alternative antibiotics in the second scheme layer judgment matrix, and the scheme layer weights for the average pass rate and the number of tests in the third scheme layer judgment matrix.

[0039] Multiply the weight value of the basic performance indicator by the scheme layer weight value of the amount of antibiotics used per unit of animal or animal product to obtain the weight value of the amount of antibiotics used per unit of animal or animal product. Multiply the weight value of the basic performance indicator by the scheme layer weight value of the month-on-month increase in the amount of antibiotics used per unit of animal or animal product to obtain the weight value of the month-on-month increase in the amount of antibiotics used per unit of animal or animal product. Repeat the above steps to obtain the weight values ​​of the drug risk coefficient, the proportion of antibiotic alternatives, the average pass rate, and the number of tests, respectively.

[0040] According to a second aspect of the present invention, an evaluation device for the effectiveness of reducing the use of antibacterial drugs is provided, the device comprising:

[0041] Data acquisition module: used to acquire basic performance data, risk control performance data, and testing performance data of animals or animal products from farms within a preset time unit;

[0042] Indicator Calculation Module: Used to calculate basic performance indicators based on basic performance data, calculate risk control performance indicators based on risk control performance data, and use detection performance data as detection performance indicators.

[0043] Indicator Score Acquisition Module: Used to obtain scores for basic performance indicators, risk control performance indicators, and detection performance indicators based on the preset standard data of various indicators.

[0044] Comprehensive evaluation module: This module uses the analytic hierarchy process (AHP) to determine the weights of each indicator and, based on the weights and scores of each indicator, obtains a comprehensive evaluation score for the effectiveness of reducing antibiotic dosage.

[0045] According to a third aspect of the present invention, a storage medium is provided, the storage medium storing a computer program, which, when executed by a master controller, implements the various steps in the digital twin-based logistics equipment redesign method.

[0046] The technical solutions provided by the embodiments of the present invention may include the following beneficial effects:

[0047] This application obtains basic performance data, risk control performance data, and testing performance data of animals or animal products from farms. It then calculates various evaluation indicators based on these data, and calculates scores for each indicator according to standard data. The weights of each indicator are determined using the analytic hierarchy process (AHP). Based on the weights and scores of each indicator, a comprehensive evaluation score for antibiotic reduction effectiveness is obtained. This comprehensive evaluation score is used to specifically evaluate the effectiveness of antibiotic reduction in veterinary use. In calculating this score, all data obtained are definite and quantifiable, eliminating the influence of human subjectivity compared to existing technologies. Furthermore, the calculation of the comprehensive evaluation score considers data from multiple dimensions, making the evaluation more comprehensive than existing technologies.

[0048] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit the invention. Attached Figure Description

[0049] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0050] Figure 1 This is a flowchart illustrating an exemplary embodiment of a method for evaluating the effectiveness of reducing the use of antimicrobial drugs;

[0051] Figure 2 This is a schematic diagram of a system for evaluating the effectiveness of reducing the use of antimicrobial drugs, according to another exemplary embodiment.

[0052] In the attached diagram: 1-Data acquisition module, 2-Indicator calculation module, 3-Indicator score acquisition module, 4-Comprehensive evaluation module. Detailed Implementation

[0053] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the invention as detailed in the appended claims.

[0054] Example 1

[0055] Figure 1 This is a flowchart illustrating an exemplary method for evaluating the effectiveness of reducing the use of antimicrobial drugs, as shown in the example. Figure 1As shown, the method includes:

[0056] S1, obtain basic performance data, risk control performance data and testing performance data of animals or animal products in the farm within a preset time unit;

[0057] S2, calculate basic performance indicators based on basic performance data, calculate risk control performance indicators based on risk control performance data, and use detection performance data as detection performance indicators.

[0058] S3, based on the standard data of the preset indicators, obtains the scores of basic performance indicators, risk control performance indicators and detection performance indicators.

[0059] S4. The weights of each indicator are determined by the analytic hierarchy process. Based on the weights and scores of each indicator, a comprehensive evaluation score for the effectiveness of reducing the amount of antimicrobial drugs is obtained.

[0060] Understandably, this application obtains basic performance data, risk control performance data, and testing performance data of animals or animal products from farms. It then calculates various evaluation indicators based on these data, calculates scores for each indicator according to standard data, determines the weights of each indicator using the analytic hierarchy process (AHP), and obtains a comprehensive evaluation score for antibiotic reduction effectiveness based on the weights and scores of each indicator. This comprehensive evaluation score is then used to specifically evaluate the effectiveness of antibiotic reduction in veterinary use. In calculating this score, all data obtained are definite and quantifiable, eliminating the influence of human subjectivity compared to existing technologies. Furthermore, the calculation of the comprehensive evaluation score considers data from multiple dimensions, making the evaluation more comprehensive than existing technologies.

[0061] Preferably,

[0062] The acquisition of basic performance data of farm animals or animal products within a preset time unit includes:

[0063] Get the total amount of antibiotics used on animals within a preset time unit, get the total weight of animals slaughtered or the total amount of animal products within a preset time unit, and get the amount of antibiotics used per animal or animal product within the previous preset time unit.

[0064] Understandably, in terms of obtaining basic effectiveness data, the data includes the total amount of veterinary antibiotics used in animals within one year of implementing the reduction policy, the total weight of animals slaughtered or the total amount of animal products within one year of implementing the reduction policy, and the amount of veterinary antibiotics used in animals or animal products in the previous year.

[0065] Preferably,

[0066] The basic performance indicators include: the amount of antibiotics used per unit of animal or animal product and the month-on-month growth rate of the amount of antibiotics used per unit of animal or animal product.

[0067] The calculation of basic performance indicators based on basic performance data includes:

[0068] The total amount of antibiotics used on animals within a preset time unit is divided by the total weight of animals slaughtered or the total amount of animal products within the preset time unit to obtain the amount of antibiotics used per animal or animal product.

[0069] The month-on-month growth rate of antibiotic usage per animal or animal product is obtained by subtracting 1 from the amount of antibiotic usage per animal or animal product in the previous preset time unit.

[0070] Understandably, after obtaining the aforementioned basic performance data, the basic performance indicators include the calculation of indicators in two dimensions: the amount of veterinary antibiotics used per unit of animal or animal product, and the month-on-month growth rate of the amount of veterinary antibiotics used per unit of animal or animal product. The amount of veterinary antibiotics used per unit of animal or animal product is equal to the total amount of veterinary antibiotics used by animals within one year of implementing the reduction measures, divided by the total weight of animals slaughtered or the total amount of animal products. This indicator reflects the control of antibiotic use in animals or animal products within one year. The month-on-month growth rate of veterinary antibiotic use per unit of animal or animal product is equal to the current year's amount of veterinary antibiotics used per animal or animal product, divided by the previous year's amount of veterinary antibiotics used per animal or animal product, minus 1. This indicator reflects the strength of the farm's antibiotic reduction implementation; the larger the month-on-month negative growth rate, the stronger the farm's antibiotic reduction implementation.

[0071] Preferably,

[0072] The acquisition of risk control effectiveness data for farm animals or animal products within a preset time unit includes:

[0073] Based on the antibiotic classification standard, the total amount of antibiotics used by animals at each level within a preset time unit, the total amount of antibiotic alternative products used by animals within a preset time unit, and the total amount of drugs used were obtained.

[0074] Understandably, the acquisition of risk control effectiveness data is based on the antibiotic grading standards. This involves obtaining the usage of antibiotics of various grades in livestock or animal products within a preset time unit, as well as the usage of antibiotic alternatives in livestock or animal products within the same preset time unit. It's worth noting that the antibiotics used by livestock farms are graded according to the "Administrative Measures for the Clinical Application of Veterinary Antimicrobial Drugs for Food Animals (Draft for Comments)" and the "Catalogue for the Graded Management of Clinical Application of Veterinary Antimicrobial Drugs for Food Animals (Draft for Comments)." Veterinary antibiotics are divided into three levels: unrestricted use, restricted use, and special use. Unrestricted use antibiotics are those with relatively low concern about bacterial resistance; restricted use antibiotics are those with relatively high concern about bacterial resistance; and special use antibiotics are those with extremely high concern about bacterial resistance. The total drug usage includes the total usage of antibiotics, antibiotic alternatives, vaccines, disinfectants, etc.

[0075] Preferably,

[0076] The risk control effectiveness indicators include: drug risk coefficient and the proportion of alternative antibiotics;

[0077] The calculation of risk control effectiveness indicators based on risk control effectiveness data includes:

[0078] The proportion of each grade of antibiotic used was obtained by dividing the amount of each antibiotic used by the total amount of antibiotics used.

[0079] The risk coefficients of each level of antimicrobial drug are preset. The proportion of each level of antimicrobial drug used in the total amount of antimicrobial drugs is multiplied by the risk coefficient of each level of antimicrobial drug and then added together to obtain the drug risk coefficient.

[0080] The percentage of antibiotic alternatives is obtained by dividing the total amount of antibiotic alternatives used by animals within a preset time unit by the total amount of drugs used.

[0081] Understandably, after obtaining the risk control effectiveness data, for a single farm, the cumulative weight of antibiotics used within a year is M. Based on the drug classification, the weights of unrestricted antibiotics (M1), restricted antibiotics (M2), and specially used antibiotics (M3) are calculated, where M = M1 + M2 + M3. The proportions of unrestricted antibiotics (P1 = M1 / M), restricted antibiotics (P2 = M2 / M), and specially used antibiotics (P3 = M3 / M) are also considered. The risk coefficient for unrestricted antibiotics is set to 1, and for restricted antibiotics... The risk coefficient for primary antibiotics is set at 1.1, and the risk coefficient for special-use antibiotics is set at 1.2. The comprehensive risk coefficient for antibiotic resistance in farms is calculated as W = P1*1 + P2*1.1 + P3*1.2. The proportion of antibiotic alternatives is equal to the amount of antibiotic alternative products used in a year / the total amount of drugs used. This indicator reflects the use of non-antibiotics in farms in a year. The higher this indicator, the higher the safety of the animals or animal products in the farm (total drug usage includes antibiotic usage and conventional drug usage, and conventional drugs include traditional Chinese medicine preparations and other antibiotic alternatives).

[0082] Preferably,

[0083] The acquisition of test results data for farm animals or animal products within a preset time unit includes:

[0084] Obtain the average pass rate of third-party testing institutions or government agencies for animals or animal products within a preset time unit, and obtain the number of tests conducted by third-party testing institutions or government agencies within a preset time unit;

[0085] The use of detection performance data as an indicator of detection performance includes:

[0086] The average pass rate of third-party testing institutions or government agencies for animals or animal products within a preset time unit is used as the average pass rate indicator, and the number of tests conducted by third-party testing institutions or government agencies within a preset time unit is used as the number of tests indicator.

[0087] Understandably, the average pass rate refers to the average pass rate of tests conducted by third-party testing agencies or government agencies since the implementation of antibiotic reduction measures. The higher this value, the higher the level of safety management at the farm. Third-party testing agencies or government agencies typically test animal products or animals for the presence of various veterinary drug residues, or whether the residue levels are below preset thresholds. The average pass rate is the average of the pass rates for each veterinary drug test. For example, if there are 10 veterinary drug residue tests, and 9 are passed while one is failed, then the average pass rate is 90%. The number of tests equals the cumulative number of tests conducted by third-party testing agencies or government agencies since the implementation of antibiotic reduction measures. With the same pass rate, the higher this value, the higher the level of safety management at the farm.

[0088] It is worth noting that after obtaining the data for each indicator, a score for each indicator will be obtained based on the standard data. The scoring criteria are as follows:

[0089]

[0090] Preferably,

[0091] The determination of the weights of each indicator using the analytic hierarchy process includes:

[0092] The basic performance indicators, risk control performance indicators, and detection performance indicators are used as the criteria layer.

[0093] The dosage of antibiotics per unit animal or animal product, the month-on-month growth rate of antibiotics per unit animal or animal product, the drug risk coefficient, the proportion of antibiotic alternatives, the average pass rate, and the number of tests are used as the scheme layers under each corresponding criterion layer.

[0094] The importance of any two indicators in the criterion layer is measured using a relative scale to obtain the scale values ​​of any two indicators. A criterion layer judgment matrix is ​​then established based on the scale values ​​of any two indicators.

[0095] The importance of the two scheme-level indicators under the basic performance indicators is measured by relative scale to obtain the scale value between the two scheme-level indicators. The first scheme-level judgment matrix is ​​established based on the scale value between the two scheme-level indicators. The above steps are repeated to establish the second scheme-level judgment matrix of the risk control performance indicators and the third scheme-level judgment matrix of the detection performance indicators in turn.

[0096] The columns of the criterion-level judgment matrix are summed, and the sum of each column is normalized. Then the sum of each row is summed, and the sum of each row is normalized. The normalized values ​​of each row are used as the weight values ​​of the basic performance indicator, the risk control performance indicator, and the detection performance indicator, respectively.

[0097] The columns of the first scheme layer judgment matrix are summed, and the sums of the columns are normalized. Then, the sums of the rows are summed, and the rows are normalized. The normalized values ​​of each row are used as the scheme layer weights for the amount of antibiotics used per unit animal or animal product and the month-on-month increase in the amount of antibiotics used per unit animal or animal product. The above steps are repeated to obtain the scheme layer weights for the drug risk coefficient and the proportion of alternative antibiotics in the second scheme layer judgment matrix, and the scheme layer weights for the average pass rate and the number of tests in the third scheme layer judgment matrix.

[0098] Multiply the weight value of the basic performance indicator by the protocol layer weight value of the amount of antibiotics used per unit of animal or animal product to obtain the weight value of the amount of antibiotics used per unit of animal or animal product. Multiply the weight value of the basic performance indicator by the protocol layer weight value of the month-on-month increase in the amount of antibiotics used per unit of animal or animal product to obtain the weight value of the month-on-month increase in the amount of antibiotics used per unit of animal or animal product. Repeat the above steps to obtain the weight values ​​of the drug risk coefficient, the proportion of alternative antibiotics, the average pass rate, and the number of tests, respectively.

[0099] Understandably, by using the Analytic Hierarchy Process (AHP) to determine the weights of the indicators in the above steps, the weights corresponding to indicators A1, A2, B1, B2, C1, and C2 are obtained as W1, W2, W3, W4, W5, and W6, respectively. The AHP is a comprehensive evaluation method that combines qualitative and quantitative analysis. Its main idea is to decompose complex problems into several levels and factors, compare the importance of each pair of indicators, establish a judgment matrix, and calculate the maximum eigenvalue and corresponding eigenvector of the judgment matrix to derive the weights of different options' importance, thus providing a basis for selecting the optimal solution. Specifically:

[0100] First: Establish a hierarchical model: Target layer: effectiveness of reducing antibiotic use; Criteria layer: basic effectiveness, risk control effectiveness, and testing effectiveness; Plan layer: antibiotic usage per unit animal or animal product, month-on-month growth of antibiotic usage per unit animal or animal product, drug risk coefficient, proportion of alternative antibiotics, average test pass rate, and number of tests.

[0101] Second: The importance of each pair of indicators is compared using a relative scale: a scale value of 1 indicates that element i is equally important as element j; a scale value of 3 indicates that element i is slightly more important than element j; a scale value of 5 indicates that element i is significantly more important than element j; a scale value of 7 indicates that element i is strongly more important than element j; a scale value of 9 indicates that element i is extremely more important than element j; 2, 4, 6, and 8 represent the intermediate scale values ​​for the above adjacent judgments. If the scale value of element i relative to element j is aij, then the scale value of element j relative to element i is aji, where aji = 1 / aij;

[0102] The criterion-level judgment matrix is ​​established as shown in the table below:

[0103] D Basic Achievements A Risk control effectiveness B Detection results C Basic Achievements A 1 5 7 Risk control effectiveness B 1 / 5 1 3 Detection results C 1 / 7 1 / 3 1

[0104] The first-stage decision matrix is ​​established as shown in the table below:

[0105]

[0106] The second scheme layer judgment matrix is ​​established as shown in the table below:

[0107] B Drug risk factor B1 Antibiotic alternatives account for B2 Drug risk factor B1 1 5 Antibiotic alternatives account for B2 1 / 5 1

[0108] The third-stage decision matrix is ​​established as shown in the table below:

[0109] C Average pass rate C1 Number of tests C2 Average pass rate C1 1 5 Number of tests C2 1 / 5 1

[0110] The columns of the criterion-level judgment matrix are summed, and the sums are then normalized. The results are shown in the table below:

[0111] D Basic Achievements A Risk control effectiveness B Detection results C Basic Achievements A 1 5 7 Risk control effectiveness B 1 / 5 1 3 Detection results C 1 / 7 1 / 3 1 sum of columns 1.3429 6.3333 11

[0112] Then, summing the values ​​of each row and normalizing the result, we obtain the single sort weight value:

[0113] D Basic Achievements A Risk control effectiveness B Detection results C Sum of all walks of life normalization Basic Achievements A 0.7447 0.7895 0.6364 2.1705 0.7235 Risk control effectiveness B 0.1489 0.1579 0.2727 0.5796 0.1932 Detection results C 0.1064 0.0526 0.0909 0.2499 0.0833

[0114] In the table, the criterion layer weight value for basic effectiveness is 0.7235, the criterion layer weight value for risk control effectiveness is 0.1932, and the criterion layer weight value for detection effectiveness is 0.0833.

[0115] After calculating the weight values, since it is a third-order matrix, the consistency of the matrix still needs to be checked. The checking process is as follows:

[0116] Calculate the maximum eigenvalue of the criterion layer matrix:

[0117]

[0118]

[0119] Calculate the consistency index:

[0120]

[0121] The consistency criteria table for matrices of various orders is shown below:

[0122] n 1 2 3 4 5 6 7 8 9 RI 0 0 0.58 0.90 1.12 1.24 1.32 1.41 1.45

[0123] It can be seen that the standard value RI of the third-order matrix is ​​0.58.

[0124]

[0125] It is evident that the criterion-level judgment matrix exhibits satisfactory consistency.

[0126] Similarly, we can conclude that:

[0127] The single sorting weight values ​​of the first scheme layer judgment matrix and their consistency test results are as follows:

[0128] W = (0.8333, 0.1667) T The first scheme layer judgment matrix is ​​a 2-order matrix. A 2-order matrix itself has complete consistency, so there is no need to judge consistency.

[0129] The single sorting weight values ​​of the judgment matrix for the second scheme layer and their consistency test results are as follows:

[0130] W = (0.8333, 0.1667) T The second scheme layer judgment matrix is ​​a 2-order matrix. A 2-order matrix itself has complete consistency, so there is no need to judge consistency.

[0131] The single sorting weight values ​​of the third scheme layer judgment matrix and their consistency test results are as follows:

[0132] W = (0.8333, 0.1667) T The third scheme layer judgment matrix is ​​a 2-order matrix. A 2-order matrix itself has complete consistency, so there is no need to judge consistency.

[0133] The weight values ​​of each indicator are shown in the table below:

[0134]

[0135] The comprehensive evaluation formula for the effectiveness of antibiotic reduction in specific farms is as follows:

[0136] A1*0.6029+A2*0.1206+B1*0.1610+B2*0.0322+C1*0.0694+C2*0.0139;

[0137] This embodiment also provides the following specific examples:

[0138] This document compiles relevant data for three farms (farms 1, 2, and 3) in a certain district since the implementation of the antimicrobial reduction campaign: antibiotic usage per unit animal or animal product (g / ton), drug risk coefficient, and the proportion of antibiotic alternatives. The statistical period is the most recent statistical year. The year-on-year growth rate of antibiotic usage per unit animal or animal product is based on the two most recent statistical years. The number of tests and average pass rate are cumulative data since the implementation of the antimicrobial reduction campaign (the national veterinary antimicrobial usage reduction campaign began in 2021). Specific data are shown in the table below.

[0139]

[0140] The standardized scoring data is shown in the table below:

[0141]

[0142] The comprehensive evaluation score for the effectiveness of antibiotic reduction in farm 1 is equal to:

[0143] A1*0.6029+A2*0.1206+B1*0.1610+B2*0.0322+C1*0.0694+C2*0.0139= 5*0.6029+4*0.1206+3*0.1610+2*0.0322+2*0.0694+5*0.0139=4.2526;

[0144] The comprehensive evaluation score for the effectiveness of antibiotic reduction in farm 2 is equal to:

[0145] A1*0.6029+A2*0.1206+B1*0.1610+B2*0.0322+C1*0.0694+C2*0.0139= 5*0.6029+3*0.1206+2*0.1610+1*0.0322+4*0.0694+5*0.0139=4.0776;

[0146] The comprehensive evaluation score for the effectiveness of antibiotic reduction in livestock farms is equal to:

[0147] A1*0.6029+A2*0.1206+B1*0.1610+B2*0.0322+C1*0.0694+C2*0.0139= 5*0.6029+5*0.1206+5*0.1610+5*0.0322+2*0.0694+5*0.0139=4.7918;

[0148] Conclusion: Farm 3 showed the most significant reduction in antibiotic dosage, followed by Farm 1, while Farm 2 showed the least significant reduction in antibiotic dosage.

[0149] Example 2

[0150] This embodiment also discloses a system schematic diagram of an evaluation device for the effectiveness of reducing the amount of antibacterial drugs used, as shown in the attached diagram. Figure 2 As shown, it includes:

[0151] Data acquisition module 1: Used to acquire basic performance data, risk control performance data, and testing performance data of animals or animal products from farms within a preset time unit;

[0152] Indicator Calculation Module 2: Used to calculate basic performance indicators based on basic performance data, calculate risk control performance indicators based on risk control performance data, and use detection performance data as detection performance indicators.

[0153] Indicator Score Acquisition Module 3: This module is used to obtain scores for basic performance indicators, risk control performance indicators, and detection performance indicators based on the preset standard data of various indicators.

[0154] Comprehensive Evaluation Module 4: This module is used to determine the weights of each indicator using the analytic hierarchy process (AHP). Based on the weights and scores of each indicator, a comprehensive evaluation score for the effectiveness of reducing the amount of antimicrobial drugs is obtained.

[0155] Understandably, this application acquires basic performance data, risk control performance data, and testing performance data of farm animals or animal products within a preset time unit through data acquisition module 1; calculates basic performance indicators based on basic performance data and risk control performance indicators based on risk control performance data through indicator calculation module 2, and uses testing performance data as testing performance indicators; obtains scores for basic performance indicators, risk control performance indicators, and testing performance indicators through indicator score acquisition module 3 based on preset standard data for each indicator; and determines the weight of each indicator through the analytic hierarchy process (AHP) through comprehensive evaluation module 4, and obtains a comprehensive evaluation score for the effectiveness of antibiotic reduction based on the weights and scores of each indicator. This application acquires basic performance data, risk control performance data, and testing performance data of farm animals or animal products within a preset time unit through data acquisition module 1; Based on the data and testing results, various evaluation indicators are calculated using basic performance data, risk control performance data, and testing performance data. Then, scores for each evaluation indicator are calculated based on standard data. The weights of each indicator are determined using the analytic hierarchy process (AHP). Based on the weights and scores of each indicator, a comprehensive evaluation score for the effectiveness of antibiotic reduction is obtained. This comprehensive evaluation score is used to specifically evaluate the effectiveness of antibiotic reduction in veterinary use. In calculating this score, all data obtained are definite and quantifiable, eliminating the influence of human subjectivity compared to existing technologies. Furthermore, the calculation of the comprehensive evaluation score considers data from multiple dimensions, making the evaluation more comprehensive than existing technologies.

[0156] Example 3:

[0157] This embodiment provides a storage medium storing a computer program, which, when executed by a host controller, implements the various steps in the above method.

[0158] It is understood that the storage medium mentioned above can be a read-only memory, a hard disk, or an optical disk, etc.

[0159] It is understood that the same or similar parts in the above embodiments can be referred to each other, and the contents not described in detail in some embodiments can be referred to the same or similar contents in other embodiments.

[0160] It should be noted that in the description of this invention, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance. Furthermore, in the description of this invention, unless otherwise stated, "a plurality of" means at least two.

[0161] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process, and the scope of the preferred embodiments of the invention includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as will be understood by those skilled in the art to which embodiments of the invention pertain.

[0162] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0163] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0164] Furthermore, the functional units in the various embodiments of the present invention can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0165] The storage media mentioned above can be read-only memory, disk, or optical disk, etc.

[0166] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0167] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for evaluating the effectiveness of reducing the amount of antibacterial drugs used, characterized in that, include: Acquire basic performance data, risk control performance data, and testing performance data of animals or animal products from farms within a preset time unit; The acquisition of basic performance data of farm animals or animal products within a preset time unit includes: Get the total amount of antibiotics used on animals within a preset time unit, get the total weight of animals slaughtered or the total amount of animal products within a preset time unit, and get the amount of antibiotics used on animals or animal products within the previous preset time unit. The acquisition of risk control effectiveness data for farm animals or animal products within a preset time unit includes: Based on the antibiotic classification standard, the total amount of antibiotics used by animals at each level within a preset time unit, the total amount of antibiotic alternative products used by animals within a preset time unit, and the total amount of drugs used were obtained. The acquisition of test results data for farm animals or animal products within a preset time unit includes: Obtain the average pass rate of third-party testing institutions or government agencies for animals or animal products within a preset time unit, and obtain the number of tests conducted by third-party testing institutions or government agencies within a preset time unit; calculate basic performance indicators based on basic performance data, calculate risk control performance indicators based on risk control performance data, and use testing performance data as testing performance indicators. The basic performance indicators include: the amount of antibiotics used per unit of animal or animal product and the month-on-month growth rate of the amount of antibiotics used per unit of animal or animal product. The calculation of basic performance indicators based on basic performance data includes: The total amount of antibiotics used on animals within a preset time unit is divided by the total weight of animals slaughtered or the total amount of animal products within the preset time unit to obtain the amount of antibiotics used per animal or animal product. The month-on-month growth rate of antibiotic usage per animal or animal product is obtained by subtracting 1 from the amount of antibiotic usage per animal or animal product in the previous preset time unit. The risk control effectiveness indicators include: drug risk coefficient and the proportion of alternative antibiotics; The calculation of risk control effectiveness indicators based on risk control effectiveness data includes: The proportion of each grade of antibiotic used was obtained by dividing the amount of each antibiotic used by the total amount of antibiotics used. The risk coefficients of each level of antimicrobial drug are preset. The proportion of each level of antimicrobial drug used in the total amount of antimicrobial drugs is multiplied by the risk coefficient of each level of antimicrobial drug and then added together to obtain the drug risk coefficient. The percentage of antibiotic alternatives is obtained by dividing the total amount of antibiotic alternatives used by animals within a preset time unit by the total amount of drugs used. The use of detection performance data as an indicator of detection performance includes: The average pass rate of third-party testing institutions or government agencies for animals or animal products within a preset time unit is used as the average pass rate indicator, and the number of tests conducted by third-party testing institutions or government agencies within a preset time unit is used as the number of tests indicator. Scores for basic performance indicators, risk control performance indicators, and detection performance indicators are obtained based on the standard data of the preset indicators. The weights of each indicator are determined by the analytic hierarchy process (AHP). Based on the weights and scores of each indicator, a comprehensive evaluation score for the effectiveness of reducing the amount of antimicrobial drugs is obtained. The determination of the weights of each indicator using the analytic hierarchy process includes: The basic performance indicators, risk control performance indicators, and detection performance indicators are used as the criteria layer. The dosage of antibiotics per unit animal or animal product, the month-on-month growth rate of antibiotics per unit animal or animal product, the drug risk coefficient, the proportion of antibiotic alternatives, the average pass rate, and the number of tests are used as the scheme layers under each corresponding criterion layer. The importance of any two indicators in the criterion layer is measured using a relative scale to obtain the scale values ​​of any two indicators. A criterion layer judgment matrix is ​​then established based on the scale values ​​of any two indicators. The importance of the two scheme-level indicators under the basic performance indicators is measured by relative scale to obtain the scale value between the two scheme-level indicators. The first scheme-level judgment matrix is ​​established based on the scale value between the two scheme-level indicators. The above steps are repeated to establish the second scheme-level judgment matrix of the risk control performance indicators and the third scheme-level judgment matrix of the detection performance indicators in turn. The columns of the criterion-level judgment matrix are summed, and the sum of each column is normalized. Then the sum of each row is summed, and the sum of each row is normalized. The normalized values ​​of each row are used as the weight values ​​of the basic performance indicator, the risk control performance indicator, and the detection performance indicator, respectively. The columns of the first scheme layer judgment matrix are summed, and the sums of the columns are normalized. Then, the sums of the rows are summed, and the rows are normalized. The normalized values ​​of each row are used as the scheme layer weights for the amount of antibiotics used per unit animal or animal product and the month-on-month increase in the amount of antibiotics used per unit animal or animal product. The above steps are repeated to obtain the scheme layer weights for the drug risk coefficient and the proportion of alternative antibiotics in the second scheme layer judgment matrix, and the scheme layer weights for the average pass rate and the number of tests in the third scheme layer judgment matrix. Multiply the weight value of the basic performance indicator by the scheme layer weight value of the amount of antibiotics used per unit of animal or animal product to obtain the weight value of the amount of antibiotics used per unit of animal or animal product. Multiply the weight value of the basic performance indicator by the scheme layer weight value of the month-on-month increase in the amount of antibiotics used per unit of animal or animal product to obtain the weight value of the month-on-month increase in the amount of antibiotics used per unit of animal or animal product. Repeat the above steps to obtain the weight values ​​of the drug risk coefficient, the proportion of antibiotic alternatives, the average pass rate, and the number of tests, respectively.

2. An evaluation device for the effectiveness of reducing the amount of antibacterial drugs used, characterized in that, The device is used to implement the method for evaluating the effectiveness of reducing the use of antibacterial drugs as described in claim 1, comprising: Data acquisition module: used to acquire basic performance data, risk control performance data, and testing performance data of animals or animal products from farms within a preset time unit; The acquisition of basic performance data of farm animals or animal products within a preset time unit includes: Get the total amount of antibiotics used on animals within a preset time unit, get the total weight of animals slaughtered or the total amount of animal products within a preset time unit, and get the amount of antibiotics used on animals or animal products within the previous preset time unit. The acquisition of risk control effectiveness data for farm animals or animal products within a preset time unit includes: Based on the antibiotic classification standard, the total amount of antibiotics used by animals at each level within a preset time unit, the total amount of antibiotic alternative products used by animals within a preset time unit, and the total amount of drugs used were obtained. The acquisition of test results data for farm animals or animal products within a preset time unit includes: Obtain the average pass rate of third-party testing institutions or government agencies for animals or animal products within a preset time unit, and obtain the number of tests conducted by third-party testing institutions or government agencies within a preset time unit; Indicator Calculation Module: Used to calculate basic performance indicators based on basic performance data, calculate risk control performance indicators based on risk control performance data, and use detection performance data as detection performance indicators. The basic performance indicators include: the amount of antibiotics used per unit of animal or animal product and the month-on-month growth rate of the amount of antibiotics used per unit of animal or animal product. The calculation of basic performance indicators based on basic performance data includes: The total amount of antibiotics used on animals within a preset time unit is divided by the total weight of animals slaughtered or the total amount of animal products within the preset time unit to obtain the amount of antibiotics used per animal or animal product. The month-on-month growth rate of antibiotic usage per animal or animal product is obtained by subtracting 1 from the amount of antibiotic usage per animal or animal product in the previous preset time unit. The risk control effectiveness indicators include: drug risk coefficient and the proportion of alternative antibiotics; The calculation of risk control effectiveness indicators based on risk control effectiveness data includes: The proportion of each grade of antibiotic used was obtained by dividing the amount of each antibiotic used by the total amount of antibiotics used. The risk coefficients of each level of antimicrobial drug are preset. The proportion of each level of antimicrobial drug used in the total amount of antimicrobial drugs is multiplied by the risk coefficient of each level of antimicrobial drug and then added together to obtain the drug risk coefficient. The percentage of antibiotic alternatives is obtained by dividing the total amount of antibiotic alternatives used by animals within a preset time unit by the total amount of drugs used. The use of detection performance data as an indicator of detection performance includes: The average pass rate of third-party testing institutions or government agencies for animals or animal products within a preset time unit is used as the average pass rate indicator, and the number of tests conducted by third-party testing institutions or government agencies within a preset time unit is used as the number of tests indicator. Indicator Score Acquisition Module: Used to obtain scores for basic performance indicators, risk control performance indicators, and detection performance indicators based on the preset standard data of various indicators. Comprehensive evaluation module: This module is used to determine the weight of each indicator through the analytic hierarchy process (AHP). Based on the weight of each indicator and the score of each indicator, a comprehensive evaluation score for the effectiveness of reducing the amount of antimicrobial drugs is obtained. The determination of the weights of each indicator using the analytic hierarchy process includes: The basic performance indicators, risk control performance indicators, and detection performance indicators are used as the criteria layer. The dosage of antibiotics per unit animal or animal product, the month-on-month growth rate of antibiotics per unit animal or animal product, the drug risk coefficient, the proportion of antibiotic alternatives, the average pass rate, and the number of tests are used as the scheme layers under each corresponding criterion layer. The importance of any two indicators in the criterion layer is measured using a relative scale to obtain the scale values ​​of any two indicators. A criterion layer judgment matrix is ​​then established based on the scale values ​​of any two indicators. The importance of the two scheme-level indicators under the basic performance indicators is measured by relative scale to obtain the scale value between the two scheme-level indicators. The first scheme-level judgment matrix is ​​established based on the scale value between the two scheme-level indicators. The above steps are repeated to establish the second scheme-level judgment matrix of the risk control performance indicators and the third scheme-level judgment matrix of the detection performance indicators in turn. The columns of the criterion-level judgment matrix are summed, and the sum of each column is normalized. Then the sum of each row is summed, and the sum of each row is normalized. The normalized values ​​of each row are used as the weight values ​​of the basic performance indicator, the risk control performance indicator, and the detection performance indicator, respectively. The columns of the first scheme layer judgment matrix are summed, and the sums of the columns are normalized. Then, the sums of the rows are summed, and the rows are normalized. The normalized values ​​of each row are used as the scheme layer weights for the amount of antibiotics used per unit animal or animal product and the month-on-month increase in the amount of antibiotics used per unit animal or animal product. The above steps are repeated to obtain the scheme layer weights for the drug risk coefficient and the proportion of alternative antibiotics in the second scheme layer judgment matrix, and the scheme layer weights for the average pass rate and the number of tests in the third scheme layer judgment matrix. Multiply the weight value of the basic performance indicator by the scheme layer weight value of the amount of antibiotics used per unit of animal or animal product to obtain the weight value of the amount of antibiotics used per unit of animal or animal product. Multiply the weight value of the basic performance indicator by the scheme layer weight value of the month-on-month increase in the amount of antibiotics used per unit of animal or animal product to obtain the weight value of the month-on-month increase in the amount of antibiotics used per unit of animal or animal product. Repeat the above steps to obtain the weight values ​​of the drug risk coefficient, the proportion of antibiotic alternatives, the average pass rate, and the number of tests, respectively.

3. A storage medium, characterized in that, The storage medium stores a computer program, which, when executed by the main controller, implements each step of the method for evaluating the effectiveness of reducing the use of antibacterial drugs as described in claim 1.

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