CN115631870A - Veterinary pathogen drug resistance rapid identification application platform - Google Patents
Veterinary pathogen drug resistance rapid identification application platform Download PDFInfo
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Abstract
The invention relates to an application platform for rapidly identifying veterinary pathogen drug resistance, which comprises a data acquisition module, a drug analysis module and a drug analysis module, wherein the data acquisition module is used for acquiring veterinary drug application data; the storage module is connected with the data acquisition module and used for storing veterinary drug application data, and comprises a database for storing veterinary drug application data and a priority calculation unit for calculating the priority of each sample; the sample binding module is connected with the storage module and is used for acquiring a pre-binding mode according to the priority of the sample data; and the identification module is connected with the sample binding module and the storage module and is used for judging the drug resistance condition, the propagation condition and the identification condition of the sample according to a pre-binding mode. The invention establishes the association of the disease identification result and the medication, the disease symptoms and the illness state, the disease occurrence and the geographical position, and identifies the medication, the drug resistance and the spreading condition.
Description
Technical Field
The invention relates to the field of veterinary pathogen identification, in particular to an application platform for quickly identifying drug resistance of veterinary pathogens.
Background
The detection of animal pathogenic microorganisms is mainly carried out by methods such as etiology detection, molecular biology detection, serology detection and the like, in the past, pathogeny is generally used, inoculation identification is carried out by separating sample microorganisms, but the method is long in time, low in efficiency and low in accuracy, along with the development of molecular biology technology, the detection and identification of microorganisms causing animal diseases are greatly improved by a DNA or RNA sequence detection technology, particularly, the detection efficiency and accuracy are improved, but at present, the detection of animal diseases, the detection of pathogenic microorganisms and the integrity identification of drug use conditions are still in the initial stage, most of animal diseases are treated by experience, namely, a planning and objective identification result cannot be formed, and the spreading of the diseases cannot be predicted.
Chinese patent CN101792790B discloses an analysis method for animal-derived bacterial drug resistance and a system for implementing the analysis method, which identifies animal-derived bacterial drug resistance by receiving animal-derived bacterial data and a search request transmitted from a client, then performing search matching, and returning the search result to the client, but it still does not solve the identification problem of sample medication suggestions, especially the disease transmission situation.
Disclosure of Invention
Therefore, the invention provides an application platform for rapidly identifying veterinary pathogenic drug resistance, which can solve the technical problem that the drug use, drug resistance and propagation condition of the veterinary pathogenic drug resistance cannot be determined according to the case data information.
In order to achieve the above object, the present invention provides an application platform for rapid identification of veterinary pathogenic drug resistance, comprising:
the data acquisition module is used for acquiring veterinary drug application data, wherein the veterinary drug application data comprises animal pathogenic microorganisms applied to veterinary drugs, geographic positions of the veterinary drugs, animal performance symptoms of the veterinary drugs and drug use conditions;
the storage module is connected with the data acquisition module and used for storing veterinary drug application data, and comprises a database for storing veterinary drug application data and a priority calculation unit for calculating the priority of each sample, wherein the priority calculation unit calculates the sample priority p = c × w × d, wherein c is a sample identification index, w is a geographic position index of the applied veterinary drug, and d is an animal symptom index of the applied veterinary drug;
the sample binding module is connected with the storage module and is used for acquiring a pre-binding mode according to the priority of the sample data;
the identification module is connected with the sample binding module and the storage module and used for judging drug resistance, propagation and identification of the sample according to a pre-binding mode, the sample binding module acquires a current sample binding mode according to the priority of the current sample to output the result of the current sample, the identification module outputs the drug result of the current sample when the sample binding module selects a first preset binding mode to output the current sample result, the identification module outputs the drug result of the current sample when the sample binding module selects a second preset binding mode to output the current sample result, the identification module outputs the drug condition of the current sample or judges the drug resistance according to the severity of the current sample, and the identification module determines the propagation degree of the current state of illness according to the morbidity degree of the current sample within a preset range of the geographic position when the sample binding module selects a third preset binding mode to output the current sample result.
Further, the priority calculating unit determines a disease index B according to the number of times of occurrence of the current sample nucleic acid data a in the database ba1 and the cure amount ba2, and sets B = ba2/ba1 × aj, where aj is a ratio of the total number of occurrences of the current sample species to the total number of the occurrence of the current sample species, and compares the disease index B of the current sample with a preset disease index B to select an identification index c of the current sample, where,
when B is less than or equal to B1, the priority calculating unit sets a first preset identification index c1 as a current sample identification index;
when B1 is more than B and less than B2, the priority calculating unit sets a second preset identification index c2 as a current sample identification index;
when B is larger than or equal to B2, the priority calculating unit sets a third preset identification index c3 as a current sample identification index;
the priority calculating unit is used for presetting an illness state index B, setting a first preset illness state index B1 and a second preset illness state index B2, presetting an identification index c, setting a first preset identification index c1, a second preset identification index c2 and a third preset identification index c3.
Further, the storage module stores the position range V of the historical morbidity sample, and the priority calculating unit acquires the geographic position V of the veterinary drug applied to the current sample when the current sample is used
V belongs to V, and the priority calculating unit takes a first preset geographic position index w1 as a current sample geographic position index;
the priority calculating unit presets a geographical position coordinate w, and sets a first preset geographical position index w1 and a second preset geographical position index w2.
Further, the priority calculating unit obtains a current sample symptom and selects a symptom index d, wherein if the current sample symptom is one-level, the priority calculating unit selects a first preset symptom index d1 as the current sample symptom index; if the current sample symptom is second grade, the priority calculation unit selects a second preset symptom index d2 as the current sample symptom index; if the current sample symptom is three-level, the priority calculation unit selects a second preset symptom index d3 as the current sample symptom index; if the current sample symptom is four, the priority calculating unit selects a fourth preset symptom index d4 as the current sample symptom index.
Further, the sample binding module compares the priority P of the current sample with a preset priority P, and the sample binding module selects a pre-binding mode to output the result of the current sample, wherein,
when P is less than or equal to P1, the sample binding module selects a first preset binding mode to output the result of the current sample;
when P1 is larger than P and smaller than P2, the sample binding module selects a second preset binding mode to output the result of the current sample;
when P is larger than or equal to P2, the sample binding module selects a third preset binding mode to output the result of the current sample;
the sample binding module presets a priority P, and sets a first preset priority P1 and a second preset priority P2.
Further, when the sample binding module selects a first preset binding mode to output the result of the current sample, the identification module outputs suggested medication according to the animal pathogenic microorganisms of the current sample applied to the veterinary drug, wherein the identification module calls the common medication of the current pathogenic microorganisms of the current sample species from the storage module to output the common medication.
Further, when the sample binding module selects a second preset binding mode to output the result of the current sample, the identification module obtains the disease condition index b of the current sample and the symptom index di of the current sample to obtain the severity F of the current sample, sets F =10 × b × di, and the identification module compares the severity of the current sample with the preset severity F0 to judge the disease condition of the current sample, wherein,
when F is less than or equal to F0, the identification module judges that the current sample is not serious in disease state, and the identification module calls the current common medicine of pathogenic microorganisms of the current sample species to output;
and when F is larger than F0, the identification module judges that the current sample is serious in illness state, and acquires the medication time of the current sample to judge the drug resistance of the current sample.
Further, the identification module judges that the current sample is serious in illness state, acquires the drug using time t of the current sample and judges the drug resistance of the pathogen of the current sample, wherein,
when T is less than or equal to T1, the identification module judges that the pathogen of the current sample generates no drug resistance temporarily, and the identification module outputs the historical medication of the current sample;
when T1 is more than T and less than T2, the identification module judges that the monitoring time of the current sample is shortened so as to ensure the judgment of the pathogen resistance of the current sample and simultaneously outputs the historical medication of the current sample;
when T is more than or equal to T2, the identification module judges that the pathogen of the current sample generates drug resistance, and the identification module replaces the drug of the current sample and outputs the drug;
the identification module is used for presetting medication time T, and setting first preset medication time T1 and second preset medication time T2.
Further, when the sample binding module selects a third preset binding mode to output a result of the current sample, the identification module obtains a disease degree g in a preset position range by using the current sample position as an origin, and sets g = (n 1 × d1+ n2 × d2+ n3 × d3+ n4 × d 4)/(n 1+ n2+ n3+ n 4), where n1 is the number of cases in which a symptom index in the preset position range is a first preset symptom index, n2 is the number of cases in which a symptom index in the preset position range is a second preset symptom index, n3 is the number of cases in which a symptom index in the preset position range is a third preset symptom index, and n4 is the number of cases in which a symptom index in the preset position range is a fourth preset symptom index.
Further, the identification module compares the disease degree g in the preset position range with a preset disease degree to determine the current disease propagation condition, wherein,
when G is less than or equal to G1, the identification module judges that the current disease condition is not transmitted temporarily;
when G1 is more than G and less than G2, the identification module reduces the preset position range to judge the propagation of the current disease again, wherein the identification module reduces the preset position range r to r1, and sets r1= r x (1- (G2-G) x (G-G1)/(G1 XG 2));
when G is larger than or equal to G2, the identification module judges that the current state of an illness is transmitted, and the identification module sends out a transmission early warning;
the identification module is used for presetting morbidity degree G, setting a first preset morbidity degree G1 and a second preset morbidity degree G2.
Compared with the prior art, the invention has the advantages that the invention is provided with the data acquisition module for acquiring the use condition of the veterinary drug, the acquired data is transmitted to the database of the storage module for storage, the sample object is constructed according to the classification and summarization of a large amount of acquired data, the association among various species, pathogens, diseases and positions is realized, the subsequent tracking management is convenient, when new sample data is acquired, the priority calculation unit in the storage module acquires the priority of the current sample, and the pre-binding mode is selected according to the parameter value of the priority.
Particularly, the disease index is calculated according to the disease times and the cure rate of cases with the same identification result of the current sample and the disease incidence of the species of the current sample, the situation of the host and the disease incidence of the species of the current sample is comprehensively evaluated, meanwhile, the priority calculating unit is also provided with a disease index, the priority calculating unit compares the disease index of the current sample with preset disease indexes and selects the best identification index, wherein if the disease index of the current sample is smaller than or equal to the first preset disease index, the condition of the current sample is not serious, the priority calculating unit selects a first preset identification index with a smaller value as the identification index of the current sample, if the disease index of the current sample is between the first preset disease index and the second preset disease index, the condition of the current sample is serious, the second preset identification index with an intermediate value is selected by the priority calculating unit as the identification index of the current sample, the index of the current sample is larger than the second preset disease index, the condition of the current sample is extremely serious, and the priority calculating unit selects a third preset identification index with a larger value as the identification index of the current sample, so as the condition of the current sample to evaluate the condition of the current sample.
Particularly, the storage module stores the position range of the historical disease sample, the preset positions on the periphery of the historical disease sample are set as the disease range, the priority calculation unit determines the position index according to whether the current sample belongs to the position range, and in the animal breeding process, as pathogenic microorganisms are difficult to clean, and the growth environment and hosts of the pathogenic microorganisms carry the pathogenic microorganisms, the probability of reoccurrence of the position once attacked is high, therefore, the storage module determines whether the current sample occurs at the position of the historical disease sample according to the position of the current sample compared with the coordinates of the historical disease position, so as to determine whether the current sample is caused by the propagation of the pathogenic microorganisms.
Particularly, the symptom indexes are determined according to the sample symptoms, more specifically, the symptom indexes of the samples are comprehensively evaluated according to the current sample and the morbidity condition in the position range, the sample symptoms are gradually increased, the larger the morbidity sample amount at the peripheral position is, the more serious the morbidity condition is, the higher the symptom indexes are, and the symptom grade of the current sample is comprehensively evaluated.
Particularly, the sample binding module is provided with a priority, the sample binding module compares a calculation result of the priority of the current sample with a preset priority and selects a binding mode according to the comparison result of the priority calculation result of the current sample with the preset priority, wherein when the priority of the current sample acquired by the sample binding module is smaller than or equal to the first preset priority, the sample binding module selects the first preset binding mode to clarify the association relation between the identification result and the drug use so as to output the identification result of the drug use, when the priority of the current sample acquired by the sample binding module is between the first preset priority and the second preset priority, the sample binding module selects the second preset binding mode to clarify the association relation between the state of illness and the drug resistance of the current sample so as to output the identification result of the drug use, and when the priority of the current sample acquired by the sample binding module is larger than or equal to the second preset priority, the sample binding module selects the third preset binding mode to clarify the association relation between the position of the current sample and the transmission so as to output the identification result that whether the pathogenic microorganism has been transmitted.
Particularly, the invention selects a second preset binding mode in the sample binding module to determine whether the current sample has drug resistance so as to determine the drug use, the identification module comprehensively evaluates whether the current sample has serious illness according to the disease condition index and symptom index of the current sample, wherein when the severity of the current sample acquired by the identification module is less than or equal to the preset severity, the current sample has no serious illness, the identification module does not control the drug use of the current sample, and selects the conventional drug use of the current sample.
Particularly, when the sample binding module selects a third preset binding mode to output a result of a current sample, the identification module acquires the morbidity degree of the current sample by acquiring the morbidity condition of the current sample at a preset position of the morbidity position, compares the acquired preset morbidity degree of the morbidity degree, and determines whether the current sample disease is spread or not, wherein when the acquired morbidity degree of the identification module is less than or equal to the first preset morbidity degree, the identification module determines that the current disease is not spread temporarily, when the acquired morbidity degree of the identification module is between the first preset morbidity degree and the second preset morbidity degree, the identification module further determines whether the current sample disease is spread or not by narrowing a preset range, and when the acquired morbidity degree of the identification module is greater than or equal to the second preset morbidity degree, the identification module determines that the current disease is spread, and the identification module gives a propagation warning.
Drawings
Fig. 1 is a schematic diagram of an application platform for rapid identification of veterinary pathogen resistance in an embodiment of the invention.
Detailed Description
In order that the objects and advantages of the invention will be more clearly understood, the invention is further described in conjunction with the following examples; it should be understood that the specific embodiments described herein are merely illustrative of the invention and do not delimit the invention.
Preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only for explaining the technical principle of the present invention, and do not limit the scope of the present invention.
Referring to fig. 1, a schematic diagram of an application platform for rapid identification of veterinary drug resistance according to an embodiment of the present invention includes,
the data acquisition module is used for acquiring veterinary drug application data, wherein the veterinary drug application data comprises animal pathogenic microorganisms applied to veterinary drugs, geographic positions of the veterinary drugs, animal performance symptoms of the veterinary drugs and drug use conditions;
the storage module is connected with the data acquisition module and used for storing veterinary drug application data, and comprises a database for storing veterinary drug application data and a priority calculation unit for calculating the priority of each sample, wherein the priority calculation unit calculates the priority p = c × w × d of the sample, wherein the sample identification index, w is the geographic position index of the applied veterinary drug, and d is the animal symptom index of the applied veterinary drug;
the sample binding module is connected with the storage module and is used for acquiring a pre-binding mode according to the priority of the sample data;
and the identification module is connected with the sample binding module and the storage module and is used for judging the drug resistance condition, the propagation condition and the identification condition of the sample according to a pre-binding mode.
Specifically, the veterinary drug administration system is provided with a data acquisition module for acquiring the use condition of veterinary drugs, the acquired data is transmitted to a database of a storage module for storage, a sample object is constructed according to the classification and summarization of a large amount of acquired data, the association among various species, pathogens, diseases and positions is realized, the follow-up tracking management is facilitated, when new sample data is acquired, a priority calculation unit in the storage module acquires the priority of a current sample, and a pre-binding mode is selected according to the parameter value of the priority.
Specifically, the samples of the embodiment of the invention comprise blood, tissues and feces samples of animal medicaments, DNA or RNA nucleic acid data in the samples are sequenced to determine the dominant flora of the microorganisms in the samples as the result of nucleic acid identification, and more specifically, the embodiment of the invention determines the pathogenic microorganisms in the samples according to the nucleic acid sequencing data and sets the maximum amount of the pathogenic microorganisms as the dominant flora of the samples.
Specifically, the collected data is classified and summarized to construct sample objects without limitation as long as the sample objects can meet the query of species, pathogens, symptoms and related information, and the embodiment of the present invention provides a preferred embodiment, wherein the data collected in the database is referred to table one, and a plurality of groups are set, wherein the first group is mainly based on species, the data group for constructing species objects is referred to table two, the second group is mainly based on symptoms, the data group for constructing symptoms objects is referred to table three, and the third group is mainly based on geographical positions, and the data group for constructing geographical position objects is referred to table four.
TABLE I sample data information
Wherein, the coordinates of the position I are 116.81 and 40.30, the coordinates of the position II are 116.20 and 40.62, the coordinates of the position III are 115.79,
39.74 with coordinates 116.81, 40.30 for position iv and 116.05, 39.70 for position v.
TABLE II species object data set
TABLE III, data set of subjects with disorders
TABLE IV geographical location object data set
The priority calculation unit determines a disease index b according to the number of times of occurrence of the current sample nucleic acid data identification result a in the database ba1 and the cure amount ba2, and sets b = ba2/ba1 × aj, wherein aj is the ratio of the total number of occurrences of the current sample species to the total number of the occurrences of the current sample species.
Specifically, in the embodiment of the invention, the current sample is a pig, the sample of pig manure microorganisms is extracted for detection, the detection result shows that the pathogenic dominant flora in the pig manure is escherichia coli, the priority calculation unit calls 651 times of disease occurrence of the animal caused by the escherichia coli in the database, the cure amount is 487 times, wherein the species is the pig and the disease occurrence is 325 times, and therefore, the disease index b of the current sample is 487/651 (325/651) =0.373
Wherein the priority calculating unit compares the disease condition index B of the current sample with a preset disease condition index B to select an identification index c of the current sample,
when B is less than or equal to B1, the priority calculation unit sets a first preset identification index c1 as a current sample identification index;
when B1 is more than B and less than B2, the priority calculating unit sets a second preset identification index c2 as a current sample identification index;
when B is larger than or equal to B2, the priority calculating unit sets a third preset identification index c3 as a current sample identification index;
the priority calculating unit is used for presetting an illness state index B, setting a first preset illness state index B1 and a second preset illness state index B2, presetting an identification index c, setting a first preset identification index c1, a second preset identification index c2 and a third preset identification index c3.
Specifically, the specific parameters of the disease condition index and the specific parameters of the identification index are not limited in the embodiments of the present invention, and may be specifically set according to characteristics of data acquisition, that is, the current platform is applied to a large farm, and the amount of data acquired is large, and the data of the farm is more likely to reflect the general situation, so the disease condition index is set to 0.2-0.6, where the first preset disease condition index is 0.2-0.4, the second preset disease condition index is 0.4-0.6, the identification index is 1-3, the first preset identification index c1 is 1, the second preset identification index c2 is 2, and the third preset identification index c3 is 3. More specifically, when the breeding onset period is met, the set disease indexes and the identification indexes are correspondingly changed, wherein the disease indexes are set to be 0.3-0.7, the first preset disease index is 0.3-0.5, the second preset disease index is 0.5-0.7, the identification indexes are 2-6, the first preset identification index c1 is 2, the second preset identification index c2 is 4, and the third preset identification index c3 is 6.
Specifically, the disease condition indexes are calculated according to the disease incidence times and the cure amount of cases with the same identification result of the current sample and the disease incidence rate of the species of the current sample, the situation of the species, namely the host and the disease incidence amount, is comprehensively evaluated, meanwhile, the priority calculating unit is also provided with a disease condition index, the priority calculating unit compares the disease condition index of the current sample with a preset disease condition index and selects the best identification index, wherein if the disease condition index of the current sample is smaller than or equal to the first preset disease condition index, the current sample is not serious, the priority calculating unit selects a smaller first preset identification index as the current sample identification index, if the disease condition index of the current sample is between the first preset disease condition index and the second preset disease condition index, the current sample is serious, the priority calculating unit selects a middle second preset identification index as the current sample identification index, the current sample index is larger than the second preset disease condition index, the current sample index is extremely serious, and the priority calculating unit selects a larger third preset identification index as the current sample identification index to evaluate the disease condition of the current sample.
The storage module stores a position range V of a historical morbidity sample, and the priority calculation unit acquires a current veterinary drug application geographic position V of the sample when the current veterinary drug application geographic position V is detected
V belongs to V, and the priority computing unit takes a first preset geographic position index w1 as a current sample geographic position index;
the priority computing unit presets a geographic position coordinate w, and sets a first preset geographic position index w1 and a second preset geographic position index w2.
Specifically, the storage module stores the position range of the historical disease sample, the preset positions around the historical disease sample are set as the disease range, the priority calculation unit determines the position index according to whether the current sample belongs to the position range, and in the animal breeding process, as pathogenic microorganisms are difficult to clean, and the growing environment and hosts of the pathogenic microorganisms carry the pathogenic microorganisms, the probability of reoccurrence of the position once attacked is high, therefore, the storage module determines whether the current sample occurs at the position of the historical disease sample according to the position of the current sample compared with the coordinates of the positions of the historical disease samples, so as to determine whether the current sample is caused by the propagation of the pathogenic microorganisms.
Specifically, the embodiment of the present invention does not limit the position range of the historical disease sample, and the position of the disease sample may be divided by taking the disease sample as a central point and taking a preset distance, and further, the present invention does not limit the geographical position index, and the embodiment of the present invention provides a preferred implementation scheme, where the first preset geographical position index w1 is 10, and the second preset geographical position index w2 is 1.
The priority calculation unit acquires a current sample symptom and selects a symptom index d, wherein if the current sample symptom is a first level, the priority calculation unit selects a first preset symptom index d1 as the current sample symptom index; if the current sample symptom is second grade, the priority calculation unit selects a second preset symptom index d2 as the current sample symptom index; if the current sample symptom is three-level, the priority calculation unit selects a second preset symptom index d3 as the current sample symptom index; if the current sample symptom is four, the priority calculating unit selects a fourth preset symptom index d4 as the current sample symptom index.
Specifically, the embodiment of the present invention determines the symptom level according to the sample data stored in the storage module, wherein if the current sample has only a slight single symptom and only one sample of the current geographic location shows the symptom, the symptom of the current sample is evaluated as first level, if the current sample has more than two symptoms and only one sample of the current geographic location shows the symptom, the symptom of the current sample is evaluated as second level, if the current sample has more than two symptoms and more than two samples show the symptom, the symptom of the current sample is evaluated as third level, and if the current sample has the symptoms and the current geographic location has a death case, the symptom of the current sample is evaluated as fourth level.
Specifically, the symptom indexes are determined according to the sample symptoms, more specifically, the symptom indexes of the samples are comprehensively evaluated according to the current sample and the disease incidence condition in the position range, the sample symptoms are gradually increased, the larger the amount of the disease incidence sample at the peripheral position is, the more serious the disease incidence condition is, the higher the symptom indexes are, and the symptom grade of the current sample is comprehensively evaluated.
Specifically, the embodiment of the present invention establishes a pre-binding manner, where the first binding manner is an association relationship between an identification result and a medication to output an identification result of medication use, the second binding manner is an association relationship between a current sample disease state and a drug resistance state to output an identification result of medication use, and the third binding manner is an association relationship between a current sample position and propagation to output an identification result of whether a pathogenic microorganism has propagated.
The sample binding module compares the priority P of the current sample with the preset priority P, and the sample binding module selects a pre-binding mode to output the result of the current sample, wherein,
when P is less than or equal to P1, the sample binding module selects a first preset binding mode to output the result of the current sample;
when P1 is larger than P and smaller than P2, the sample binding module selects a second preset binding mode to output the result of the current sample;
when P is more than or equal to P2, the sample binding module selects a third preset binding mode to output the result of the current sample;
the sample binding module presets a priority P, and sets a first preset priority P1 and a second preset priority P2.
Specifically, the sample binding module is provided with a priority, the sample binding module compares a calculation result of the priority of the current sample with a preset priority, and selects a binding mode, wherein when the priority of the current sample acquired by the sample binding module is less than or equal to the first preset priority, the sample binding module selects the first preset binding mode to clarify the association relationship between the identification result and the drug consumption so as to output the identification result of the drug consumption, when the priority of the current sample acquired by the sample binding module is between the first preset priority and the second preset priority, the sample binding module selects the second preset binding mode to clarify the association relationship between the disease condition and the drug resistance condition of the current sample so as to output the identification result of the drug consumption, and when the priority of the current sample acquired by the sample binding module is greater than or equal to the second preset priority, the sample binding module selects the third preset binding mode to clarify the association relationship between the position of the current sample and the transmission so as to output the identification result whether the pathogenic microorganism has been transmitted.
When the sample binding module selects a first preset binding mode to output the result of the current sample, the identification module outputs suggested medication according to the animal pathogenic microorganisms of the current sample applied to the veterinary drug, wherein the identification module outputs the general medication of the current pathogenic microorganisms of the current sample species by calling the general medication from the storage module.
Wherein, when the sample binding module selects a second preset binding mode to output the result of the current sample, the identification module obtains the disease condition index b of the current sample and the symptom index di of the current sample to obtain the severity F of the current sample, sets F =10 × b × di, the identification module compares the severity of the current sample with the preset severity F0 to judge the disease condition of the current sample, wherein,
when F is less than or equal to F0, the identification module judges that the current sample is not serious in disease state, and the identification module calls the current common medicine of pathogenic microorganisms of the current sample species to output;
and when F is larger than F0, the identification module judges that the current sample is serious in illness state, and acquires the medication time of the current sample to judge the drug resistance of the current sample.
Specifically, the identification module judges that the current sample is serious in illness state, acquires the drug use time t of the current sample and judges the drug resistance of the pathogen of the current sample, wherein,
when T is less than or equal to T1, the identification module judges that the pathogen of the current sample generates no drug resistance temporarily, and the identification module outputs the historical medication of the current sample;
when T1 is more than T and less than T2, the identification module judges that the monitoring time of the current sample is shortened so as to ensure the judgment of the pathogen resistance of the current sample and simultaneously outputs the historical medication of the current sample;
when T is more than or equal to T2, the identification module judges that the pathogen of the current sample generates drug resistance, and the identification module replaces the current sample for medication and outputs the drug;
the identification module is used for presetting medication time T, and setting first preset medication time T1 and second preset medication time T2.
Specifically, in the embodiment of the present invention, the medication time is the total time of the current sample using the current medicine, that is, the time of using the medicine for the first disease of the current sample is 3 days, the time of using the medicine for the second disease is 5 days, and the time of using the medicine for the current disease is 1 day, so the medication time is 9 days.
Specifically, the method includes the steps that a second preset binding mode is selected by a sample binding module to determine whether a current sample has drug resistance or not so as to determine whether the current sample has serious disease or not, when the severity of the current sample disease acquired by the identification module is smaller than or equal to a preset severity, the current sample has no serious disease, the identification module does not control the drug taking of the current sample, and selects the conventional drug taking of the current sample, when the severity of the current sample disease acquired by the identification module is larger than the preset severity, the current sample has serious disease, the identification module determines whether the current sample has drug resistance to the currently used drug according to the drug using time of the current sample, wherein if the current sample has short drug using time, the identification module temporarily cannot determine the drug resistance of the current sample to the current drug, so that the current drug is determined to be output for further determination, if the current sample has long drug using time, the identification module determines to shorten the monitoring time of the current sample, namely, the data acquisition time of the next pair of samples is shortened to ensure the determination of the current sample pathogen resistance, and meanwhile, the drug using time of the current sample is determined to cause that the current sample has drug resistance, and the current sample has long drug taking time for the current pathogen treatment is longer.
When the sample binding module selects a third preset binding mode to output the result of the current sample, the identification module obtains the disease degree g in a preset position range by taking the current sample position as an origin, sets g = (n 1 × d1+ n2 × d2+ n3 × d3+ n4 × d 4)/(n 1+ n2+ n3+ n 4), wherein n1 is the number of cases with the symptom index in the preset position range being a first preset symptom index, n2 is the number of cases with the symptom index in the preset position range being a second preset symptom index, n3 is the number of cases with the symptom index in the preset position range being a third preset symptom index, and n4 is the number of cases with the symptom index in the preset position range being a fourth preset symptom index, and determines the propagation condition of the current disease condition by comparing the disease degree g in the preset position range with the preset disease degree, wherein,
when G is less than or equal to G1, the identification module judges that the current disease condition is not transmitted temporarily;
when G1 is more than G and less than G2, the identification module reduces the preset position range to judge the propagation of the current disease again, wherein the identification module reduces the preset position range r to r1, and sets r1= r x (1- (G2-G) x (G-G1)/(G1 XG 2));
when G is larger than or equal to G2, the identification module judges that the current state of an illness is transmitted, and the identification module sends out a transmission early warning;
the identification module presets the incidence degree G, sets a first preset incidence degree G1 and a second preset incidence degree G2.
Specifically, when the sample binding module selects a third preset binding mode to output a result of a current sample, the identification module acquires the morbidity degree of the current sample through acquiring the morbidity condition of the current sample at a preset position of the morbidity position, compares the acquired preset morbidity degree of the morbidity degree, and determines whether the current sample disease is spread or not.
So far, the technical solutions of the present invention have been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of the present invention is obviously not limited to these specific embodiments. Equivalent changes or substitutions of related technical features can be made by those skilled in the art without departing from the principle of the invention, and the technical scheme after the changes or substitutions can fall into the protection scope of the invention.
Claims (10)
1. An application platform for rapidly identifying veterinary pathogen drug resistance is characterized by comprising:
the data acquisition module is used for acquiring veterinary drug application data, wherein the veterinary drug application data comprises animal pathogenic microorganisms applied to a veterinary drug, the geographic position of the veterinary drug, animal performance symptoms of the veterinary drug and a drug use condition;
the storage module is connected with the data acquisition module and used for storing veterinary drug application data, and comprises a database for storing veterinary drug application data and a priority calculation unit for calculating the priority of each sample, wherein the priority calculation unit calculates the sample priority p = c × w × d, wherein c is a sample identification index, w is a geographic position index of the applied veterinary drug, and d is an animal symptom index of the applied veterinary drug;
the sample binding module is connected with the storage module and is used for acquiring a pre-binding mode according to the priority of sample data;
the identification module is connected with the sample binding module and the storage module and used for judging the drug resistance condition, the propagation condition and the identification condition of the sample according to a pre-binding mode, the sample binding module acquires the current sample binding mode according to the priority of the current sample so as to output the result of the current sample,
when the sample binding module selects a second preset binding mode to output a current sample result, the identification module outputs the medication condition of the current sample or judges the drug resistance according to the severity of the current sample;
when the sample binding module selects a third preset binding mode to output a current sample result, the identification module determines the propagation degree of the current state of an illness according to the morbidity degree of the current sample within the preset range of the geographic position.
2. The application platform for rapid identification of veterinary pathogen resistance according to claim 1, wherein the priority calculating unit determines a disease index B according to the number of times of onset ba1 and the cure amount ba2 of the nucleic acid data identification result a of the current sample in the database, and sets B = ba2/ba1 × aj, where aj is the ratio of the total number of onset of the current sample species to the total number of onset samples, and compares the disease index B of the current sample with a preset disease index B to select the identification index c of the current sample, wherein,
when B is less than or equal to B1, the priority calculating unit sets a first preset identification index c1 as a current sample identification index;
when B1 is more than B and less than B2, the priority calculation unit sets a second preset identification index c2 as a current sample identification index;
when B is larger than or equal to B2, the priority calculating unit sets a third preset identification index c3 as a current sample identification index;
the priority calculating unit is used for presetting an illness state index B, setting a first preset illness state index B1 and a second preset illness state index B2, presetting an identification index c, setting a first preset identification index c1, a second preset identification index c2 and a third preset identification index c3.
3. The application platform for rapidly identifying veterinary drug resistance according to claim 2, wherein the storage module stores the position range V of historical disease samples, and the priority calculation unit obtains the geographic position V of the veterinary drug applied to the current sample when the current sample is used
V belongs to V, and the priority computing unit takes a first preset geographic position index w1 as a current sample geographic position index;
the priority calculating unit presets a geographical position coordinate w, and sets a first preset geographical position index w1 and a second preset geographical position index w2.
4. The application platform for rapidly identifying veterinary pathogen resistance according to claim 3, wherein the priority calculating unit obtains the current sample symptom and selects a symptom index d, wherein if the current sample symptom is one level, the priority calculating unit selects a first preset symptom index d1 as the current sample symptom index; if the current sample symptom is second grade, the priority calculation unit selects a second preset symptom index d2 as the current sample symptom index; if the current sample symptom is three-level, the priority calculation unit selects a second preset symptom index d3 as the current sample symptom index; if the current sample symptom is four, the priority calculating unit selects a fourth preset symptom index d4 as the current sample symptom index.
5. The application platform for rapidly identifying veterinary pathogen resistance according to claim 2, wherein the sample binding module compares the priority P of the current sample with a preset priority P, and the sample binding module selects a pre-binding mode to output the result of the current sample, wherein,
when P is less than or equal to P1, the sample binding module selects a first preset binding mode to output the result of the current sample;
when P1 is larger than P and smaller than P2, the sample binding module selects a second preset binding mode to output the result of the current sample;
when P is larger than or equal to P2, the sample binding module selects a third preset binding mode to output the result of the current sample;
the sample binding module presets a priority level P, and sets a first preset priority level P1 and a second preset priority level P2.
6. The application platform for rapidly identifying veterinary pathogenic drug resistance according to claim 5, wherein when the sample binding module selects a first preset binding mode to output the result of the current sample, the identification module outputs a recommended drug according to the animal pathogenic microorganism of the current sample applied to the veterinary drug, and the identification module outputs the recommended drug by retrieving the current drug of the pathogenic microorganism of the current sample species from the storage module.
7. The application platform for rapid identification of veterinary pathogen resistance according to claim 5, wherein when the sample binding module selects a second preset binding mode to output the result of the current sample, the identification module obtains the disease index b of the current sample and the symptom index di of the current sample to obtain the severity F of the current sample, and sets F =10 xb xdi, and the identification module compares the severity of the current sample with the preset severity F0 to determine the disease condition of the current sample, wherein,
when F is less than or equal to F0, the identification module judges that the current sample is not serious in disease state, and the identification module calls general medicines of current pathogenic microorganisms of the current sample species to output;
and when F is larger than F0, the identification module judges that the current sample is serious in illness state, and acquires the medication time of the current sample to judge the drug resistance of the current sample.
8. The platform of claim 6, wherein the identification module determines the current sample is a serious disease, and the identification module determines the pathogen resistance of the current sample by obtaining the drug time t of the current sample, wherein,
when T is less than or equal to T1, the identification module judges that the pathogen of the current sample generates no drug resistance temporarily, and the identification module outputs the historical medication of the current sample;
when T1 is more than T and less than T2, the identification module judges that the monitoring time of the current sample is shortened so as to ensure the judgment of the pathogen resistance of the current sample and simultaneously outputs the historical medication of the current sample;
when T is more than or equal to T2, the identification module judges that the pathogen of the current sample generates drug resistance, and the identification module replaces the drug of the current sample and outputs the drug;
the identification module presets medication time T, and sets first preset medication time T1 and second preset medication time T2.
9. The application platform for rapidly identifying veterinary pathogen resistance according to claim 5, wherein when the sample binding module selects a third preset binding manner to output the result of the current sample, the identification module obtains the disease degree g in a preset position range by using the current sample position as an origin, and sets g = (n 1 xd 1+ n2 xd 2+ n3 xd 3+ n4 xd 4)/(n 1+ n2+ n3+ n 4), where n1 is the number of cases in which the symptom index in the preset position range is the first preset symptom index, n2 is the number of cases in which the symptom index in the preset position range is the second preset symptom index, n3 is the number of cases in which the symptom index in the preset position range is the third preset symptom index, and n4 is the number of cases in which the symptom index in the preset position range is the fourth preset symptom index.
10. The platform of claim 9, wherein the identification module determines the current disease status according to the disease degree g within a predetermined range of positions compared with a predetermined disease degree, wherein,
when G is less than or equal to G1, the identification module judges that the current disease condition is not transmitted temporarily;
when G1 is more than G and less than G2, the identification module reduces the preset position range to judge the propagation of the current disease again, wherein the identification module reduces the preset position range r to r1, and sets r1= r x (1- (G2-G) x (G-G1)/(G1 XG 2));
when G is larger than or equal to G2, the identification module judges that the current state of an illness has spread, and the identification module sends out a spread early warning;
the identification module is used for presetting morbidity degree G, setting a first preset morbidity degree G1 and a second preset morbidity degree G2.
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