11 results about "Epidemic spread" patented technology

The invention discloses an animal epidemic disease port remote real-time monitoring and early warning system, and relates to the technical field of Internet of Things monitoring, and the system comprises a state evaluation module which is used for obtaining various real-time parameters in an animal port so as to determine a risk state index of the animal port; through the system, an abnormal detection area can be rapidly identified, a grading early warning mechanism is automatically triggered, quarantine personnel are assisted to preferentially dispose high-risk point locations, and an epidemic disease transmission chain is effectively blocked; in addition, through a spatial hot spot analysis technology, the system can visually display a core detection area of epidemic disease distribution, and a scientific basis is provided for accurate prevention and control; a real-time risk map and an intelligent algorithm are combined, an optimal disposal path is automatically planned, a high-risk detection area is avoided, and the epidemic situation diffusion risk is reduced to the maximum extent; meanwhile, aiming at the problem of resource shortage in an emergency scene, the system dynamically coordinates epidemic prevention resources through an elastic scheduling mechanism, can match available epidemic prevention stations nearby, and optimizes a carrier and personnel allocation scheme.

This invention discloses a method for optimizing the allocation of epidemic prevention and control resources based on complex networks. The method includes: acquiring big data from online social platforms to measure participants' attitudes and opinions on epidemics and corresponding prevention and control measures; designing and executing specific decision-making experiments to measure participants' feedback to different types of incentives and information; analyzing experimental results and data to extract individual behavioral rules in different research scenarios and constructing a new generation of agent-based epidemic transmission models; conducting multi-layer community analysis based on deep learning to achieve accurate community discovery within a multi-layer framework; combining community discovery with impact maximization research to identify key user sets in the multi-layer system, allocate prevention and control resources, explore the evolutionary patterns of epidemics, and achieve optimized control of the epidemic transmission process under multi-dimensional uncertainties in parameters and models. This invention contributes to the rational allocation of epidemic prevention and control resources, providing effective protection for the lives and health of the people.

The application discloses a fluorescent PCR kit for detecting pseudorabies virus and application, the kit comprises a primer and probe combination for detecting the pseudorabies virus and a primer and probe combination of an internal standard, the nucleotide sequence of the upstream primer for detecting the pseudorabies virus is shown in SEQ ID NO: 7, the nucleotide sequence of the downstream primer is shown in SEQ ID NO: 8, and the nucleotide sequence of the probe is shown in SEQ ID NO: 9; the nucleotide sequence of the upstream primer of the primer and probe combination of the internal standard is shown in SEQ ID NO: 10, the nucleotide sequence of the downstream primer is shown in SEQ ID NO: 11, and the nucleotide sequence of the probe is shown in SEQ ID NO: 12. The minimum detection limit of the kit is 1.5*10 2 copies / mL, which is at least 10 times higher than that of a national standard method, the kit has excellent specificity, and is helpful to realize rapid diagnosis and early prevention and control and reduce the risk of epidemic spread.

The invention relates to the technical field of yak epidemic disease prevention and control, and discloses a disinfecting and killing device for yak epidemic disease prevention and control, the disinfecting and killing device comprises a support, a box body, a disinfectant storage tank, a sensor, an execution mechanism, spraying devices and a control box, the bottom of the box body is provided with a yak channel, and the spraying devices are arranged on the two sides of the inner wall of the yak channel; the disinfectant storage tank is arranged outside the box body and is connected with the box body through a first pipeline, and the box body is connected with the spraying device through a second pipeline; the sensors are arranged at the two ends of the yak channel and used for detecting the positions of yaks. A control module is arranged in the control box, and the control module is electrically connected with the sensor and the executing mechanism. Compared with the prior art, the yak disinfection device has the following advantages and effects that automatic spraying disinfection is carried out when yaks pass through the yak channel, the disinfection effect is ensured, automation of the disinfection process is achieved, epidemic disease transmission is effectively prevented, operators do not need to make close contact with the yaks and disinfectant, and the infection risk is greatly reduced.

The invention discloses a multivariate coupling epidemic propagation prediction method and system, and relates to the technical field of epidemic prediction, and the method comprises the steps: obtaining a current optimal state estimation value and policy intervention intensity based on an extended Kalman filtering algorithm in combination with an optimal state estimation value at a previous moment and a real observation error; aggregating the social public opinion text risk scores to obtain a social information pressure index, generating group alertness in combination with a three-state model, and determining climate regulation factors according to meteorological data; constructing a dynamic regulation factor and a dynamic propagation rate based on the group alertness, the climate regulation factor, the policy intervention intensity and the external input risk, and substituting the dynamic regulation factor and the dynamic propagation rate into the differential equation set to calculate a state evolution sequence; and through game theory multi-objective optimization, iteratively minimizing a comprehensive decision loss function containing economic, healthy and fatigue weights, and outputting an epidemic situation state prediction curve and optimal policy intervention intensity. Unified coupling of multiple subsystems is achieved, prediction precision is improved, quantitative decision support is provided for scientific prevention and control, and the method is suitable for complex epidemic propagation scenes.

The invention provides an epidemic disease prediction method and device based on a large language model, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining initial environment data in a preset simulation environment and initial state data of a plurality of preset agents; generating initial context information based on the initial environment data and the initial state data; generating an initial cue word in combination with a thinking chain action cue strategy; inputting the initial cue word into a large language model to obtain an initial action instruction; repeatedly executing iteration steps for preset times to update the initial environment data, the initial state data and the initial action instruction to obtain corresponding intermediate environment data, intermediate state data and intermediate action instruction; and based on the intermediate environment data, performing nonlinear fitting on the epidemic propagation state in the preset time period to obtain an epidemic prediction result. According to the epidemic disease prediction method and device based on the large language model provided by the invention, the prediction accuracy of the epidemic disease transmission state is improved.

The invention discloses an infectious disease transmission simulation-prediction integrated modeling method based on ensemble populations, and belongs to the technical field of infectious disease monitoring and prediction, and the method comprises the following steps: S1, obtaining the historical data of infectious disease transmission; s2, filling the infectious disease data of the adjacent areas; s3, obtaining a time fusion feature; s4, constructing an interaction relation network among the set populations, and performing multi-layer spatial-temporal feature extraction to obtain multi-layer fusion spatial-temporal features; s5, outputting double-branch reconstruction decoding and prediction decoding; and S6, obtaining an initial prediction result in combination with double-branch reconstruction decoding and prediction decoding, and outputting simulation of infectious disease data in an unknown region and prediction of future propagation of all regions. According to the method, the dynamic law of case propagation can be accurately described, and the propagation condition of an unknown region can be simulated, so that a reliable theoretical basis and technical support can be provided for formulating and implementing a disease prevention and control strategy.

The invention discloses a self-media influence-fused consciousness-epidemic disease co-evolution transmission analysis method, which aims at the limitation that the existing epidemic disease model does not fully consider the key influence of self-media on public consciousness awakening and epidemic disease transmission. Through crawling and integrating social media and disease prevention and control data, a double-layer coupling network model of consciousness-epidemic disease co-evolution propagation under a self-media background is constructed; wherein the upper-layer virtual contact network realizes consciousness diffusion through interaction between a common individual and a self-media node, and the lower-layer physical contact network nodes are in one-to-one correspondence with the upper-layer virtual contact network to simulate an infectious disease transmission process; a microcosmic Markov chain method is proposed to analyze a model dynamics process, and the influence of self-media propaganda guidance and individual awareness on epidemic disease outbreak is quantitatively analyzed by establishing a state transition equation set and deducing a critical threshold value under a steady state condition; according to the invention, a quantitative analysis tool is provided for propagation law research and accurate intervention control of sudden epidemic diseases in a we-media environment.

The application provides an influenza prediction method, system, device and medium based on epidemic dynamics, and relates to the technical field of epidemic transmission prediction, which realizes collaborative modeling of data-driven and mechanism-driven by fusing multiple source monitoring data and epidemic transmission mechanism; in the feature engineering stage, the influenza monitoring data is structured and features are extracted, forming influenza transmission features with physical meaning; in the prediction stage, a physical information neural network model based on a deep neural network framework is used, which includes an input layer, a multi-layer feedforward network, a time embedding representation layer and an output layer, and is trained by fusing an observation data fitting and a composite loss function constrained by the epidemic dynamics mechanism, so that the model can fit the historical monitoring data and strictly follow the internal dynamics law of disease transmission, thereby significantly improving the accuracy, interpretability, extrapolation stability and robustness to small samples and noise interference of the prediction result.

The present application relates to pig house breeding system technical field, especially to a kind of pig house disinfection, deodorization, epidemic prevention breeding system, including collection module, it is used to the current pig house in environmental information collection, analysis module, it is connected with collection module, for according to the current pig house in environmental information analysis, and generate analysis result, storage module, it is connected with collection module and analysis module, for the pig house information and the data of analysis module derived are stored, output module, it is connected with analysis module, it is used to the analysis result of analysis module is collected, and analysis result is output. Therefore, the present application can view the real-time state of each stall in pig house in real time, facilitate the adjustment of stall in abnormal state by technical personnel, and the stall in warning state can be killed in time, prevent epidemic spread.

The invention provides an epidemic co-evolution modeling method and system driven by multi-source information, and belongs to the technical field of epidemic propagation kinetics, and the method comprises the steps: obtaining cognitive information and official information; constructing a double-layer self-adaptive sequential network in which the virtual social contact layer and the physical contact layer are in one-to-one correspondence; integrating a self-adaptive reconnection mechanism driven by cognitive information and a mandatory adjustment mechanism driven by official information in the framework; constructing and solving a kinetic model based on the integrated framework, and obtaining a quantitative mapping relationship between the propagation threshold and the behavior parameters; and based on the relationship, simulating and evaluating propagation scales under different behavior strategies, and outputting prevention and control optimization indexes. By uniformly modeling heterogeneous behavior response driven by multi-source information and real-time dynamic coupling of the heterogeneous behavior response and disease transmission, the defect that an existing model behavior feedback mechanism is single or split is overcome, more accurate simulation of epidemic disease transmission is achieved, and a decision basis is provided for formulating an accurate and efficient public health intervention strategy.