Personal Information

  • (Associate professor)
  • Name (Pinyin):

    liuyong
  • School/Department:

    理学院
  • Gender:

    Male
  • Professional Title:

    Associate professor
  • Status:

    Employed
  • Discipline:

    Mathematics

Study on the regional risk classification method for the prevention and control of emerging infectious diseases based on directed graph theory

  • Release time:2026-10-17
  • Hits:
  • Affiliation of Author(s):

    理学院
  • Journal:

    Frontiers in Public Health
  • Key Words:

    scale-free network, emerging infectious diseases, graph theory, grading and zoning, epidemic
  • Abstract:

    Background: Emerging infectious diseases are a class of diseases that are spreading rapidly and are highly contagious. It seriously aPurpose: We aim to propose an eMethods: Using the graph theory method, we first define the network structure of social groups and construct the risk transmission network of the new epidemic region. Then, combined with the risk classification method, the classification of high, medium, and low risk levels of the new epidemic region is discussed from two cases with common and looped graph nodes, respectively. Finally, the reasonableness of the classification method is verified by simulation data. Results: The directed weighted scale-free network can better describe the transmission law of an epidemic. Moreover, the proposed method of classifying the risk level of a region by using the correlation function between two regions and the risk value of the regional nodes can eConclusions: It is necessary to distinguish scientifically between the risk level of the epidemic area and the neighboring regions so that the constructed social network model of the epidemic region’s spread risk can better describe the spread of the epidemic risk in the social network relations.
  • First Author:

    zhangchongqi,liuyong
  • Indexed by:

    Journal paper
  • Correspondence Author:

    王笑
  • Translation or Not:

    no
  • Date of Publication:

    2023-09-25
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