Modelling epidemic spreading in structured organisations

被引:7
|
作者
Kuikka, Vesa [1 ]
机构
[1] Finnish Def Res Agcy, Tykkikentantie 1,POB 10, Riihimaki 11311, Finland
关键词
Epidemic spreading; Structured organisation; Complex network; Bridge node; Herd immunity; COVID-19;
D O I
10.1016/j.physa.2022.126875
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Modelling epidemic spreading in a population or in organisations is important in planning preventive measures and allocating resources for treating infected individuals in hospitals. We present a structural spreading model capable of describing detailed structures of organisations. We discuss methods and results with the help of an example organisation. The example organisation is a real-world organisation but our main focus is on presenting modelling approaches. Our spreading model is designed for describing indirect virus spreading mechanics via respiratory droplets and aerosols from an infected person rather than spreading via physical person to person contacts. To this end, we propose a new complex contagion model that describes the spreading process alike a social interaction process. Different preventive measures and their combinations can be compared by our model. We show that the optimised preventive measures in the complex contagion model can be different from the corresponding simple contagion model. We study the effects of limiting contacts between different organisation structures and shortening chains of infection together with general risk mitigation actions. Out-centrality, in-centrality and betweenness measures are used in analysing different aspects of epidemic spreading. Examples of calculating community immunity are presented, in which strategies based on out-centrality and betweenness measures are prioritised. (c) 2022 The Author. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
引用
收藏
页数:23
相关论文
共 50 条
  • [1] Networks to Stop the Epidemic Spreading
    Fioriti, Vincenzo
    Chinnici, Marta
    Arbore, Andrea
    Sigismondi, Nicola
    Roselli, Ivan
    UNIVERSAL ACCESS IN HUMAN-COMPUTER INTERACTION. ACCESS TO MEDIA, LEARNING AND ASSISTIVE ENVIRONMENTS, UAHCI 2021, PT II, 2021, 12769 : 358 - 366
  • [2] How the reversible change of contact networks affects the epidemic spreading
    Xincheng Shu
    Zhongyuan Ruan
    Nonlinear Dynamics, 2024, 112 : 731 - 739
  • [3] How the reversible change of contact networks affects the epidemic spreading
    Shu, Xincheng
    Ruan, Zhongyuan
    NONLINEAR DYNAMICS, 2024, 112 (01) : 731 - 739
  • [4] Epidemic spreading in complex networks with spreading delay based on cellular automata
    Wang Ya-Qi
    Jiang Guo-Ping
    ACTA PHYSICA SINICA, 2011, 60 (08)
  • [5] Influence of dynamic immunization on epidemic spreading in networks
    Wu, Qingchu
    Fu, Xinchu
    Jin, Zhen
    Small, Michael
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2015, 419 : 566 - 574
  • [6] Influence of periodic traffic congestion on epidemic spreading
    Zheng, Muhua
    Ruan, Zhongyuan
    Tang, Ming
    Do, Younghae
    Liu, Zonghua
    INTERNATIONAL JOURNAL OF MODERN PHYSICS C, 2016, 27 (05):
  • [7] Multi-regional epidemic spreading in transportation network: Modelling and optimal control strategies
    Jiang J.-H.
    Sheng D.
    Yang P.
    Kongzhi yu Juece/Control and Decision, 2023, 38 (06): : 1695 - 1702
  • [8] Critical time-dependent branching process modelling epidemic spreading with containment measures*
    Sun, Hanlin
    Kryven, Ivan
    Bianconi, Ginestra
    JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL, 2022, 55 (22)
  • [9] Identifying epidemic spreading dynamics of COVID-19 by pseudocoevolutionary simulated annealing optimizers
    Choujun Zhan
    Yufan Zheng
    Zhikang Lai
    Tianyong Hao
    Bing Li
    Neural Computing and Applications, 2021, 33 : 4915 - 4928
  • [10] Epidemic spreading on networks with vaccination
    史红静
    段志生
    陈关荣
    李嵘
    Chinese Physics B, 2009, 18 (08) : 3309 - 3317