73 results about "Epidemiology" patented technology

The invention provides a disease burden prediction and prevention and control decision-making method and system based on machine learning, and relates to the technical field of disease prediction and public health decision-making, and the method comprises the steps: obtaining epidemiological data of tuberculosis and related diseases from an authoritative database, and carrying out the preprocessing of the epidemiological data; respectively training an XGBoost model, an RF (Radio Frequency) model and a Prophet model; training a random forest meta-model by adopting a Stacking fusion strategy, and constructing a hybrid prediction model; calculating RMSE, MAE, MAPE and Rindex evaluation model performance; based on the obtained hybrid prediction model; based on the variable importance analysis result and the prediction result, the influence of the key independent variable on the tuberculosis burden dependent variable is quantified, the effect of the independent variable change on the dependent variable is simulated, and a tuberculosis prevention and control intervention strategy suggestion is generated. By fusing multi-source data and a hybrid modeling technology, tuberculosis prediction precision is remarkably improved, confidence interval quantization and prevention and control strategies are linked for the first time, and data-driven decision support is provided for global tuberculosis prevention and control.

A system and method for pharmacy-level surveillance of all prescription behaviors using one or more artificial intelligence (AI) agents integrated with real-time prescription records, refill timelines, prescriber data, patient histories, PDMP registries, and epidemiological signals. The system evaluates these inputs with configurable heuristics and machine-learned models to detect prescription abuse, public health risks, and equity or bias trends, including overlapping providers, dosage escalation, refill velocity, and prescriber clustering. When an anomaly is identified, a structured alert is routed to pharmacists, prescribers, or regulatory personnel through a secure, role-authenticated communication interface. Each system transaction and user outcome is captured by a Medical Data Governance (MDG) layer, providing cryptographic sealing, timestamping, and immutable ledger storage. In some embodiments, the audit log uses a blockchain-based distributed ledger. The system's feedback-driven, adaptive architecture enables analytic and policy modules to update automatically based on real-time outcomes, public health signals, and usage trends.

The invention provides an anti-duck adenovirus 3 type monoclonal antibody, a hybridoma cell strain and application thereof, the anti-duck adenovirus 3 type monoclonal antibody is secreted by a hybridoma cell strain 2F12, the classification name of the hybridoma cell strain 2F12 is Hybridoma cell line 2F12, the hybridoma cell strain 2F12 is preserved in China Center for Type Culture Collection on November 13, 2025, the preservation address is Wuhan University, Wuhan, China, and the preservation number is CGMCC NO. The preservation number of the strain is CCTCC (China Center For Type Culture Collection) NO: The blocking ELISA kit for detecting the duck adenovirus 3 antibody, which is prepared by utilizing the monoclonal antibody, is strong in specificity, high in sensitivity and good in repeatability, and has a very good application prospect in the aspects of epidemiological investigation of the duck adenovirus 3, vaccine immune efficacy evaluation and diagnosis of the duck adenovirus 3 disease.

The invention discloses a primer and probe composition for detecting nocardia seriolae based on TaqMan qPCR (quantitative polymerase chain reaction) and application of the primer and probe composition. According to the invention, a qualitative and quantitative detection method for nocardia seriolae is established by utilizing the specific primers and probes, and the method is used for carrying out qualitative detection on water bodies and fish bodies of farms of snakeheads and hybrid snakeheads in different regions and detecting different tissues after the hybrid snakeheads counteract the nocardia seriolae, and has a very good detection effect. According to the invention, the purposes of nocardia seriolae monitoring, nocardia disease diagnosis, pathological degree measurement and the like can be realized, a reliable detection tool can be provided for nocardia seriolae epidemiological investigation, and nocardia disease can be diagnosed in an early stage so as to guide culture management and reasonable medication treatment; and a research basis and a technical support are provided for exploring epidemic characteristics and pathological mechanisms of nocardia seriolae.

The invention provides an intelligent auxiliary flow scheduling method for a whole flow scheduling process, and relates to the technical field of big data, and the method comprises the steps: S1, deploying an artificial intelligence computing power cluster at a center end; s2, registering a traffic scheduling task through a held mobile terminal by a traffic scheduling person during traffic scheduling, interacting with the central terminal in the traffic scheduling task execution process to call an artificial intelligence computing power cluster to perform remote identity verification and auxiliary traffic scheduling question and answer on a traffic scheduling object, and after the traffic scheduling task is finished, according to a generated traffic scheduling question and answer record, performing traffic scheduling on the traffic scheduling object according to the traffic scheduling question and answer record; and completing structured analysis and generating an epidemiological investigation report. The method has the beneficial effects that by deploying the artificial intelligence computing power cluster at the center end, unified management and application of the flow scheduling artificial intelligence models and reasonable scheduling of resources are realized, so that each flow scheduling artificial intelligence model can be integrated into the whole flow scheduling process, and the flow scheduling efficiency and accuracy are effectively improved.

The invention relates to the technical field of medical artificial intelligence and public health data management crossing, in particular to an intelligent tuberculosis screening and data analysis management system which comprises a data acquisition module, an intelligent screening module, a data analysis management module, a clinical interaction module and a system management module. The multi-source data fusion and the dynamic threshold reasoning enable the early-stage tiny focus detection rate to be larger than or equal to 85%, the screening time is shortened to 5 minutes per case (80% higher than that of manual film reading), cross-mechanism and cross-dimension data integrated acquisition and sharing are achieved, 'hospital-disease control-grassroots' data intercommunication is achieved, and the screening efficiency is improved. Complete data support is provided for epidemiological analysis, longitudinal individual tracking and transverse group analysis are combined, the early warning period of regional outbreak is larger than or equal to 2 weeks, and a public health prevention and control gateway is assisted to move forwards.

The invention provides a CPA-LFD method for detecting Rahnella aquatilis and a detection kit, and belongs to the technical field of microbiological detection. On the basis of a single cross primer isothermal amplification technology (CPA) and in combination with a transverse flow test strip (LFD) prepared by colloidal gold, a real-time detection method for Rahnella aquatilis under the condition of 63 DEG C isothermal amplification is developed. According to the method, a specific primer is designed, and a probe containing Biotin and an FAM label is used for identifying a DNA specific region, so that rahnella aquatica is effectively detected within 1 hour; the optimized Bst DNA polymerase can be directly applied to isothermal amplification reaction of DNA, so that the detection process is simplified, and the time is shortened; the method is simple to operate, does not need to depend on professional detection personnel, has low requirements on instruments, realizes visual interpretation of detection results, has relatively high sensitivity and specificity, can detect Rahnella aquatica with the lower limit of 48fg / mu L, is suitable for rapid detection of Rahnella aquatica in human clinical samples, animals, fishes and food pollution, and can be widely applied to detection of Rahnella aquatica. The method has important significance on monitoring, diagnosis and epidemiological prevention and control of diseases caused by rahnella aquatica.

The invention discloses a primer and a kit for rapidly detecting yersinia rouxii through RPA-CRISPR / Cas12a and application of the primer and the kit, and relates to the technical field of disease prevention and control in aquaculture. The invention aims to solve the problems that the existing detection method is time-consuming and labor-consuming, is easy to cause pollution and needs to be matched with professional detection equipment. According to the present invention, the RPA amplification primer is composed of a forward primer yrp1-RPA-F2 and a reverse primer yrp1-RPA-R2, the crRNA is yrp1-crRNA-R1, and the kit for rapid detection of yersinia rouxii contains the RPA amplification primer and the crRNA. The method for rapidly detecting yersinia rouxii comprises a fluorescence method and a test paper method. The method disclosed by the invention has the advantages of good inclusiveness, strong specificity, high sensitivity and the like, detection is carried out based on the RPA primer and the crRNA, and the obtained RPA product is detected by using a lateral flow chromatography test strip and fluorescence, so that the purpose of portable visual rapid detection on site or in a breeding base is achieved, and the method is suitable for large-scale popularization and application. The method has very high clinical application value in the aspects of early discovery of diseases, epidemiological investigation and comprehensive prevention and control.

The invention discloses a porcine epidemic diarrhea virus G2c genotype strain as well as a separation method and application thereof. Aiming at the current epidemic PEDV variant strain, the genetic variation rule of the epidemic strain is clarified by carrying out virus separation, identification and pathogenicity analysis, and the method has important significance on epidemiology, vaccine development and the like of the PEDV. Specifically, an applicant successfully separates a PEDV strain capable of realizing stable passage propagation in Vero-CCL81 cells from intestinal contents of diarrhea piglets collected from a pig farm of Jiangpermanent Province in Hunan, the PEDV strain is identified and determined as a porcine epidemic diarrhea virus G2c subtype, the PEDV strain is named PEDV CH / HNJY / 2025, the PEDV strain is preserved in China General Microbiological Culture Collection Center on December 11, 2025, and the preservation number of the PEDV strain is CGMCC NO. The preservation number is CGMCC (China General Microbiological Culture Collection Center)

The invention discloses application of glucoraphanin to preparation of a product for reducing biological accumulation of perfluorooctane sulfonate, and belongs to the technical field of biological medicine. The occurrence probability of the high PFOS level in the body of a participant frequently eating broccoli is confirmed to be remarkably reduced through population epidemiological experiments, and then the PFOS level in the body of the participant is confirmed to be remarkably reduced after glucoraphanin intervention through clinical RCT random control experiments. The glucoraphanin-intervened serum has the advantages that the glucoraphanin-intervened serum is used as a main body, the metabolic change of steroid, ceramide and bile acid in the glucoraphanin-intervened serum is confirmed to be closely related to the reduction of the PFOS level through lipidomics analysis, and finally, the glucoraphanin is confirmed to be capable of effectively reducing the PFOS in-vivo accumulation and improving the liver injury caused by the PFOS through animal experiments and an AI reverse targeting technology; and the glucoraphanin and the in-vivo metabolite sulforaphane thereof have relatively strong binding capacity with a liver-specific PXR receptor, so that a good technical foundation is laid for research and development of drugs for treating diseases related to PFOS accumulation.

This invention discloses a primer set for amplifying a novel HCV subtype 6xp and a primer set for detecting drug resistance mutations. The primer set for amplifying the novel HCV subtype 6xp includes nested PCR primers for amplifying the full length of the novel HCV subtype 6xp, while the primer set for detecting drug resistance mutations is a set of primers targeting drug resistance mutation sites in the three functional regions of NS3, NS5A, and NS5B. The primer set provided by this invention has high specificity and high amplification efficiency, enabling specific amplification of the entire genome of the novel HCV subtype 6xp and accurate detection of drug resistance mutation sites in the three functional regions. It is suitable for clinical diagnosis, antiviral treatment guidance, epidemiological surveys, and viral evolution research of this subtype, and has significant clinical application value and scientific research significance.

The invention relates to the field of virus detection, in particular to a specific primer probe combination, a method and a kit for identifying avian influenza virus H9 prevalent strains SZ, A and X. The sequences of the three pairs of primers are as shown in SEQ ID NO: 1-9. The primer probe combination provided by the invention can achieve the purpose of distinguishing and detecting different strains of avian influenza H9 through fluorescent quantitative RT-PCR (Reverse Transcription-Polymerase Chain Reaction). The primer probe combination provided by the invention has the advantages of high sensitivity, strong specificity and the like, and provides a new effective detection means for rapid differential diagnosis, epidemiological investigation and prevention and control of the avian influenza virus H9 clinically.

The invention relates to the technical field of biological detection, relates to a dual RT-ddPCR detection method for equine encephalomyelitis viruses in the eastern and western parts, and in particular relates to a monitoring and quantitative detection method for samples with relatively low equine encephalomyelitis virus content or complex matrix, such as feeds, animal tissues and animal-derived products. The double reverse transcription microdroplet digital PCR detection method for the equine encephalomyelitis virus, established by the invention, is strong in specificity, high in sensitivity, good in repeatability and strong in anti-interference capability, and can be used for absolutely quantifying the copy concentration of the eastern equine encephalomyelitis virus EEEV and the western equine encephalomyelitis virus WEEV in an actual sample; a novel and reliable technical method is provided for early trace early warning and monitoring of Eastern equine encephalomyelitis virus EEEV and Western equine encephalomyelitis virus WEEV infection, differential diagnosis of other common viruses, research of propagation rules of the viruses, epidemiological risk assessment and other systematic applications.

The invention provides a fluorescent quantitative PCR (polymerase chain reaction) detection primer, a kit and a method for a novel variable chalmavirus VP gene, and belongs to the technical field of virus detection. A specific primer is designed and synthesized according to a conserved sequence of a VP gene of the novel variant chalmavirus, a recombinant plasmid is constructed, then the recombinant plasmid is used as a standard substance to establish a standard curve, a real-time fluorescent quantitative PCR detection system aiming at the novel variant chalmavirus is constructed, and specific detection of the novel variant chalmavirus is realized. The detection method can be used for quantitatively detecting the novel variant chalmavirus in the to-be-detected sample, and has the characteristics of high speed, high sensitivity, strong specificity and the like; the method provides a key technical support for molecular epidemiological investigation of the Sepamavirus in animal populations, is helpful for realizing early screening of infected individuals and timely blocking of virus transmission, and has important practical significance for guaranteeing population health and maintaining high mountain ecosystem stability.

The invention discloses construction and application of an interpretability model for virus molecular propagation network clustering. The construction comprises the steps of sorting a sample data set, preprocessing the data set, constructing a model, training, selecting an optimal model for interpretability analysis and the like. The method has the advantages that sequences and epidemiological information are converted into digital signals at the same time, comprehensive information fusion is carried out, and interpretable comprehensiveness and accuracy are achieved; meanwhile, an SHAP black box model is used for explaining a framework, an optimal model is selected for interpretability analysis, the SHAP value of each sample feature is calculated, contribution of the features to a model prediction result is quantified, and composition and features of the network are more effectively explained.

This invention discloses a kit for detecting porcine reproductive and respiratory syndrome virus (PRRSV) antibodies and its applications, belonging to the field of animal disease detection technology. The kit uses a mutant nucleocapsid protein (N protein) of the PRRSV-2 class NADC30 strain CHsx1401 as the coating antigen; the N protein mutant has mutations at amino acid positions 23, 75, and / or 90 compared to the wild-type N protein. High purity is achieved through optimized prokaryotic expression systems and purification processes. Under optimal detection conditions, the kit exhibits strong specificity, high sensitivity, and good reproducibility, with significantly superior detection performance compared to existing commercial kits. It can be used for PRRSV-2 antibody detection, epidemiological surveys, and disease control.

The present application relates to a kind of respiratory infectious disease scale and medical resource demand prediction method based on propagation dynamics, the present application uses next generation matrix method to carry out preliminary estimation to effective contact rate, and then uses Markov chain monte carlo algorithm to correct fitting parameter, improve the accuracy of model prediction.Most epidemiological parameters cannot obtain an accurate value, and are mostly an interval, therefore the present application carries out sampling in interval, and calculates 95% confidence interval, improve the reliability of prediction.Increase the prediction of medical resource demand such as the number of hospital beds, ICU bed number, whether the reserve of medical resource can be effectively evaluated, and resource can be timely called according to the prediction result if necessary.The present application realizes the prediction of infection scale and medical resource demand under different intervention measures, provides basis for taking appropriate intervention measures.

This invention relates to a primer set and probe set for dual real-time quantitative PCR detection of GAstV-1 and GAstV-2. The sequences of the primer set are shown in SEQ ID NO. 1-3, and the sequences of the probe set are shown in SEQ ID NO. 4-5. This invention provides a primer set, probe set, and kit for dual real-time quantitative PCR detection of GAstV-1 and GAstV-2, and establishes a detection method capable of simultaneously detecting GAstV-1 and GAstV-2. This method has advantages such as saving primer quantity, reducing detection costs, simultaneous detection, rapid detection, high efficiency, accurate quantification, high sensitivity, strong specificity, and good reproducibility. It lays the foundation for conducting molecular epidemiological surveys of GAstV-1 and GAstV-2 and subsequent scientific prevention and control of related diseases, and has significant research value.

The present invention provides a disease data analysis method, device, electronic device and storage medium, which relate to the field of data processing technology, including: obtaining multi-source disease data associated with a target area within a preset time period; wherein the multi-source disease data includes at least one of the following: pharmacy sales data, school absenteeism, hospital visit data, pathogen data, epidemiological survey reports and disease news information data in the target area; based on the multi-source disease data, constructing a regional graph network of the target area; after splicing the regional graph network and the multi-source fusion features of the multi-source disease data, inputting them into a disease data analysis model containing multiple expert intelligent agents, and outputting the disease analysis results of the target area.

The present application relates to a kind of primer set and probe set for chicken circle virus AGV2 and GyV7 dual real-time fluorescent quantitative PCR detection, the sequence of the primer set and probe set is as shown in SEQ ID NO.1-6, the present application provides primer set and probe set and kit for chicken circle virus AGV2 and GyV7 dual real-time fluorescent quantitative PCR detection, and establishes the detection method capable of simultaneously detecting chicken circle virus AGV2 and GyV7, with the advantages of simultaneous detection, rapid detection, high efficiency, quantitative accuracy, high sensitivity, strong specificity, good repeatability, for chicken population to carry out new chicken circle virus AGV2 and GyV7 molecular epidemiology survey and subsequent scientific prevention and control related disease lay foundation, with very important research significance.

The application provides a general avian infectious bronchitis virus whole genome deep sequencing method and application. The method realizes efficient amplification of long fragments of whole genomes of different genotype IBV epidemic strains by designing and applying a set of combinations containing 24 pairs of specific primers. The specific sequences of the primer combinations are shown in SEQ NO:1 to SEQ NO:48. Compared with a traditional sequencing method, the application significantly reduces the sequencing cost. Only two PCR reactions are needed, and more than 27 kb of IBV full-length genome sequence can be successfully obtained, which provides a more economical and efficient solution for IBV related scientific research and molecular epidemiology monitoring, and helps to promote the development of related field scientific research.

The application discloses a kind of Chinese lung cancer high-risk population risk prediction method based on multi-modal feature fusion, comprising: step 1, data acquisition;Step 2, data preprocessing;Step 3, multi-source risk feature evaluation and screening: verify and evaluate the prediction efficiency of lung cancer epidemiology risk score, tumor marker and lung cancer related multi-gene risk score, and screen out the optimal single dimension score of each dimension from it;Step 4, multi-modal score construction: according to the smoking status of participants, the population is divided, the optimal single dimension score of each dimension screened out is standardized, then the multi-source features are fused using Logistic regression model and the weighted coefficients are optimized, and the multi-modal lung cancer risk prediction score suitable for smokers and non-smokers is constructed respectively.The present application has superior discrimination performance, can accurately identify high-risk individuals, guide subsequent imaging examination and early intervention, and improve the early diagnosis rate and treatment effect of lung cancer.

The invention relates to the technical field of public health management and decision-making, and discloses a public health risk comprehensive evaluation and decision-making optimization method based on multi-source information, and a constructed emergent public health event analysis model comprises a medical resource competition sub-model and an infectious disease diffusion sub-model. Model calibration, a nonlinear generalized predictive adaptive control law and comprehensive overflow effect evaluation based on data envelope analysis are adopted to deeply integrate infectious diseases, a resource competition theory, an optimal control theory, operational research and an information theory method; a comprehensive model system capable of reflecting complex system interaction of'epidemic situation-resource-decision-society 'in public health events is constructed, strong robustness and dynamic optimization capability for dealing with uncertainty are achieved, the model precision and reliability are remarkably improved, errors are reduced, the defect that traditional evaluation is single is overcome, and the method is suitable for popularization and application. The overall effect of emergency decision making can be comprehensively evaluated from multiple aspects of medical treatment, society, economy and the like, and efficient and comprehensive decision making support is achieved.

The invention relates to the technical field of animal epidemic disease prevention and control management, and particularly discloses an animal epidemic disease health risk evaluation method and system, and the technical key points are that the method comprises the steps: firstly, collecting multi-source data of animal health monitoring, laboratory detection, environmental factors, epidemiology and the like, and carrying out the standardization processing of the data; key factors such as immune level, health deviation degree, environmental stress degree and epidemiological risk are extracted; by establishing a multi-factor comprehensive risk evaluation model, quantitative calculation is carried out on epidemic disease risks of animal groups, and dynamic updating and self-learning optimization of risk indexes are realized in combination with time sequence correction and machine learning correction; the system structurally comprises a data acquisition module, a data processing module, a risk assessment module and a result output module, and can realize risk grade division, visual display and cross-terminal early warning push. When the risk reaches a medium-high level, the system can be linked with ventilation, disinfection and isolation measures of the farm to form a closed loop of evaluation, early warning and disposal.

The present invention relates to an ESP decision optimization system for epidemiological modeling. ESP based modeling approach is used to predict how non-pharmaceutical interventions (NPIs) affect a given pandemic, and then automatically discover effective NPI strategies as control measures. The ESP decision optimization system comprises of a data-driven predictor, a supervised machine learning model, trained with historical data on how given actions in given contexts led to specific outcomes. The Predictor is then used as a surrogate in order to evolve prescriptor, i.e. neural networks that implement decision policies (i.e. NPIs) resulting in best possible outcomes. Using the data-driven LSTM model as the Predictor, a Prescriptor is evolved in a multi-objective setting to minimize the pandemic impact.

The invention provides a zoonosis risk prediction method coupling climatic factor time sequence characteristics and land utilization space landscape characteristics under the background of climate and land utilization change, and relates to the technical field of zoonosis space epidemiology. According to the method, land utilization types such as buildings, roads, greenbelts and water bodies are identified through high-resolution remote sensing, landscape features are constructed, weather time sequences such as air temperature, rainfall and humidity are obtained by combining a geographic space big data cloud computing platform, and climate features are extracted by adopting a long-short-term memory network; and meanwhile, spatial population distribution characteristics are formed by utilizing the population data set. And based on the multi-source spatial-temporal characteristics, constructing a multilayer perceptron to simulate and predict the propagation rate. A true propagation rate is calculated based on the case matrix and the susceptible-infected-restorer epidemiological model. And calculating a loss function of the predicted propagation rate and the real propagation rate to optimize deep learning network parameters, and realizing risk dynamic assessment of the coupling space-time propagation mechanism.

This invention discloses an intelligent triage and etiology early warning system and method for acute abdominal pain, belonging to the field of medical technology. It aims to solve the problem of low triage efficiency in existing technologies for emergency response to public health emergencies when a large influx of patients occurs. The system includes a data acquisition module, an intelligent triage module, an etiology analysis and early warning module, and a terminal interaction module. The data acquisition module collects patient information, including basic information, symptom information, physical signs information, epidemiological history information, and auxiliary examination data. The intelligent triage module, based on patient information and a built-in acute abdominal pain triage model, matches patients' severity levels with the appropriate departments. The etiology analysis and early warning module integrates batch patient information, extracts key features, performs commonality analysis, identifies concentrated etiologies, and issues graded early warnings based on the severity of the etiology. This invention has the advantage of improving triage efficiency.

This application provides a method and system for infectious disease risk prediction based on a large language model and wastewater monitoring. The method includes: acquiring a multimodal time-series dataset of a target area in a first time period, wherein the multimodal time-series dataset includes wastewater epidemiological data sequences of the target disease, vaccination data sequences of the target disease, clinical monitoring data sequences of the target disease, environmental data sequences, and demographic data sequences obtained based on technologies such as multipathogen hybridization capture sequencing and PCR; converting the multimodal time-series dataset into a text time-series data sequence; inputting the text time-series data sequence into a preset risk prediction model to generate corresponding feature vectors, and predicting the trend of hospitalization rate changes of the target disease based on the feature vectors; and predicting the risk level of the target disease in the target area based on the trend of hospitalization rate changes and the wastewater epidemiological data sequence, thereby improving the accuracy of infectious disease area risk prediction.

A collector device of environmental exposure is provided. This device may be used to collect and, after technical upgrade, monitor environmental exposure in personal and stationary settings. By coupling with advanced genomic analysis and chemical analysis technologies, the device and its accompanying methodology are capable of detecting environmental agents of diverse nature, many of which could pose health risks if going unaware of or uncontrolled. This type of information provides much needed clues to reconstruct and pinpoint the course of disease etiology at both personal and epidemic scales. By combining personal exposome and personal omics analyses, we can recapitulate with the intention to then prescribe treatment plans with unprecedented precision.