CN115631870B - 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 a veterinary pathogen resistance rapid identification application platform, which comprises a data acquisition module, a data analysis module and a data 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 the 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 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 transmission condition and the identification condition of the sample according to a pre-binding mode. The invention establishes the association of the disease identification result with the drug, the disease symptoms and conditions, the occurrence of the disease and the geographic position, and identifies the drug administration, drug resistance and transmission condition.
Description
Technical Field
The invention relates to the field of veterinary pathogen identification, in particular to a veterinary pathogen resistance rapid identification application platform.
Background
The detection of animal pathogenic microorganisms mainly comprises the steps of etiology detection, molecular biological detection, serological detection and the like, in the past, etiology is usually used, and inoculation identification is carried out by separating sample microorganisms, but the method has long time, low efficiency and low accuracy, and with the development of molecular biological technology, the detection and identification of the microorganisms causing animal morbidity are greatly improved by a DNA or RNA sequence detection technology, particularly in terms of detection efficiency and accuracy, but the current detection of animal diseases, the detection of pathogenic microorganisms and the integral identification of drug administration conditions are still in a starting stage, and most of the animal diseases are treated by adopting experience, namely planned and objective identification results cannot be formed, and the transmissibility of the diseases cannot be predicted.
Chinese patent CN101792790B discloses an analysis method of animal-derived bacterial drug resistance and a system for implementing the analysis method, which receives animal-derived bacterial data and search requests transmitted from clients, then performs search matching, and returns search results to the clients to identify animal-derived bacterial drug resistance, but it still does not solve the identification problem of sample medication advice, especially disease transmission conditions.
Disclosure of Invention
Therefore, the invention provides a rapid identification application platform for veterinary pathogen resistance, which can solve the technical problem that the drug use, drug resistance and transmission condition of the veterinary pathogen resistance cannot be determined according to the case data information.
In order to achieve the above object, the present invention provides a veterinary pathogen resistance rapid identification application platform, comprising:
the data acquisition module is used for acquiring veterinary drug application data, wherein the veterinary drug application data comprise animal pathogenic microorganisms applied to veterinary drugs, geographic positions of the applied veterinary drugs, animal expression symptoms of the applied veterinary drugs and medication conditions;
the storage module is connected with the data acquisition module and used for storing veterinary drug application data, the storage module comprises a database for storing the veterinary drug application data and a priority calculation unit for calculating the priority of each sample, and the priority calculation unit calculates the priority p=c×w×d of the sample, wherein c is a sample identification index, w is a geographical position index of the veterinary drug application, and d is an animal symptom index of the veterinary drug application;
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 is used for judging the sample drug resistance condition, the propagation condition and the identification condition according to the pre-binding mode, the sample binding module acquires the current sample binding mode according to the current sample priority to output the current sample result, when the sample binding module selects the first pre-binding mode to output the current sample result, the identification module outputs the current sample drug use result, when the sample binding module selects the second pre-binding mode to output the current sample result, the identification module outputs the current sample drug use condition or judges the drug resistance according to the current sample severity, and when the sample binding module selects the third pre-binding mode to output the current sample result, the identification module determines the current disease propagation degree according to the disease incidence degree in the geographical position pre-setting range of the current sample.
Further, the priority calculating unit determines a disease index B according to the disease frequency ba1 and the cure rate ba2 of the current sample nucleic acid data identification result a in the database, and sets b=ba2/ba1×aj, wherein aj is the ratio of the total number of the disease of the current sample species to the total number of the disease samples, the priority calculating unit 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, 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 smaller than B and smaller than B2, the priority calculating unit sets a second preset identification index c2 as a current sample identification index;
when B is more 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 presets a disease index B, a first preset disease index B1 and a second preset disease index B2, the priority calculating unit presets an identification index c, and a first preset identification index c1, a second preset identification index c2 and a third preset identification index c3 are set.
Further, the storage module stores a position range V of the historical disease sample, and the priority calculating unit obtains a geographic position V of the veterinary drug applied by the current sample when
V epsilon 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 geographic position coordinate w, and sets a first preset geographic position index w1 and a second preset geographic position index w2.
Further, the priority calculating unit obtains the current sample symptom and selects a symptom index d, wherein if the current sample symptom is first-level, the priority calculating unit selects a first preset symptom index d1 as the current sample symptom index; if the current sample symptom is of a second level, the priority calculating unit selects a second preset symptom index d2 as the current sample symptom index; if the current sample symptom is three-level, the priority calculating unit selects a third preset symptom index d3 as the current sample symptom index; if the current sample symptom is four-level, the priority calculating unit selects a fourth preset symptom index d4 as the current sample symptom index.
Further, the sample binding module compares the current sample priority P 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 less than P and less 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.
Further, when the sample binding module selects a first preset binding mode to output the result of the current sample, the identification module outputs recommended medication according to animal pathogenic microorganisms of the current sample applied to veterinary drugs, wherein the identification module outputs the current pathogenic microorganisms of the current sample species by calling the general medication of the current pathogenic microorganisms of the current sample species from the storage module.
Further, when the sample binding module selects the 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, sets f=10×b×di, and the identification module determines the disease condition of the current sample according to the severity of the current sample compared with the preset severity F0,
when F is less than or equal to F0, the identification module judges that the current sample is not ill, and the identification module invokes the general drug of the current pathogenic microorganism of the current sample species for outputting;
when F is more than F0, the identification module judges that the current sample has heavier illness state, and the identification module 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 has heavier illness state, the identification module acquires the current sample medication time t to judge the pathogen resistance 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 does not generate drug resistance temporarily, and the identification module outputs the historical drug of the current sample;
when T1 is less than T and less than T2, the identification module judges to shorten the monitoring time of the current sample so as to ensure the judgment of 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 drug and outputs the drug;
the authentication module presets a medication time T, and sets a first preset medication time T1 and a second preset medication time T2.
Further, when the sample binding module selects the third preset binding mode to output the result of the current sample, the identification module uses the current sample position as an origin, obtains the morbidity degree g in the preset position range, and sets g= (n1xd1+n2xd2+n3xd3+n4xd4)/(n1+n2+n3+n4), wherein n1 is the number of cases of the first preset symptom index in the preset position range, n2 is the number of cases of the second preset symptom index in the preset position range, n3 is the number of cases of the third preset symptom index in the preset position range, and n4 is the number of cases of the fourth preset symptom index in the preset position range.
Further, the identification module determines the current disease spread according to the disease degree g in the preset position range compared with the preset disease degree, wherein,
when G is less than or equal to G1, the identification module judges that the current illness state is not transmitted temporarily;
when G1 is less than G and less than G2, the identification module reduces the preset position range to judge the current disease spread again, wherein the identification module reduces the preset position range r to r1, and r1=rX (1- (G2-G) × (G-G1)/(G1×G 2));
when G is more than or equal to G2, the identification module judges that the current illness state is transmitted, and the identification module sends out transmission early warning;
the identification module presets the morbidity degree G, and sets a first preset morbidity degree G1 and a second preset morbidity degree G2.
Compared with the prior art, the invention has the beneficial effects that the data acquisition module for acquiring the use condition of veterinary drugs is arranged, the acquired data are transmitted into the database of the storage module for storage, and sample objects are constructed according to the classification and summarization of a large amount of acquired data, so that the correlation among various species, pathogens, symptoms and positions is realized, the follow-up tracking management is convenient, when new sample data are acquired, the 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.
In particular, according to the invention, the disease index is calculated according to the disease times and cure amount of the cases with the same identification result of the current sample and the disease rate of the species of the current sample, the situation of the species, namely the host and the disease rate is comprehensively evaluated, meanwhile, the priority calculating unit is also provided with the disease index, the priority calculating unit compares the disease index of the current sample with the preset disease index, and selects the optimal identification index, wherein if the disease index of the current sample is smaller than or equal to the first preset disease index, the current sample is not serious, the priority calculating unit selects the smaller first preset identification index as the current sample identification index, if the disease index of the current sample is between the first preset disease index and the second preset disease index, the current sample is serious, the priority calculating unit selects the second preset identification index with the intermediate value as the current sample identification index, the current sample disease index is greater than the second preset disease index, the current sample is extremely serious, and the priority calculating unit selects the larger third preset identification index as the current sample identification index, so as to evaluate the disease of the current sample.
In particular, 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 calculating unit determines the position index according to whether the current sample belongs to the position range, and in the animal breeding process, the pathogenic microorganisms are difficult to clean, the growth environment and the host can carry the pathogenic microorganisms, so that the possibility of re-disease at the once-disease position is high, and therefore, the invention determines whether the current sample occurs at the historical disease sample position according to the comparison of the position of the current sample and the coordinates of each historical disease position, so as to determine whether the current sample is caused by the transmission of the pathogenic microorganisms.
In particular, the invention determines symptom indexes according to sample symptoms, more specifically, comprehensively evaluates the symptom indexes of the samples according to the current samples and the disease conditions in the position range, wherein the sample symptoms are gradually increased, the larger the disease sample quantity at the surrounding positions is, the more serious the disease conditions are, the higher the symptom indexes are, so as to comprehensively evaluate the current sample symptom level.
In particular, the sample binding module is provided with a priority, the binding mode is selected according to the comparison of the priority calculation result of the current sample and 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 clearly identify the association relation between the result and the drug administration so as to output the identification result of 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 clearly identify the association relation between the illness state of the current sample and the drug resistance so as to output the identification result of 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 clearly identify the association relation between the position of the current sample and the transmitted so as to output the identification result of whether the pathogenic microorganism has transmitted.
In particular, the invention selects the second preset binding mode to determine whether the current sample has drug resistance to clearly apply drugs, the identification module comprehensively evaluates whether the current sample has serious illness state according to the illness state index and symptom index of the current sample, wherein when the identification module obtains the illness state of the current sample to be less than or equal to the preset severity degree, the illness state of the current sample is not serious, the identification module does not regulate and control the drug application of the current sample, still selects the conventional drug application of the current sample, when the identification module obtains the illness state of the current sample to be greater than the preset severity degree, the identification module judges whether the current sample has drug resistance to the currently applied drugs according to the time of using the current sample, if the current sample has short time of using the current sample, the identification module temporarily cannot judge the current sample has drug resistance to the currently applied drugs, so that the current sample is judged to be output further, if the current sample has long time of using the current sample, the identification module judges that the monitoring time of the current sample is shortened, namely the time of next pair of data acquisition is shortened, so that the current sample has drug resistance to be ensured, and meanwhile, if the current sample has long time of using the current sample and the illness state of the current sample is judged that the illness state of the current sample has little drug resistance to change, if the current sample has serious cause and the illness state of the current sample is judged that the current sample has serious cause.
Particularly, when the sample binding module selects the third preset binding mode to output the result of the current sample, the identification module acquires the morbidity of the current sample by acquiring the morbidity of the preset position of the morbidity position of the current sample, and compares the acquired morbidity of the current sample with the acquired morbidity of the current sample, so as to determine whether the current sample is already transmitted, wherein when the morbidity of the current sample is smaller than or equal to the first preset morbidity, the identification module determines that the current disease is not transmitted temporarily, when the morbidity of the current sample is between the first preset morbidity and the second preset morbidity, the identification module further determines whether the current sample is transmitted by narrowing the preset range, and when the morbidity of the current sample is larger than or equal to the second preset morbidity, the identification module determines that the current disease is already transmitted and sends a transmission early warning.
Drawings
FIG. 1 is a schematic diagram of an application platform for rapid identification of veterinary pathogen resistance according to an embodiment of the invention.
Detailed Description
In order that the objects and advantages of the invention will become more apparent, the invention will be further described with reference to the following examples; it should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of 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 merely for explaining the technical principles of the present invention, and are not intended to limit the scope of the present invention.
Referring to fig. 1, a schematic diagram of a veterinary pathogen resistance rapid identification application platform according to an embodiment of the invention includes,
the data acquisition module is used for acquiring veterinary drug application data, wherein the veterinary drug application data comprise animal pathogenic microorganisms applied to veterinary drugs, geographic positions applied to the veterinary drugs, animal expression symptoms applied to the veterinary drugs and medication conditions;
the storage module is connected with the data acquisition module and used for storing veterinary drug application data, the storage module comprises a database for storing veterinary drug application data and a priority calculation unit for calculating the priority of each sample, and the priority calculation unit calculates the priority p=c×w×d of the sample, wherein w is a geographic position index of the veterinary drug application, and d is an animal symptom index of the veterinary drug application;
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;
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 transmission condition and the identification condition of the sample according to a pre-binding mode.
Specifically, the invention is provided with a data acquisition module for acquiring the use condition of veterinary drugs, transmits acquired data into a database of a storage module for storage, classifies and gathers according to a large amount of acquired data, constructs sample objects, realizes the association among various species, pathogens, diseases and positions, is convenient for subsequent tracking management, and when new sample data is acquired, a priority calculation unit in the storage module acquires the priority of a current sample and selects a pre-binding mode according to the parameter value of the priority.
Specifically, the sample of the embodiment of the invention comprises a blood, tissue and stool sample of a veterinary animal, and the dominant bacterial population of the sample microorganism is determined as a nucleic acid identification result by sequencing DNA or RNA nucleic acid data in the sample, more specifically, the embodiment of the invention determines the pathogenic microorganism existing in the sample according to the nucleic acid sequencing data, and sets the maximum pathogenic microorganism amount as the dominant bacterial population of the sample.
Specifically, the embodiment of the invention does not limit the classification, summarization and construction of the sample object of the collected data, as long as the sample object can meet the query of species, pathogens, diseases and related information, and provides a preferred implementation scheme, wherein the collected data in the database is referred to as a table one, and a plurality of groups are arranged, wherein the first group is mainly of species, the construction of the species object data group is referred to as a table two, the second group is mainly of diseases, the construction of the disease object group is referred to as a table three, the third group is mainly of geographic positions, and the construction of the geographic position object group is referred to as a table four.
First, sample data information
Wherein, the position I coordinates are 116.81 and 40.30, the position II coordinates are 116.20 and 40.62, the position III coordinates are 115.79,
39.74, position iv as 116.81, 40.30 and position v as 116.05, 39.70.
Table II, data set of species objects
TABLE three, disease subject data set
Table IV, geographic location object data set
The priority calculating unit determines a disease index b according to the disease times ba1 and the cure rate ba2 of the current sample nucleic acid data identification result a in the database, and sets b=ba2/ba1×aj, wherein aj is the ratio of the total disease number of the current sample species to the total disease sample.
Specifically, the current sample of the embodiment of the invention is pigs, the pig manure microorganisms of the sample are extracted for detection, the detection result shows that the dominant bacterial population causing diseases in the pig manure is escherichia coli, the frequency of occurrence of animal diseases caused by the escherichia coli is 651 times, the cure rate is 487 times, wherein the species is pigs, the occurrence frequency 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 index B of the current sample with a preset disease index B to select an 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 smaller than B and smaller than B2, the priority calculating unit sets a second preset identification index c2 as a current sample identification index;
when B is more 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 presets a disease index B, a first preset disease index B1 and a second preset disease index B2, the priority calculating unit presets an identification index c, and a first preset identification index c1, a second preset identification index c2 and a third preset identification index c3 are set.
Specifically, the embodiment of the invention does not limit specific parameters of disease indexes and specific parameters of identification indexes, and can be specifically set according to the characteristics of data acquisition, namely, the current platform is applied to a large-scale farm, the acquired data volume is large, and the data of the farm can reflect the general situation, so that the disease indexes are set to 0.2-0.6, wherein the first preset disease index is 0.2-0.4, the second preset disease 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 disease period of the cultivation is encountered, the set disease index and the identification index are correspondingly changed, wherein the disease index is 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 index is 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, according to the invention, the disease index is calculated according to the disease times and cure amount of the cases with the same identification result of the current sample and the disease rate of the species of the current sample, the situation of the species, namely the host and the disease rate is comprehensively evaluated, meanwhile, the priority calculating unit is also provided with the disease index, the priority calculating unit compares the disease index of the current sample with the preset disease index, and selects the optimal identification index, wherein if the disease index of the current sample is smaller than or equal to the first preset disease index, the current sample is not serious, the priority calculating unit selects the smaller first preset identification index as the current sample identification index, if the disease index of the current sample is between the first preset disease index and the second preset disease index, the current sample is serious, the priority calculating unit selects the second preset identification index with the intermediate value as the current sample identification index, the current sample disease index is greater than the second preset disease index, the current sample is extremely serious, and the priority calculating unit selects the larger third preset identification index as the current sample identification index, so as to evaluate the disease of the current sample.
Wherein the storage module stores a position range V of a historical disease sample, and the priority calculating unit obtains a geographic position V of the veterinary drug applied to the current sample when
V epsilon 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 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 position ranges of the peripheral preset positions of the historical disease sample are set as the disease ranges, the priority calculating unit determines the position index according to whether the current sample belongs to the position range, and in the animal breeding process, the pathogenic microorganisms are difficult to clean, the growth environment and the host can carry the pathogenic microorganisms, so that the possibility of re-disease at the once-disease position is high, and therefore, the invention determines whether the current sample occurs at the historical disease sample position according to the comparison of the position of the current sample and the coordinates of each historical disease position, so as to determine whether the current sample is caused by the transmission of the pathogenic microorganisms.
Specifically, the embodiment of the present invention does not limit the position range of the historical disease sample, which may divide the position of the disease sample by a preset distance with the disease sample as a center point, and further, the present invention does not limit the geographical position index, and the embodiment of the present invention provides a preferred embodiment, where the first preset geographical position index w1 is 10, and the second preset geographical position index w2 is 1.
The priority calculating unit obtains the current sample symptom and selects a symptom index d, wherein if the current sample symptom is first-level, the priority calculating unit selects a first preset symptom index d1 as the current sample symptom index; if the current sample symptom is of a second level, the priority calculating unit selects a second preset symptom index d2 as the current sample symptom index; if the current sample symptom is three-level, the priority calculating unit selects a third preset symptom index d3 as the current sample symptom index; if the current sample symptom is four-level, the priority calculating unit selects a fourth preset symptom index d4 as the current sample symptom index.
Specifically, the embodiment of the 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 in the current geographic position shows the symptom, the current sample symptom is evaluated as a first level, if the current sample has more than two expression symptoms and only one sample in the current geographic position shows the symptom, the current sample symptom is evaluated as a second level, if the current sample has more than two expression symptoms and more than two samples in the current geographic position show the symptom, the current sample symptom is evaluated as a third level, and if the current sample has the expression symptom and the current geographic position has a death case, the current sample symptom is evaluated as a fourth level.
Specifically, the invention determines the symptom index according to the sample symptoms, more specifically, comprehensively evaluates the symptom index of the sample according to the current sample and the disease conditions in the position range, gradually increases the sample symptoms, and increases the symptom index according to the larger the disease sample quantity of the surrounding positions and the serious disease conditions, thereby comprehensively evaluating the current sample symptom level.
Specifically, the embodiment of the invention establishes a pre-binding mode, wherein the first binding mode is the association relation between an identification result and medication so as to output the identification result of medication, the second binding mode is the association relation between the condition of a current sample and the condition of medication so as to output the identification result of medication, and the third binding mode is the association relation between the position of the current sample and transmission so as to output the identification result of whether the pathogenic microorganism is transmitted.
The sample binding module compares the current sample priority P 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 less than P and less 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, a priority is set in a sample binding module, a binding mode is selected according to the comparison of a priority calculation result of a current sample and a preset priority, wherein when the priority of the current sample acquired by the sample binding module is smaller than or equal to a first preset priority, the sample binding module selects the first preset binding mode to clearly identify the association relation between the result and medication so as to output the identification result of drug use, when the priority of the current sample acquired by the sample binding module is between the first preset priority and a second preset priority, the sample binding module selects the second preset binding mode to clearly identify the association relation between the illness state of the current sample and the drug resistance so as to output the identification result of 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 clearly identify the association relation between the position of the current sample and the transmission so as to output the identification result of whether the pathogenic microorganism has spread.
When the sample binding module selects a first preset binding mode to output the result of the current sample, the identification module outputs recommended medication according to animal pathogenic microorganisms of the current sample applied to veterinary drugs, wherein the identification module outputs the current pathogenic microorganisms of the current sample species by calling the general medication of the current pathogenic microorganisms of the current sample species 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 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 judges the disease condition of the current sample according to the comparison of the severity of the current sample and the preset severity F0,
when F is less than or equal to F0, the identification module judges that the current sample is not ill, and the identification module invokes the general drug of the current pathogenic microorganism of the current sample species for outputting;
when F is more than F0, the identification module judges that the current sample has heavier illness state, and the identification module acquires the medication time of the current sample to judge the drug resistance of the current sample.
In particular, the identification module judges that the current sample has heavier illness state, the identification module acquires the current sample medication time t to judge the pathogen resistance 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 does not generate drug resistance temporarily, and the identification module outputs the historical drug of the current sample;
when T1 is less than T and less than T2, the identification module judges to shorten the monitoring time of the current sample so as to ensure the judgment of 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 drug and outputs the drug;
the authentication module presets a medication time T, and sets a first preset medication time T1 and a second preset medication time T2.
Specifically, the administration time in the embodiment of the invention is the total time of using the current medicine by the current sample, namely, the time of using the medicine for the first time of illness of the current sample is 3 days, the time of using the medicine for the second time of illness is 5 days, the time of using the medicine for the present illness is 1 day, and the administration time is 9 days.
Specifically, the second preset binding mode is selected by the sample binding module to determine whether the current sample has drug resistance or not so as to clearly apply drugs, and the identification module comprehensively evaluates whether the current sample has serious illness state according to the illness state index and the symptom index of the current sample, wherein when the severity of the illness state of the current sample acquired by the identification module is smaller than or equal to the preset severity, the illness state of the current sample is not serious, the identification module does not regulate and control the drugs of the current sample, the conventional drugs of the current sample are still selected, when the severity of the illness state of the current sample acquired by the identification module is larger than the preset severity, the illness state of the current sample is heavier, the identification module judges whether the current sample has drug resistance to the currently used drugs according to the time of the current sample using drugs, if the current sample using time of the current sample is shorter, the identification module temporarily cannot judge the current sample having drug resistance to the current drugs, so that the current drugs are further judged, if the current sample using time of the current sample using the current drugs is longer, the identification module judges that the next pair of data acquisition time is shortened, so that the current sample pathogen resistance is ensured, and meanwhile, if the current sample using the current sample is seriously used for the current sample is judged to have the disease resistance.
When the sample binding module selects a third preset binding mode to output the result of the current sample, the identification module takes the current sample position as an origin to obtain the morbidity degree g in a preset position range, sets g= (n1xd1+n2xd2+n3xd3+n4xd4)/(n1+n2+n3+n4), wherein n1 is the case number of the first preset symptom index in the preset position range, n2 is the case number of the second preset symptom index in the preset position range, n3 is the case number of the third preset symptom index in the preset position range, n4 is the case number of the fourth preset symptom index in the preset position range, and the identification module determines the spreading condition of the current illness state according to the morbidity degree g in the preset position range and the preset morbidity degree, wherein,
when G is less than or equal to G1, the identification module judges that the current illness state is not transmitted temporarily;
when G1 is less than G and less than G2, the identification module reduces the preset position range to judge the current disease spread again, wherein the identification module reduces the preset position range r to r1, and r1=rX (1- (G2-G) × (G-G1)/(G1×G 2));
when G is more than or equal to G2, the identification module judges that the current illness state is transmitted, and the identification module sends out transmission early warning;
the identification module presets the morbidity degree G, and sets a first preset morbidity degree G1 and a second preset morbidity degree G2.
Specifically, when the sample binding module selects the third preset binding mode to output the result of the current sample, the identification module acquires the morbidity of the current sample by acquiring the morbidity of the preset position of the morbidity position of the current sample, compares the acquired morbidity of the current sample with the acquired morbidity of the current sample, and determines whether the current sample is already transmitted, wherein when the morbidity of the current sample acquired by the identification module is smaller than or equal to the first preset morbidity, the identification module determines that the current disease is not transmitted temporarily, when the morbidity of the current sample acquired by the identification module is between the first preset morbidity and the second preset morbidity, the identification module further determines whether the current sample is transmitted by narrowing the preset range, and when the morbidity of the current sample acquired by the identification module is larger than or equal to the second preset morbidity, the identification module determines that the current disease is already transmitted and sends a transmission early warning.
Thus far, the technical solution of the present invention has 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 protection of the present invention is not limited to these specific embodiments. Equivalent modifications and substitutions for related technical features may be made by those skilled in the art without departing from the principles of the present invention, and such modifications and substitutions will be within the scope of the present invention.
Claims (5)
1. A veterinary pathogen resistance rapid identification application platform, comprising:
the data acquisition module is used for acquiring veterinary drug application data, wherein the veterinary drug application data comprise animal pathogenic microorganisms applied to veterinary drugs, geographic positions of the applied veterinary drugs, animal expression symptoms of the applied veterinary drugs and medication conditions;
the storage module is connected with the data acquisition module and used for storing veterinary drug application data, the storage module comprises a database for storing the veterinary drug application data and a priority calculation unit for calculating the priority of each sample, and the priority calculation unit calculates the priority p=c×w×d of the sample, wherein c is a sample identification index, w is a geographical position index of the veterinary drug application, and d is an animal symptom index of the veterinary drug application;
the sample binding module is connected with the storage module and is used for acquiring a preset binding mode according to the priority of sample data;
the identification module is connected with the sample binding module and the storage module and is used for judging the sample drug resistance condition, the propagation condition and the identification condition according to a preset binding mode, the sample binding module acquires the current sample binding mode according to the current sample priority 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 transmission degree of the current illness state according to the illness degree in the preset range of the geographic position of the current sample;
the sample binding module compares the current sample priority P with a preset priority P, and the sample binding module selects a preset 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 less than P and less 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;
when the sample binding module selects a first preset binding mode to output the result of the current sample, the identification module outputs recommended medication according to animal pathogenic microorganism output of the current sample applied to veterinary drugs, wherein the identification module outputs the current pathogenic microorganism universal medication of the current sample species by calling the current pathogenic microorganism universal medication of the current sample species from the storage module;
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, sets f=10×b×di, and judges the disease condition of the current sample according to the comparison of the severity of the current sample and the preset severity F0,
when F is less than or equal to F0, the identification module judges that the current sample is not ill, and the identification module invokes the general medication of the current pathogenic microorganism of the current sample species for output;
when F is more than F0, the identification module judges that the current sample has heavier illness state, and the identification module acquires the medication time of the current sample to judge the drug resistance of the current sample;
when the sample binding module selects a third preset binding mode to output the result of the current sample, the identification module takes the current sample position as an origin, acquires the morbidity degree g in a preset position range, and sets g= (n1xd1+n2xd2+n3xd3+n4xd4)/(n1+n2+n3+n4), wherein n1 is the number of cases of the first preset symptom index in the preset position range, n2 is the number of cases of the second preset symptom index in the preset position range, n3 is the number of cases of the third preset symptom index in the preset position range, and n4 is the number of cases of the fourth preset symptom index in the preset position range;
the priority calculating unit obtains the current sample symptom and selects a current sample symptom index di, wherein if the current sample symptom is first-level, the priority calculating unit selects a first preset symptom index d1 as the current sample symptom index; if the current sample symptom is of a second level, the priority calculating unit selects a second preset symptom index d2 as the current sample symptom index; if the current sample symptom is three-level, the priority calculating unit selects a third preset symptom index d3 as the current sample symptom index; if the current sample symptom is four-level, the priority calculating unit selects a fourth preset symptom index d4 as the current sample symptom index.
2. The rapid identification application platform for veterinary pathogen resistance according to claim 1, wherein the priority calculating unit determines a disease index B according to the number of times ba1 of the current sample nucleic acid data identification result a and the cure rate ba2 in the database, and sets b=ba2/ba1×aj, wherein aj is the ratio of the total number of the disease of the current sample species to the total number of the disease samples, and the priority calculating unit 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, 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 smaller than B and smaller than B2, the priority calculating unit sets a second preset identification index c2 as a current sample identification index;
when B is more 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 presets a disease index B, a first preset disease index B1 and a second preset disease index B2, the priority calculating unit presets an identification index c, and a first preset identification index c1, a second preset identification index c2 and a third preset identification index c3 are set.
3. The rapid identification of veterinary pathogen resistance application platform of claim 2, wherein the storage module stores a range of positions V of historical pathogen specimens, and the priority calculation unit obtains a current specimen application veterinary medicine geographic position V when
V epsilon 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 geographic position coordinate w, and sets a first preset geographic position index w1 and a second preset geographic position index w2.
4. The rapid identification of veterinary pathogen resistance application platform of claim 1, wherein the identification module determines that the current sample is relatively heavy, the identification module obtains the current sample administration time t to determine the pathogen resistance 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 does not generate drug resistance temporarily, and the identification module outputs the historical drug of the current sample;
when T1 is less than T and less than T2, the identification module judges to shorten the monitoring time of the current sample so as to ensure the judgment of 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 drug and outputs the drug;
the authentication module presets a medication time T, and sets a first preset medication time T1 and a second preset medication time T2.
5. The rapid identification of veterinary pathogen resistance application platform of claim 1 wherein the identification module determines the spread of the current condition based on the extent of disease g within a predetermined location range as compared to a predetermined extent of disease, wherein,
when G is less than or equal to G1, the identification module judges that the current illness state is not transmitted temporarily;
when G1 is less than G and less than G2, the identification module reduces the preset position range to judge the current disease spread again, wherein the identification module reduces the preset position range r to r1, and r1=rX (1- (G2-G) × (G-G1)/(G1×G 2));
when G is more than or equal to G2, the identification module judges that the current illness state is transmitted, and the identification module sends out transmission early warning;
the identification module presets the morbidity degree G, and sets a first preset morbidity degree G1 and a second preset morbidity degree G2.
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