An application of small-world network on predicting the behavior of infectious disease on campus

作     者：Guojin Wang Wei Yao 

作者机构：School of ManagementFudan University220 Handan RoadShanghai200433China Shanghai Key Laboratory of Acupuncture Mechanism and Acupoint FunctionFudan University220 Handan RoadShanghai200433China 

出 版 物：《Infectious Disease Modelling》 (传染病建模（英文）)

年 卷 期：2024年第9卷第1期

页      面：177-184页

核心收录：

学科分类：1004[医学-公共卫生与预防医学(可授医学、理学学位)] 100401[医学-流行病与卫生统计学] 10[医学] 

基　　金：funded by National Natural Science Foundation of China(grant number:12172092) Shanghai Key Laboratory of Acupuncture Mechanism and Acupoint Function(grant number:21DZ2271800) 

主　　题：Small-world network Complex networks Infectious disease on campus Susceptible-infected model Numerical simulation Shared nodes between networks 

摘      要：Networks haven been widely used to understand the spread of infectious *** study examines the properties of small-world networks in modeling infectious disease on *** different small-world models are developed and the behaviors of infectious disease in the models are observed through numerical *** results show that the behavior pattern of infectious disease in a small-world network is different from those in a regular network or a random *** spread of the infectious disease increases as the proportion of long-distance connections p increasing,which indicates that reducing the contact among people is an effective measure to control the spread of infectious *** probability of node position exchange in a network(p2)had no significant effect on the spreading speed,which suggests that reducing human mobility in closed environments does not help control infectious ***,the spreading speed is proportional to the number of shared nodes(s),which means reducing connections between different groups and dividing students into separate sections will help to control infectious *** the end,the simulating speed of the small-world network is tested and the quadratic relationship between simulation time and the number of nodes may limit the application of the SW network in areas with large populations.