115 results about "Epidemiology" patented technology

The AI-enhanced cellular modeling and simulation platform is a computational system designed to enhance biomedical research and development and personalized medicine and wellness. This platform integrates simulation modeling, machine learning and artificial intelligence, multi-omics data, and sophisticated data fusion and decision-support techniques to create comprehensive models of cellular systems and processes across multiple scales. It enables researchers and clinicians to simulate complex biological interactions, predict disease progression, and design or optimize treatment strategies or medical devices with improved accuracy and efficacy. The system's architecture allows for integration of various components, including real-time data processing, federated learning, and quantum computing enhancements. From personalized drug discovery and cancer therapies to synthetic biology and epidemiological analysis, this platform offers powerful tools for understanding and manipulating cellular systems and bioengineered systems. By bridging the gap between molecular-level interactions between cells and materials and organism-wide effects, it enables significant advancements in healthcare and biological sciences.

The invention discloses an animal epidemic disease cross-border transmission risk analysis method based on big data, and particularly relates to the technical field of data analysis. Through a multi-modal data fusion algorithm of deep learning, multi-source heterogeneous data is integrated in real time to form a unified data set, a cross-border propagation path model based on an infectious disease propagation model and an epidemiological theory is constructed, a propagation path of epidemic diseases is accurately simulated in combination with spatio-temporal information and propagation characteristics, and on the basis, the propagation path of the epidemic diseases is accurately simulated. A machine learning algorithm is utilized to analyze the fusion degree of cross-border propagation data between different regions, and based on a multi-source data fusion evaluation result, a high-risk region and a propagation speed are predicted in real time, so that potential cross-border propagation risks are evaluated, and targeted prevention and control intervention measures are proposed; according to the method, the problems of data isomerism, timeliness difference and fusion processing in the prior art are effectively solved, the accuracy, the real-time performance and the scientificity of epidemic disease cross-border transmission risk analysis are improved, and accurate support is provided for epidemic prevention and control decisions.

The invention discloses an intelligent tuberculosis screening and data analysis system, relates to the technical field of medical data analysis systems, and aims to improve the diagnosis efficiency and accuracy of tuberculosis. The technical key points are that the system comprises a data acquisition module, a preprocessing module, an AI diagnosis module, a multi-modal data fusion module, a data analysis module, an intelligent follow-up visit module and a database management module. By collecting image data and clinical information of a patient, the system adopts a deep learning algorithm to automatically analyze an image, identifies a potential tuberculosis focus, and provides a personalized diagnosis result in combination with a multi-modal data fusion technology. Meanwhile, the system has intelligent follow-up visit and remote monitoring functions, physiological indexes of the patient are obtained in real time through the wearable device, and dynamic illness state tracking and early warning are carried out. According to the method, the accuracy and efficiency of tuberculosis screening can be remarkably improved, precise medical services are provided for patients, and epidemiological prediction and prevention and control in the public health field are supported.

A system for AI-driven predictive healthcare for pandemic prevention, which includes the following: a data collection module configured to capture health-related data from IoT-based wearable devices, electronic health records (EHRs), environmental sensors, and social media in real time; an AI-driven analysis module that is operationally linked to the data collection module and configured to use deep learning and natural language processing (NLP) techniques to process and analyze collected data in order to detect potential disease outbreaks; a predictive modeling module configured to use hybrid epidemiological and AI models to predict disease transmission patterns based on mobility data, population density, and historical infection trends; a warning and response module that automatically generates and disseminates notifications to health authorities, medical professionals, and vulnerable individuals based on predicted outbreak risks; a blockchain-based data security module configured to ensure the secure storage, access control, and verification of health-related data through decentralized ledger technology and smart contracts; and a decision support module that is operationally linked to the predictive modeling module and provides AI-driven recommendations for healthcare resource allocation, vaccination strategies, quarantine measures and public health measures.

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 a pathogen detection method based on targeted high-throughput sequencing. The pathogen detection method comprises the following steps: S1, acquiring NGS original sequencing data of a pathogen sample to be detected and a negative control sample; s2, removing low-quality data from the obtained original sequencing data, then performing host sequence filtering, and finally performing plasmid sequence filtering to obtain high-quality sequencing Read; s3, comparing the pathogen reference genomes to obtain specific Read data; s4, performing classification according to a comparison result, and calculating the specific Read number and the RPM value of each pathogen; s5, constructing a microbial reference genome database, and verifying the species specificity of the specific Read in the NT database; and S6, grading pathogen detection signals in the to-be-detected sample according to the RPM value and the NTRPM value to obtain a result. The method provided by the invention can effectively reduce false positive of a detection result and interference of background signals, the detection result is accurate, and the method can be well applied to the fields of disease diagnosis, epidemiological investigation, public health prevention and control and the like.

The invention relates to the technical field of biological detection, relates to a multiple ddPCR detection method for porcine intestinal coronavirus, and in particular relates to a monitoring and quantitative detection method for samples with relatively low porcine intestinal coronavirus content or complex matrix, such as feeds, animal tissues and animal-derived products. The droplet digital PCR detection method for the porcine intestinal coronavirus established in the invention has the advantages of strong specificity, high sensitivity, good repeatability and strong anti-interference capability, can be used for absolute quantification of the copy concentration of the porcine acute diarrhea syndrome coronavirus (SADS-CoV), the porcine epidemic diarrhea virus (PEDV), the porcine delta coronavirus (PDCoV) and the porcine transmissible gastroenteritis virus (TGEV) in an actual sample, and can be used for the detection of the porcine intestinal coronavirus. The invention provides a novel and reliable technical method for trace early warning and monitoring of early-stage infection of four porcine intestinal coronavirus, differential diagnosis of other common viruses, research of propagation rules of the viruses, epidemiological risk assessment and other systematic applications.

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 discloses a multiple qPCR (quantitative polymerase chain reaction) detection reagent for detecting neonatal gastrointestinal infection pathogens. The kit comprises specific primers and probes for detecting enterohemorrhagic escherichia coli, staphylococcus aureus, pseudomonas aeruginosa, streptococcus agalactiae, klebsiella pneumoniae, staphylococcus epidermidis, beta hemolytic streptococcus, salmonella, rotavirus and adenovirus. According to the invention, different fluorescently-labeled probes are utilized to add specific primers and probes of multiple pathogens into a reaction system to detect multiple targets at the same time, and the method has the advantages of good specificity, high sensitivity, short detection period, capability of simultaneously detecting multiple pathogens, rapidness, simplicity, convenience and economy; a convenient method is provided for rapid detection of pathogens causing neonatal gastrointestinal infection, and the kit has important significance in epidemiological research, clinical early molecular diagnosis and the like.

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 an anti-novel duck reovirus monoclonal antibody hybridoma cell strain, a monoclonal antibody, a reagent or a kit and application, and belongs to the technical field of novel duck reovirus detection. The monoclonal antibody hybridoma cell strain capable of resisting the novel duck reovirus is named as a hybridoma cell strain NDRV Mab-Sigma C-9, and the preservation number of the hybridoma cell strain NDRV Mab-Sigma C-9 is CCTCC (China Center for Type Culture Collection) NO: C2024284. An indirect immunofluorescence kit prepared from the monoclonal antibody secreted by the monoclonal antibody hybridoma cell strain for resisting the novel duck reovirus has good specificity and sensitivity. The kit not only can be used for detecting exogenous viruses of the NDRV in poultry virus live vaccines, but also can be used for clinical detection and epidemiological investigation of the NDRV.

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.

The invention relates to the technical field of biological nucleic acid detection, in particular to a primer combination, a detection method and a kit for detecting virulent strains and variants of infectious bursal disease viruses. The primer probe combination comprises three pairs of specific primer probes designed according to VP2 gene segments of a virulent strain, a variant 1 and a variant 2 of the infectious bursal disease virus, and 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 IBDV 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 of IBDV, epidemiological investigation and prevention and control of IBD clinically.

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 invention belongs to the field of disease prediction, and provides a zoonosis epidemiology intelligent analysis method and system.The method comprises the steps that in a preset time period, samples are collected, pathogen detection is conducted, and an infection data sequence is obtained; determining the change rate of the number of people-livestock cross-infected people according to the infection data sequence; determining the human-animal contact rate as a hidden state, and constructing a hidden Markov model; training the hidden Markov model by taking the change rate of the number of people-livestock cross infection as an observation sequence, and determining state distribution, a state transition probability matrix and observation probability distribution parameters of the hidden Markov model; deducing the current human-animal contact rate according to the current human-animal cross infection number change rate and the trained hidden Markov model; and establishing a propagation model according to the human-animal contact rate, and predicting infection data according to the propagation model.

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.