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Epidemic propagation control method for implementing isolation by considering individual infection states and individual attributes

A control method and epidemic technology, applied in the field of epidemic transmission, can solve problems such as waste of resources, neglect of activity and attraction, isolation and control of individuals without infection status, etc.

Active Publication Date: 2021-04-02
SHANGHAI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this type of immune method only considers the structural information of the individual, but ignores the infection status and attribute information of the individual, such as the activity and attractiveness of the individual, and does not implement effective isolation control for infected individuals, which will cause relatively high economic costs. High and resource-wasting cost

Method used

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  • Epidemic propagation control method for implementing isolation by considering individual infection states and individual attributes
  • Epidemic propagation control method for implementing isolation by considering individual infection states and individual attributes
  • Epidemic propagation control method for implementing isolation by considering individual infection states and individual attributes

Examples

Experimental program
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Effect test

Embodiment 1

[0064] see figure 1 and figure 2 , a method for controlling the spread of an epidemic that considers individual infection status and individual attributes to implement isolation, the method is applied to a time series network, and the operation steps are as follows:

[0065] Step S1: Initialize the activity and attractive attributes of nodes in the network;

[0066] Step S2: Time series network structure evolution;

[0067] Step S3: Simulate the epidemic spreading process according to the time series network structure;

[0068] Step S4: Statistically calculate the proportion of infected nodes in the network at steady state;

[0069] Step S5: Under random isolation measures and isolation rate π, the critical infection rate threshold λ of the epidemic c .

[0070] This embodiment considers the individual infection status and individual attributes to implement the epidemic transmission control method of isolation, which provides a basis for judging whether ...

Embodiment 2

[0072] This embodiment is basically the same as Embodiment 1, especially in that:

[0073] In this embodiment, the attractive activity-driven temporal network model is used to construct a temporal network, and the "susceptible (S)-infected (I)-susceptible (S)" propagation is used to simulate the epidemic propagation process, and random isolation is adopted. measure.

[0074] see figure 1 , figure 1 It is a schematic flowchart of a method for controlling the spread of an epidemic that considers individual infection status and individual attributes to implement isolation provided by the embodiment of the present application. Depend on figure 1 It can be seen that this embodiment mainly includes the following processes:

[0075] Step S1: Initialize the activity and attractive attributes of nodes in the network;

[0076] Step S2: Time series network structure evolution;

[0077] Step S3: Simulate the epidemic spreading process according to the time series netw...

Embodiment 3

[0112] See figure 1 , the processes of steps S1, S2, and S4 are the same as those in Embodiment 1, except that step S3.7 adopts "object isolation considering activity" and does not include step S5. details as follows:

[0113] Step S3.1: using the "SIS" propagation model to simulate the virus propagation process;

[0114] Step S3.2: Randomly select a certain proportion of nodes as the initial I-state seed nodes;

[0115] Step S3.3: The network evolves according to the rules of steps S2.1-S2.3 every time Δt;

[0116] Step S3.4: Node i updates its own epidemic status. When node i is in S state, each I-state neighbor j of node i infects node i with probability λ. When node i is in the I state, it returns to the S state with probability μ, and maintains the I state with probability 1-μ.

[0117] Step S3.5: After node i changes from S state to I state, the activity and attractiveness of node i will change according to active isolation measures and passive isolatio...

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Abstract

The invention discloses an epidemic propagation control method for implementing isolation by considering individual infection states and individual attributes. The invention discloses a sequential network epidemiological research method considering an individual state and intervention measures, and the method comprises the steps: firstly, initializing the activity and attraction attributes of nodes in a network; secondly, carrying out time sequence network structure evolution; then, selecting a passive isolation strategy and an isolation rate pi, and simulating an epidemic propagation processaccording to a time sequence network structure; then, counting the infection state node proportion of the network in a steady state; and finally, deducing a critical infection rate threshold [lambda]cof the epidemic disease under a random isolation measure and an isolation rate pi. According to the method, active isolation, passive isolation and other control measures are taken into considerationon the timing sequence network model conforming to the real situation, the critical infection rate threshold [lambda]c under the random isolation strategy is derived through the mean field approximation method, and a basis is provided for judging whether epidemic diseases can be spread in crowds or not and analyzing the efficiency of the isolation measures.

Description

technical field [0001] The present invention relates to the technical field of epidemic transmission, in particular to an epidemic transmission dynamics and control method that considers individual infection status and individual attributes to implement isolation. Background technique [0002] In the field of epidemic transmission, it is usually necessary to use various control methods to suppress the spread of epidemics. Common control methods include: active isolation and passive isolation. Active isolation means that when a susceptible individual becomes an infected individual, the infected individual actively reduces their chances of contact with the outside world. At the same time, susceptible individuals selectively reduce their contact with infected individuals. Passive isolation is a compulsory measure taken by the government and other departments to send infected individuals to hospitals for isolation and treatment. Infected individuals admitted to the hospital c...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/50G16H50/80
CPCG16H50/50G16H50/80Y02A90/10
Inventor 王冰解泽洋韩越兴
Owner SHANGHAI UNIV
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