79 results about "Communicable disease" patented technology

The invention relates to the technical field of public health information, in particular to an infectious disease transmission path generation and early warning method and system based on big data, and the method comprises the steps: collecting and cleaning multi-modal data, and obtaining a pulse event flow through neuromorphic coding; and constructing a variable order hyperedge graph in a second-level window, extracting loop life to adjust diffusion of the cellular automaton, and iteratively generating an infection prediction field. And then splicing the hyperedge graph, the prediction field and the topological fingerprint into a conditional tensor, and inputting the conditional tensor into a conditional score diffusion network to generate a future propagation event sequence. And constructing a tensor network according to the sequence, mapping the tensor network into Isin Hamiltonian, quickly selecting an intervention node through an optical delay ring reservoir and gradient descent, and issuing a ventilation or purification instruction. And after a virus load difference value before and after intervention is normalized, a tensor network, a diffusion network and a cellular automaton are synchronously updated to form a self-adaptive closed loop, so that a peak time error can be shortened, and the recall rate of a high-risk region is improved.

The invention relates to the technical field of fly infectious disease prevention and control, in particular to an intelligent fly monitoring device, comprising: a box body comprising a plurality of wall parts defining a containing cavity, the plurality of wall parts comprising a front wall, a rear wall and a bottom wall which are oppositely arranged, and the bottom wall being provided with a hole; the trapping module comprises a fly sticking plate and a bait disc, the fly sticking plate is arranged on the front wall in the containing cavity, the bait disc is located at the preset distance position of the lower side of the bottom wall, and a preset angle is formed between the connecting line between the center of the bait disc and the edge of the hole and the horizontal plane where the bait disc is located; the electric control box is arranged on the rear wall in the containing cavity, the image collecting module is configured to collect fly monitoring images on the fly sticking plate, and the intelligent control module is configured to collect and preprocess the fly monitoring images and conduct recognition, number statistics and risk early warning on fly types in the fly monitoring images. According to the method, the problem of fly missing detection in a complex environment can be effectively solved, the insect pest early warning timeliness is greatly improved, and the monitoring accuracy is high.

The utility model relates to medical instrument technical field especially is involved in a kind of anti-stab needle, including needle body and the protective shell of outer sleeve in the outside of needle body, the needle body includes needle tip, needle seat and needle tube connected in turn, the side of needle seat is also equipped with needle wing, the inside of protective shell is equipped with the passageway for needle body reciprocating sliding, and the side wall of protective shell is also equipped with the notch for needle wing to penetrate, the inner wall of passageway is equipped with first limit piece and second limit piece, when needle tip extends to the outside of passageway first limit piece is limited with needle seat cooperation, when needle tip is retracted to the inside of passageway second limit piece is limited with needle seat cooperation, the utility model protects needle head by protective shell, eliminates needle tip of needle head stab injury, reduces the probability of infection infectious disease by needle tip stab injury, with safe and reliable advantage.

An air flow delivery system for delivering conditioned air to an enclosure housing infectious disease patients, includes: (a) an air intake pipe having a first bidirectional valve therein, wherein when the bidirectional valve is in an open state, ambient air enters the enclosure; (b) an air handler, the air handler coupled to the air intake pipe; and (c) an air supply duct installed within at least one wall of the enclosure, wherein the air supply duct delivers conditioned air from the air handler to one or more air supply vents positioned at or near a bottom surface of the enclosure. The enclosure is selected from a group consisting of a pavilion, a building, a room, a nursing home, an airplane, a vehicle, a train, a ship, a critical care unit in a hospital, and a free-standing, mobile enclosure.

The present application relates to the technical field of public health safety, in particular to an infectious disease tracing method and system based on a space-time graph neural network, which integrates multi-source heterogeneous contact data, constructs a topologically enhanced space-time graph, converts the data into a space-time point cloud, constructs a multi-scale simplex complex, extracts persistent topological features, integrates the features into a graph representation, trains a multi-scale space-time graph neural network, uses multi-level time encoding and a double attention mechanism, designs a topological feature guided message passing, and finally performs topologically guided backpropagation tracing, reversely traces persistent homologous information flow and spectral graph convolution, generates multiple propagation source point hypotheses, and outputs the probability distribution of potential infection sources and the propagation path.

The application discloses a respiratory infectious disease population flow network construction and feature mining method and device based on multi-source heterogeneous traffic big data. The method collects multi-source traffic travel data such as railways, civil aviation, highways and mobile signaling and pre-processes, constructs a time-space correlation database, and generates multiple standard data tables through cleaning, desensitization, time-space alignment standardization processing. Based on the standardized data, the network topology parameters are defined, the multi-traffic mode OD flow matrix is generated, and the multiple verification and calibration are completed, the civil aviation, railway and highway hierarchical networks are respectively built, the network edge weight is fused through node alignment and interlayer coupling, the super-adjacency matrix is constructed, the multi-dimensional topological features of the multi-layer network are mined, and finally the exclusive feature data set suitable for respiratory infectious disease cross-regional transmission prediction is generated. The scheme can efficiently fuse standardized multi-source heterogeneous data, accurately construct the population flow network, and effectively improve the accuracy and timeliness of the infectious disease transmission risk assessment.

The application discloses a kind of source network load system attack path tracking and security protection method, first, source network load system network attack monitoring collection technology is proposed, and power generation side, energy storage system, load side, power grid operation, environmental factors and network security data are collected.Then, whether the instruction or the information collected is subjected to network attack by verifying whether the instruction and the uploaded power consumption data are reasonable;Secondly, according to the monitored source network load system network attack behavior, based on the mechanism of infectious disease model, the path of the source network load system subjected to network attack is given by reverse tracking the uploaded data subjected to attack.Finally, based on the key network node in the source network load system attack path selected by the sea squirt colony algorithm, the security protection measures are configured, considering the deployment cost and the expected effect, and finally outputting the protection scheme to guide the source network load system to deploy defense measures at the key nodes of the attack path and improve the security of the power grid.

The application discloses a magnetic capsule gastroscopy vehicle and a magnetic body thereof. The magnetic capsule gastroscopy vehicle comprises a vehicle body, the vehicle body comprises a vehicle compartment, the inside of the vehicle compartment is divided into a front cavity and a rear cavity arranged in front and back through an isolation door, the front cavity is a medical staff control area for medical staff activities, and the rear cavity is a patient disinfection and detection area for patient activities; the isolation door is a sliding glass isolation door; a front door for entering the front cavity is arranged at the front end of the vehicle compartment, a rear door for entering the rear cavity is arranged at the rear end of the vehicle compartment, and a general rear door for sealing the rear end of the rear cavity is further arranged at the rear side of the vehicle compartment; a check bed is detachably arranged in the rear cavity, and a magnetic body movement mechanism is arranged beside the check bed; a console is arranged in the front cavity, and the console is connected with the magnetic body movement mechanism in control. The application is convenient for flexible and mobile gastrointestinal disease screening, realizes contactless examination, expands the working range and the beneficiary population, and can provide medical aid in special environments such as infectious diseases and wars.

The invention provides a strategic mineral resource overseas supply chain risk space-time monitoring and early warning method and device based on a complex network and an improved SEIR infectious disease model, and is applied to the technical field of data processing. According to the method, on the basis of strategic mineral resource overseas supply chain risk monitoring and early warning, multiple types of data of a supply chain are integrated, a key path is identified based on an algorithm, and network topology information is generated; modeling five types of risk causal relationships by adopting a Bayesian network to obtain risk conduction information; then preprocessing the unstructured text, designing an NLP model, and generating risk identification information; setting evaluation rules according to multi-level requirements, and generating evaluation information; optimizing and improving SEIR model parameters, and generating risk propagation prediction information; defining Agent behavior rules, and generating evolution simulation information; and finally, integrating multi-source data, generating full-process intelligent early warning response information including monitoring, early warning and plan matching, and realizing risk dynamic monitoring and efficient response.

The application relates to a tracing method for latent period asymptomatic transmission based on an SAIR model, which comprises the following steps: S1, determining a single initial transmission source node in an interpersonal relationship complex network, and transmitting according to the source node according to an SAIR model until a moment t0; S2, randomly selecting a certain number of nodes as observation nodes, and knowing the state of the observation nodes at the moment; S3, screening a candidate source node set in the complex network by using a reverse propagation algorithm according to the state of the partial observation nodes, and the hop distance and the effective distance, and the number of nodes is determined by a sampling method; S4, constructing a dynamic message transmission equation according to the SAIR model, and calculating the probability of the candidate source nodes being in different states at a moment Delta t by using the partial observation nodes; and S5, calculating the likelihood probability of the nodes in the candidate source node set becoming sources by using an average field theory, and the source is the node with the maximum probability. According to the application, the spread of infectious diseases of patients with latent period and asymptomatic can be accurately reflected, and the problem of tracing the source of infection can be solved.

The present invention provides a method for analyzing the risk of malicious instructions propagating across space. The method includes establishing a coupled network structure of an active power distribution network cyber-physical system, and then using prior probability, posterior probability theory, and minimum load loss rate theory to study the process of malicious instructions in the coupled network and establish a quantitative assessment model for cross-space propagation risk. This model considers the connection between information nodes and physical nodes after intrusion, as well as the spread of risk propagation. Finally, the Bayesian theory is used to approximate the three likelihood functions of the risk propagation after the malicious instruction intrusion, and a quantitative value is calculated, providing an indicator for the safe and stable operation of the active power distribution network. The method also considers the directionality and interdependence of the link between the physical layer and the information layer, and uses an infectious disease-based infection model to characterize the risk propagation mechanism between the information layer and the physical layer, thereby improving the comprehensiveness and accuracy of the risk analysis of malicious instructions propagating across space.

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 utility model belongs to the technical field of beauty handles, and particularly relates to a noninvasive electric lead-in handle which comprises a beauty head and a handle body, the beauty head is detachably connected to the head of the handle body, the handle body comprises a handle shell and a handle end cover assembly detachably connected to the front end of the handle shell, and the handle end cover assembly is detachably connected with the beauty head. The handle end cover assembly comprises a plurality of elastic needles, the beautifying head comprises a plurality of contacts, after the beautifying head and the handle body are connected, the elastic needles make contact with the contacts, and the elastic needles are used for being electrically connected with a beautifying instrument host. The utility model provides a modularized cosmetic head in a consumable mode, the cosmetic head can be replaced, the handle does not need to be replaced, different electrodes can be matched for different skin areas, meanwhile, the cosmetic head can be specially used by a specially-assigned person, and the risks of infection or infectious diseases caused by public use of the cosmetic head are completely eradicated.

The utility model relates to the technical field of medical instruments, in particular to a sickbed isolation device. The device comprises four groups of supporting mechanisms, isolating mechanisms and four groups of connecting mechanisms, the isolation mechanism comprises an isolation cover body covering the outer side of the sickbed, an isolation curtain fixedly arranged on one side in the isolation cover body so as to divide the isolation cover body into a first space and a second space, and an air filtering assembly arranged in the first space; the first fixing assembly is arranged between the ground and the isolation cover body in a sealed mode and used for fixing the isolation cover body, and the second fixing assembly is arranged between the ground and the isolation curtain in a sealed mode and used for fixing the isolation curtain. The device solves the problem that infectious viruses can be diffused to the outside air when medical staff enter and exit from the isolation assembly.

This application relates to the fields of artificial intelligence and public health technology, and in particular to an intelligent early warning method and related device for respiratory infectious diseases. The method includes acquiring time-series body temperature data and cough audio signals; acquiring facial images and extracting facial flushing features; determining the abnormal intensity value corresponding to the cross-fusion features; determining the flushing index corresponding to the facial flushing features; determining carbon dioxide concentration and relative humidity, and constructing an environmental compensation factor based on the carbon dioxide concentration and relative humidity; performing a weighted calculation on the abnormal intensity value, flushing index, and environmental compensation factor to obtain an abnormality score; and determining the early warning level based on the abnormality score. This application can improve the timeliness and accuracy of early warning.

The present invention relates a composition for use in increasing the longevity and / or enhancing healthy aging of a subject, particularly a human subject, and methods thereof. The composition comprises at least one of: isoscabertopin; 1,7-Bis (hydroxyphenyl)-4-hepten-3-one; eupafolin; isokuranetin, (E) - aldosecologanin, or any combination thereof, and increases expression of or activates a transcription factor selected from the group consisting of: nuclear factor (erythroid-derived 2)-like 2 (NRF2), Forkhead box O3 (FOXO3) and Grainy head 1 (GRHL1). Non-therapeutic or therapeutic uses and methods are disclosed herein. The extending longevity includes stimulating innate immunity, resistance against oxidative stress, inhibition of tumor cell growth, treating or preventing age-related diseases and disorders, which include: inflammation and inflammatory diseases, non-communicable diseases including: cardiovascular diseases, arthropathies, cancer, neurodegenerative diseases, diabetes, frailty, decline of physical fitness, decline of physical endurance or combinations thereof.

The invention discloses an intelligent analysis system for public health decision and trend prediction. The intelligent analysis system comprises the following steps: establishing a random optimal control system state equation containing a drift term, a diffusion term and a control function, and an objective function; a disturbance term is introduced into the state equation, and an original optimal control problem is converted into a random differential game problem; constructing a smooth trajectory estimation function based on the observation data, and defining a joint objective function; solving a random differential game problem to obtain an optimal control function and a system parameter estimator; the method is applied to a random control SIRD infectious disease model, and dynamic estimation of time-varying parameters is achieved; and on the basis of an estimation result, predicting a future disease transmission trend, and providing decision support for prospective planning and accurate configuration of public health resources. According to the method, a system with high noise and time-varying parameters can be effectively processed, the prediction precision and robustness are improved, and a quantitative basis is provided for prevention and control of infectious diseases.

The invention relates to the technical field of electrical digital data processing, and discloses an infectious disease risk prediction system and method based on a detection sharing network, and the system comprises a dynamic topology mapping module which constructs a logic connection map, carries out the real-time statistics of instantaneous connectivity, and corrects a conduction weight through a sparsity correction coefficient which is negatively correlated with the instantaneous connectivity; the state potential energy injection module is used for locking a positive node as an active source; the probability circulation calculation module is used for iteratively calculating risk propagation in the local subgraph and introducing time domain causal verification; according to the invention, by introducing a degree-weight reverse suppression mechanism and a time domain mask, the problems of topology short circuit and time sequence inversion caused by high-density noise data are solved.

The invention discloses a feature dynamic screening-based secondary blood index data set generation method and system, and the method comprises the steps: collecting basic information and basic blood indexes of a research object, and carrying out the preprocessing, thereby obtaining an effective sample; dividing into a chronic non-infectious disease-free control group and a target disease group, and carrying out demographic characteristic statistical difference analysis; calculating secondary blood indexes according to the basic blood indexes, and integrating the screened demographic characteristics to generate an enhanced data set; the method comprises the following steps: dividing an enhanced data set into a training set and a test set according to stratified sampling of disease states, synchronously standardizing continuous indexes of the training set and the test set, then screening an optimized feature set with a nonzero coefficient through an adaptive elastic network based on stability selection, and finally performing feature synchronous filtering and integration to form a final data set. According to the method, the problem of model selection difficulty caused by low quality, non-uniform processing flow and feature redundancy of the existing blood multi-dimensional index data set can be solved.

This invention relates to the interdisciplinary field of artificial intelligence and smart education, specifically disclosing a campus risk intelligent early warning method based on multi-source data. The method includes: constructing a campus digital twin spatial model integrating data from academic affairs, access control, consumption, social interactions, and location; identifying initial risk individuals who meet psychological health and behavioral abnormality indicators; constructing a dynamic risk transmission network based on social association, spatial co-occurrence, and behavioral similarity; introducing an improved behavioral infectious disease dynamics model to simulate the risk diffusion process; and generating high, medium, and low-level early warning signals based on the degree of risk accumulation and network centrality, and pushing tiered intervention suggestions. Through the above technical solution, this invention improves the foresight, accuracy, and effectiveness of campus risk early warning and intervention.

The application provides a delay calibration method and device in an infectious disease space collection population model, and belongs to the technical field of infectious disease transmission modeling and risk assessment; the application adopts a delay time discretization method to convert continuous distribution into a discrete probability vector; an infected person allocation algorithm based on matrix operation and a time axis translation algorithm based on matrix operation are designed; the efficiency is significantly improved, and the time complexity is reduced from to; experimental verification shows that the processing speed of a 100-million-population city is at least improved by 7 times, and the processing speed of a single 100-million-population city can be improved by more than 10 times; the whole algorithm is based on matrix operation under a determined dimension variable, so it is easier to use GPU to accelerate operation, and then the algorithm can be extended to a real-time epidemic monitoring and early warning system in the future.

The invention provides an intelligent port infectious disease monitoring and early warning method and system. The method comprises the following steps: acquiring health condition information autonomously reported by passengers, propagation condition data of infectious diseases appearing at a flight departure place and flight destination environment data; determining health classification data of each passenger according to the health condition information corresponding to each passenger; analyzing whether each passenger is a suspicious passenger according to the health classification data; according to the transmission condition data of the infectious diseases appearing at the flight departure place and the flight destination environment data, calculating the transmission speed score of the infectious diseases at the destination; and counting the number of the suspicious passengers, and sending different early warning information to airport workers according to the number of the suspicious passengers and the spread speed score of the infectious diseases at the destination. According to the invention, the individual health abnormity and the external propagation environment are organically combined, a comprehensive risk assessment system is formed, and accurate early warning is facilitated.

The application relates to the technical field of information management, and discloses an information system interface capable of realizing collaborative work, which comprises an external interface, an internal interface, a subsystem module and a control module; the external interface is used for being connected with an external terminal; the internal interface comprises an epidemic situation data synchronization interface, a personnel monitoring data synchronization interface, a personnel information synchronization interface and a nucleic acid detection result synchronization interface, and the internal interface is used for data exchange and communication in the subsystem module; the subsystem module comprises an epidemic situation data acquisition, processing and analysis subsystem, a traceability prevention and control subsystem, an infectious disease knowledge base and an intelligent question and answer subsystem and nucleic acid detection equipment; the control module is connected with the internal interface, the external interface and the subsystem module, and the control module comprises an acquisition unit, a judgment unit and a processing unit. Through the collaborative work of the external interface, the internal interface, the subsystem module and the control module, efficient management and rapid updating of infectious disease related data are realized.

The utility model discloses an intrusion alarm device of an electric control access control system, which comprises a shell component, a control component, a locking component and a sterilization component, the front end of the shell component is fixedly connected with the control component, the interior of the shell component is fixedly connected with the locking component, the upper end of the shell component is fixedly connected with the sterilization component, and the lower end of the shell component is fixedly connected with the control component. The device is characterized by further comprising a shell assembly. The left end of the shell is in sliding connection with the locking insertion rod through a sliding groove; the sliding groove is formed in the left end of the shell; the inner groove is formed in the front end of the shell; the laser detectors are fixedly connected to the upper end and the lower end in the shell; the false screws are rotationally connected to the four corners of the shell; the thread groove seats are fixedly connected to the four corners of the rear end of the shell; and by arranging the sterilization assembly capable of sterilizing the device, the device can be automatically sterilized after a person with infectious diseases uses the device, and the situation that the device is infected by germs, and consequently the device is infected by the germs is avoided.

The invention relates to the technical field of infectious disease investigation, in particular to a modular processing-based questionnaire form intelligent configuration method. Comprising the following steps: a modular component construction step: packaging each element, including but not limited to an input box, a pull-down menu, a single selection box, a check box and a text area, of the questionnaire form into independent modular components, each modular component having a unique identifier and a predefined functional interface and being used for interacting with other components or systems; a configuration information acquisition step: acquiring configuration demand information of a user for the questionnaire form, wherein the configuration demand information comprises but is not limited to form themes, data types needing to be collected, form layout requirements, logical relationship requirements among form items and target audience feature information; according to the invention, variability of infectious disease investigation requirements can be realized, and modular flexible configuration of the investigation form is realized.

The utility model relates to a lower limb X-ray radiography squeezer which is characterized in that the periphery of a single chip microcomputer is connected with a host wireless communication module (12), an outlet of an inflator pump (6) is connected with a gas storage bottle (7), and a remote controller wireless communication module (14) arranged in a wireless remote controller and the host wireless communication module jointly form wireless communication; an RFID read-write module is arranged on the host control circuit board and communicates with a radio frequency electronic tag (11) embedded in a disposable extrusion strap (10), and the unique ID of the radio frequency electronic tag embedded in the disposable extrusion strap, the number of use times set in the radio frequency electronic tag and the use time are subjected to identification and read-write monitoring through a single-chip microcomputer. The device has the advantages that the risk that a patient is injured by explosion of a disposable extrusion strap air bag caused by illegal use of a counterfeit, non-original and inferior extrusion strap, repeated fatigue use, overtime fatigue use and the like is avoided, and the risk of infectious disease transmission caused by repeated use of multiple persons is avoided.

The present disclosure provides a kind of epidemic prevention and management method for enhancing infectious disease through network modeling.It includes four processes: first, according to the detailed epidemic contact information recorded in the survey report, an epidemic correlation graph is constructed;then, by defining a meta-path, a node sequence in a heterogeneous graph is generated using random walk to capture the semantic and structural correlation between multiple nodes in the heterogeneous graph;then, risk factors are introduced and adjusted, i.e.according to the risk factor level provided by the Center for Disease Control and Prevention, the weight coefficient in the random walk process is adjusted, and the risk factors include location ventilation, contact duration, personnel density and behavior habit;finally, point embedding and risk assessment are carried out to assess the importance of nodes and predict high-risk individuals and locations.Compared with the traditional network evaluation method, the present application improves the accuracy of risk prediction.

An MCP flooding attack detection method based on behavior characteristics comprises the following steps: collecting and learning a large amount of legal MCP traffic, extracting parameter length, request interval, nesting depth and response time characteristics, and constructing four-dimensional normal distribution as a legal traffic model based on the parameters, the request interval, the nesting depth and the response time characteristics; the probability density of the feature vector of each new request under the legal model is calculated to judge the abnormal request and the attack type thereof, finally, an SIR infectious disease dynamic model and an ARIMA time sequence model are further innovatively integrated to predict the zombie node scale and the attack trend, and the prediction result is used as input to automatically trigger and adjust a defense strategy; according to the method, botnet attack detection is carried out on the large language model integrated with the MCP protocol by utilizing the multi-dimensional behavior characteristics, so that attack detection and an adaptive defense strategy are effectively realized, and a security protection capability is also provided for a complex network environment in which the large language model is integrated with the MCP protocol; the invention further comprises a system, equipment and a storage medium for implementing the method.

The invention discloses a semi-closed foldable transparent bedspread suitable for aerosol blocking, and belongs to the technical field of respiratory infectious disease protection equipment. Comprising a cross rod, supporting side rods are symmetrically and fixedly connected to the outer side wall of the cross rod, vertical plates are fixedly connected to the upper surfaces of the supporting side rods, short columns are symmetrically and fixedly connected to the outer side walls of the vertical plates, inner rods are rotatably connected to the outer side walls of the short columns, and inner columns are fixedly connected to the outer side walls of the short columns; outer rods are rotationally connected to the outer side walls of the inner columns, fixing rods are fixedly connected between the two inner rods, fixing rods are fixedly connected between the two outer rods, and a foldable transparent outer cover is fixedly connected to the outer side walls of the two fixing rods and the outer side wall of the cross rod jointly.

The invention provides a medical resource allocation method and system, computer equipment and a storage medium, and belongs to the field of public health and preventive medicines.The method comprises the steps that firstly, related data of a target area is collected to construct an improved six-bin SEIRD model, the comprehensive root-mean-square error of six-bin actual and predicted data is minimized through a particle swarm optimization algorithm, and then the target area is obtained; and determining the optimal parameter of each new serious infectious disease stage, and synchronously outputting multi-chamber prediction data. Constructing a multi-objective optimization function, taking minimization of the total number of untreated patients, maximization of patient medical conditions and minimization of medical distance as objectives, adopting dynamic weight coefficient linear combination, combining five types of rigid constraints such as area distribution, hospital capacity and shelter construction, substituting prediction data into solution stage by stage, and solving the prediction data. And outputting an emergency medical treatment point construction time sequence, a spatial layout and a patient distribution strategy. And data of other bins are used for correcting stage division of major infectious diseases, constraint conditions and optimization targets, so that decision scientificity is guaranteed.