CN114444928B - Pathogenic microorganism high-risk area detection system - Google Patents
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Abstract
The invention discloses a pathogenic microorganism high-risk area detection system, and relates to the technical field of pathogenic microorganism monitoring. The administrative region dividing module divides the administrative region of the electronic map; the map marking module is used for extracting a geographic position corresponding to the detection result and marking the geographic position in a corresponding administrative area on the electronic map; the second judging module is used for counting the number of positive samples in the administrative region aiming at the administrative region with the lowest level, and marking the administrative region with the lowest level as a high risk region if the number of positive samples in the administrative region is larger than a corresponding threshold value; and the third judging module is used for counting the number of positive samples in administrative areas of other levels, and marking the administrative areas of other levels as high risk areas if the uniformity of the distribution of the high risk areas in the administrative areas of the next level is larger than a corresponding threshold value. The invention can mark the high risk area according to the detection result so as to reasonably prevent and control distribution of materials and personnel and avoid further spread of epidemic situation.
Description
Cross Reference to Related Applications
The application is based on the application number 2021101448941, and the application date is as follows: 2021, 02 and the name of the application is: a divisional application of a real-time monitoring system of a pathogenic microorganism Internet of things is provided.
Technical Field
The invention relates to the technical field of pathogenic microorganism monitoring, in particular to a pathogenic microorganism high-risk area detection system.
Background
Pathogenic microorganisms are microorganisms that cause infections and even infectious diseases, and monitoring of pathogenic microorganisms plays a vital role in the control system of infectious diseases.
The current pathogenic microorganism monitoring system detects samples through detection equipment, obtains experimental data and reports the experimental data through a manual recording system. Most of detection devices have no network function, detection operation is complex, and professional requirements on personnel are high; after the detection is finished, the equipment can only locally generate a detection report and cannot transmit data in real time; the experimenter needs to collect reports of experiments, and the reports are manually recorded and reported after the reports are arranged, so that the whole monitoring system flow is greatly influenced by human factors, and the authenticity and timeliness of the data are difficult to guarantee. The current pathogenic microorganism monitoring system is too complex, is easily influenced by human factors from experimental operation to result report, is difficult to ensure that the collected detection result is real and effective, and greatly increases the difficulty of timely prevention and control of infectious diseases. Therefore, how to realize accurate judgment after pathogenic microorganism detection, timely and effectively realize epidemic monitoring and early warning, and facilitate later-stage guidance of epidemic prevention and control is a difficult problem to be solved.
Disclosure of Invention
The invention aims to provide a pathogenic microorganism Internet of things real-time monitoring system, which is used for realizing the real-time monitoring of pathogenic microorganisms based on the Internet of things, realizing timely early warning and guiding epidemic situation prevention and control effects.
In order to achieve the above purpose, the present invention provides the following technical solutions:
A pathogen microorganism Internet of things real-time monitoring system comprises a fluorescence detection module, a data transmission module, a data processing module, a first judging module and an early warning module;
The fluorescence detection module is used for carrying out PCR amplification on the sample and detecting the fluorescence average value of each PCR amplification cycle;
the data transmission module is used for transmitting the detected fluorescence mean value to the data processing module;
The data processing module is used for dynamically calculating the amplification index of the fluorescence mean value in each moving window based on moving window calculation;
the first judging module judges that the detection result of the sample is positive when the amplification index meets a preset threshold value;
And the early warning module is used for sending out an alarm and uploading the detection result to the disease control center when detecting that the sample is positive.
Compared with the prior art, the invention has the beneficial effects that: according to the invention, detection of pathogenic microorganisms is combined with the Internet of things, so that the complexity of manually recording data is avoided, and the timeliness of the data is ensured; meanwhile, the invention adopts a moving window mode to carry out positive judgment, so that one-time judgment can be realized without outputting one-time fluorescence mean value, and early warning and prevention and control measures can be realized in the fastest time.
Further, the specific processing steps of the data processing module are as follows:
CL1, taking the i-th fluorescence mean value to the i+k-th fluorescence mean value as i-th group judgment data;
CL2, calculating the increment Δr ij of the jth fluorescence mean relative to the ith fluorescence mean:
ΔRij＝Ri+j-Ri
Wherein R i is the ith fluorescence mean value, j is more than or equal to 1 and less than or equal to k;
CL3, k= [1, K ] is plotted on the abscissa, ln (Δr ij) is plotted on the ordinate;
CL4, solving the amplification indexes of the i-th group judgment data, including a variation index CV i, a slope i and a correlation index ρ i:
Where Cov (K, ln (ΔR ij)) is the covariance of K and ln (ΔR ij), var [ K ] is the variance of K, var [ ln (ΔR ij) ] is the variance of ln (ΔR ij).
Further, the judgment standard of the first judgment module is: when the variation index CV i, the slope i and the correlation index ρ i are simultaneously larger than the corresponding threshold values, the sample is judged to be positive.
Further, the threshold value of the variation index CV i is 0.044, the threshold value of the slope i is 0.235, and the threshold value of the correlation index ρ i is 0.963.
Further, the system also comprises a positioning module, wherein the positioning module detects the geographic position at fixed time and uploads the geographic position together with the detection result to realize the positioning statistics of the positive sample.
Further, the disease control center is provided with an administrative region dividing module, a map marking module, a second judging module and a third judging module; the early warning prompt is convenient for the administrative areas with different levels.
The administrative region dividing module divides the electronic map according to administrative regions of different levels;
The map marking module is used for extracting the geographic position corresponding to the detection result and marking the geographic position in the administrative region corresponding to the electronic map;
The second judging module is used for counting the number of positive samples in the administrative region aiming at the administrative region with the lowest level, and if the number of positive samples in the administrative region is larger than a set threshold value with the lowest level, marking the administrative region with the lowest level as a high risk region;
And the third judging module is used for counting administrative areas of other levels, counting the number of positive samples in the administrative areas, calculating the uniformity of the distribution of the high risk areas in the next-level administrative area subordinate to the administrative areas if the number of positive samples is larger than a set corresponding level threshold, and marking the administrative areas of other levels as the high risk areas if the uniformity is larger than the set uniformity threshold.
Further, the method for calculating the uniformity is as follows:
TP1: counting the next administrative area which is subordinate to the administrative area of the current level and marked as a high risk area;
TP2: if two or more than two adjacent next-level administrative areas are high risk areas, making a common circumcircle;
TP3: calculating the uniformity ρ:
S 0 is the area of the administrative region of the current level; s single is the area of the single secondary administrative area marked as a high risk area; s common is the area of the common circumscribed circle; sigma is a sum operator, and a union of multiple areas is calculated.
Further, the device also comprises a reagent bottle, a two-dimensional code bound with the reagent bottle and a two-dimensional code identification module; the misoperation of setting test parameters by non-professional operators is effectively avoided.
The reagent bottle is filled with a reagent for fluorescence detection;
the two-dimensional code is used as a unique identification code of the reagent, and is recorded with the experimental steps, parameters, pathogen type detection and production date of the reagent;
The two-dimensional code identification module is used for identifying the two-dimensional code and displaying the recorded content of the two-dimensional code.
Further, the fluorescent light detection device also comprises an analog-to-digital conversion module, and the analog signal of the fluorescence mean value detected by the fluorescent light detection module is converted into a digital signal.
Drawings
Fig. 1 is a schematic overall structure of an embodiment of the present invention.
FIG. 2 is a schematic diagram illustrating a uniformity calculation according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely, and it is apparent that the described embodiments are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the invention provides a pathogenic microorganism internet of things real-time monitoring system, which comprises a local monitoring terminal and a disease control center; the local monitoring terminals realize local pathogenic microorganism detection and transmit detection results to the disease control center, and the disease control center performs summarizing analysis on the detection results transmitted by the local monitoring terminals to realize timely regional early warning.
The local monitoring terminal comprises a fluorescence detection module, an analog-to-digital conversion module, a data transmission module, a data processing module, a first judging module, an early warning module and a positioning module.
And the fluorescence detection module is used for carrying out PCR amplification on the sample and detecting the fluorescence average value of each PCR amplification cycle. The optical conduction and detection mode adopted by the fluorescence detection module is conduction through an optical fiber system, and has good light conduction property, so that the detected fluorescence value is more accurate after PCR amplification. And in the fluorescence detection link, a silicon diode of Japanese pine is adopted. The sensor has the characteristics of good reliability, high stability and the like, and can provide a guarantee on the performance of the sensor.
In addition, the hardware scheme mainly utilizes a control temperature algorithm of a main control chip and a conversion algorithm of fluorescence acquisition in performance control, so that the performance is stable, the inter-hole difference is controlled within 3%, and the stability CV is controlled within 3%. The temperature control precision is high to reach a deviation range of 1 degree, and a mature sensor PT100 (class A deviation) is mainly adopted, so that the system can control the temperature better. The android 4.4 system is selected on the operating system, and the system has the advantages of stable performance, mature technology and the like, and can provide a user with excellent operating experience.
All modules of the hardware scheme are independently provided with control chips, and the modules communicate through UART serial ports, so that the system is stable, and the quantity of connecting wires is small. The total control modules are 3, one is a temperature control module, one is an LED lamp excitation light control module, and the other is a central control board module, and the central control board module comprises a fluorescence acquisition module and a heat cover temperature control module.
During the experiment, 6 fluorescence values were read per PCR amplification cycle and averaged to reduce data errors.
It is worth mentioning that when detecting pathogenic microorganisms, strict requirements are applied to the adopted reagents, and staff trained for a long time are usually required to distinguish and operate the reagents, so that under the condition that epidemic situation occurs in a large area, the situation that professionals are in shortage is unavoidable. In another embodiment of the invention, the device further comprises a reagent bottle, a two-dimensional code bound with the reagent bottle and a two-dimensional code identification module; the misoperation of setting test parameters by non-professional operators is effectively avoided. The reagent bottle is filled with a reagent for fluorescence detection; the two-dimensional code is used as a unique identification code of the reagent to be attached to a reagent bottle, and the experimental steps, parameters, pathogen type detection and production date of the reagent are recorded; and the two-dimensional code identification module is used for identifying the two-dimensional code and displaying the recorded content of the two-dimensional code. Therefore, non-professional personnel can use the pathogenic microorganism detection instrument through simple training, and can also screen out unused reagents for a long time to be used as waste according to the production date of the reagents, so that experimental errors caused by using invalid reagents are avoided.
The analog-to-digital conversion module converts the analog signal of the fluorescence mean value detected by the fluorescence detection module into a digital signal.
And the data transmission module is used for transmitting the detected fluorescence mean value to the data processing module.
The data processing module is used for dynamically calculating the amplification index of the fluorescence mean value in each moving window based on moving window calculation;
specifically, the specific processing steps of the data processing module are as follows:
CL1, taking the i-th fluorescence mean value to the i+k-th fluorescence mean value as i-th group judgment data; for example, it takes about 40-50 minutes to complete an experiment, and each experiment will transmit a fluorescence average value of 40 times through the serial port, k being 4. Then the fluorescence average value from the 1 st fluorescence average value to the 5 th fluorescence average value is used as the 1 st group judgment data, the fluorescence average value from 2 to 6 times is used as the 2 nd group judgment data, the fluorescence average value from 3 to 7 times is used as the 3 rd group judgment data, the fluorescence average value from 36 to 40 times is used as the 36 th group judgment data, and 36 groups of judgment data are all used. The following processing steps CL2 to CL4 are sequentially performed for each set of judgment data:
CL2, calculating the increment Δr ij of the jth fluorescence mean relative to the ith fluorescence mean:
ΔRij＝Ri+j-Ri
Wherein R i is the ith fluorescence mean value, j is more than or equal to 1 and less than or equal to k;
CL3, k= [1, K ] is plotted on the abscissa, ln (Δr ij) is plotted on the ordinate;
CL4, solving the amplification indexes of the i-th group judgment data, including a variation index CV i, a slope i and a correlation index ρ i:
Where Cov (K, ln (ΔR ij)) is the covariance of K and ln (ΔR ij), var [ K ] is the variance of K, var [ ln (ΔR ij) ] is the variance of ln (ΔR ij).
To this end, a set of amplification indices is obtained at each transmission of the fluorescence mean.
And the first judging module judges that the detection result of the sample is positive when the variation index CV i, the slope i and the correlation index rho i are simultaneously larger than the corresponding threshold values. Preferably, the threshold value of the variation index CV i is 0.044, the threshold value of the slope i is 0.235, and the threshold value of the correlation index ρ i is 0.963. Therefore, when each PCR amplification cycle outputs a fluorescence mean value, a detection result can be output once, sample data with positive detection results can be screened out at the first time, and timely early warning prevention and control measures are carried out.
And the early warning module is used for sending out an alarm and uploading the detection result to the disease control center when detecting that the sample is positive.
And the positioning module is used for detecting the geographic position at fixed time, uploading the geographic position together with the detection result, and realizing positioning statistics of the positive sample, so that later regional early warning is facilitated.
The disease control center is provided with an electronic map, an administrative region dividing module, a map marking module, a second judging module and a third judging module; the early warning prompt is convenient for the administrative areas with different levels.
The administrative region dividing module divides the electronic map according to administrative regions of different levels, and specific administrative region division contents are based on different regions, and are described below by taking level division of provinces, cities, counties, towns, villages as an example.
And the map marking module is used for extracting the geographic position corresponding to the detection result and marking the geographic position in the administrative region corresponding to the electronic map.
And the second judging module is used for counting the number of positive samples in the administrative region (village) with the lowest level, and marking the administrative region with the lowest level as a high risk region if the number of positive samples in the administrative region is larger than a set threshold value with the lowest level. If the set lowest level threshold is 5, when the number of samples with positive detection results of pathogenic microorganisms in a certain village reaches 6, the village is marked as a high risk area.
And the third judging module is used for counting administrative areas of other levels, counting the number of positive samples in the administrative areas, calculating the uniformity of the distribution of the high risk areas in the next-level administrative area subordinate to the administrative areas if the number of positive samples is larger than a set corresponding level threshold, and marking the administrative areas of other levels as the high risk areas if the uniformity is larger than the set uniformity threshold. For example, a country threshold of a country is set to 20 persons, and a uniformity threshold is set to 0.5. Marking the country as a high risk area when the total number of positive samples of all villages belonging to the country reaches 21 people and the uniformity of the distribution of the high risk areas of the villages reaches more than 0.5; the same applies to high risk marks in towns, counties, cities, provinces.
In this embodiment, the uniformity is used to characterize uniformity of a high risk area in a next-level administrative area subordinate to the administrative area. The smaller the uniformity, the more concentrated the positive samples reflecting pathogenic microorganisms, which only occur in a few specific villages, the villages are not marked as high risk areas, otherwise, the maldistribution of prevention and control personnel and materials is caused. On the contrary, the larger the uniformity is, the wider the distribution of positive samples reflecting pathogenic microorganisms is, at this time, the centralized prevention and control of only a few villages is obviously insufficient, and the whole villages should be prevented and controlled.
Specifically, the method for calculating the uniformity is as follows:
TP1: the next level administrative area marked as a high risk area is counted among the administrative areas of the current level. As shown in fig. 2, a country includes 12 villages in total from A1 to a12, where A3, A6, A7, a12 are high risk areas.
TP2: if two or more than two adjacent next-level administrative areas are high risk areas, making a common circumcircle; a3, A6, A7 in FIG. 2 are in a geographical relationship bordering each other, thus making their common circumscribed circles.
TP3: calculating the uniformity ρ:
S 0 is the area of the administrative region of the current level; s single is the area of the single secondary administrative area marked as a high risk area; s common is the area of the common circumscribed circle; sigma is a sum operator, and a union of multiple areas is calculated. In this embodiment, a first union of the areas of all the first-level administrative regions, which are individually marked as high risk regions, is calculated independently, a second union of the areas of all the common circumscribed circles is calculated independently, and then the first union and the second union are calculated again to obtain a third union. And finally, taking the intersection of the third union and the total area of the country as a numerator, and solving the total area of the country as a denominator to obtain the uniformity rho. The area of the circumcircle is adopted to represent the risk degree that two or more than two adjacent secondary administrative areas are high risk areas, and the risk degree is improved because the two or more than two adjacent high risk areas are bordered with each other, so that potential large-area infection hidden danger exists, and the sum of the areas of the high risk areas is replaced by the area of the circumcircle.
The disease control center can reasonably prevent and control distribution of materials and personnel according to the actual situation and the high risk area marked in the electronic map, so that further spread of epidemic situation is avoided.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.
Claims (4)
1. A detection system for a high-risk area of pathogenic microorganisms is characterized in that,
The pathogenic microorganism high-risk area detection system is a pathogenic microorganism Internet of things real-time monitoring system and comprises a fluorescence detection module, a data transmission module, a data processing module, a first judgment module and an early warning module;
The fluorescence detection module is used for carrying out PCR amplification on the sample and detecting the fluorescence average value of each PCR amplification cycle;
the data transmission module is used for transmitting the detected fluorescence mean value to the data processing module;
The data processing module is used for dynamically calculating the amplification index of the fluorescence mean value in each moving window based on moving window calculation;
the first judging module judges that the detection result of the sample is positive when the amplification index meets a preset threshold value;
The early warning module is used for sending out an alarm and uploading a detection result to the disease control center when the sample is detected to be positive;
the specific processing steps of the data processing module are as follows:
CL1, take the first Mean value of secondary fluorescence to/>Secondary fluorescence mean as the/>Group judgment data;
CL2, calculate the first Secondary fluorescence mean value relative to the/>Increment of secondary fluorescence mean/>：
Wherein,For/>Secondary fluorescence mean value/>；
CL3, letIs on the abscissa/>Plotted as ordinate;
CL4, solve for the first Amplification index of group judgment data including mutation index/>Slope/>And correlation index/>：
Wherein,For/>And/>Covariance,/>For/>Variance of/>Is thatIs a variance of (2);
The system comprises a positioning module, an administrative region dividing module, a map marking module, a second judging module and a third judging module;
The positioning module is used for detecting the geographic position at fixed time and uploading the geographic position together with the detection result of the biological sample;
the administrative region dividing module divides the electronic map according to administrative regions of different levels;
The map marking module is used for extracting the geographic position corresponding to the detection result and marking the geographic position in the administrative region corresponding to the electronic map;
The second judging module is used for counting the number of positive samples in the administrative region aiming at the administrative region with the lowest level, and if the number of positive samples in the administrative region is larger than a set threshold value with the lowest level, marking the administrative region with the lowest level as a high risk region;
the third judging module is used for counting administrative areas of other levels, counting the number of positive samples in the administrative areas, calculating the uniformity of the distribution of the high risk areas in the next-level administrative area subordinate to the administrative areas if the number of positive samples is larger than a set corresponding level threshold, and marking the administrative areas of other levels as the high risk areas if the uniformity is larger than the set uniformity threshold;
the administrative region dividing module, the map marking module, the second judging module and the third judging module are arranged in the disease control center.
2. The pathogenic microorganism high risk area detection system of claim 1, wherein the uniformity calculation method is as follows:
TP1: counting the next administrative area which is subordinate to the administrative area of the current level and marked as a high risk area;
TP2: if two or more than two adjacent next-level administrative areas are high risk areas, making a common circumcircle;
TP3: calculating uniformity ：
Wherein,The area of the administrative region at the current level; /(I)The area of the next level administrative area that is singly marked as a high risk area; /(I)Is the area of the common circumscribing circle; /(I)For the sum operator, a union of multiple areas is calculated.
3. The pathogenic microorganism high risk area detection system of claim 1, further comprising a reagent bottle, a two-dimensional code bound to the reagent bottle, and a two-dimensional code identification module;
the reagent bottle is filled with a reagent for detecting a sample;
the two-dimensional code is used as a unique identification code of the reagent, and is recorded with the experimental steps, parameters, pathogen type detection and production date of the reagent;
The two-dimensional code identification module is used for identifying the two-dimensional code and displaying the recorded content of the two-dimensional code.
4. The pathogenic microorganism high risk area detection system of claim 1, wherein the administrative area comprises villages, towns, counties, cities, provinces, in order from low level to high level.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202210089778.9A CN114444928B (en) | 2021-02-02 | 2021-02-02 | Pathogenic microorganism high-risk area detection system |
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| CN202110144894.1A CN112862297B (en) | 2021-02-02 | 2021-02-02 | Real-time monitoring system for pathogenic microorganism Internet of things |
| CN202210089778.9A CN114444928B (en) | 2021-02-02 | 2021-02-02 | Pathogenic microorganism high-risk area detection system |
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| CN114444928B true CN114444928B (en) | 2024-05-31 |
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| CN114444927A (en) | 2022-05-06 |
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