2nd International ICST Conference on Bio-Inspired Models of Network, Information, and Computing Systems

Research Article

Epidemic Spreading on Weighted Contact Networks

Download25 downloads
  • @INPROCEEDINGS{10.4108/ICST.BIONETICS2007.2435,
        author={P. Schumm and C. Scoglio and D. Gruenbacher and T. Easton},
        title={Epidemic Spreading on Weighted Contact Networks},
        proceedings={2nd International ICST Conference on Bio-Inspired Models of Network, Information, and Computing Systems},
        publisher={IEEE},
        proceedings_a={BIONETICS},
        year={2008},
        month={8},
        keywords={Epidemiology  agent based  aggregate  dynamic parallel network simulation  weighted contact networks},
        doi={10.4108/ICST.BIONETICS2007.2435}
    }
    
  • P. Schumm
    C. Scoglio
    D. Gruenbacher
    T. Easton
    Year: 2008
    Epidemic Spreading on Weighted Contact Networks
    BIONETICS
    ICST
    DOI: 10.4108/ICST.BIONETICS2007.2435
P. Schumm1,*, C. Scoglio1,*, D. Gruenbacher1,*, T. Easton2,*
  • 1: EECE Kansas State University
  • 2: IMSE Kansas State University
*Contact email: pbshumm@ksu.edu, caterina@ksu.edu, grue@ksu.edu, teaston@ksu.edu

Abstract

The study of epidemics is a crucial issue to several areas. An epidemic can have devastating economic and social consequences. A single crop disease in Kansas could destroy the yearly income of many farmers. Previous work using graph theory has determined a universal epidemic threshold found in the graph topology for a binary contact network in the compartmental Susceptible-Infected (SI) analysis. We expand this threshold to a more realistic measure. A binary uniform level of contact within a society is too idealistic and an improved threshold is found in allowing a spectrum of contact within a contact network. The expanded contact network also allows for asymmetric contact such as a mother caring for her child. Further study in this area should lead to improved simulators, disease modeling, policies and control of infectious diseases and viruses.