• DocumentCode
    695041
  • Title

    Agent-Based Derivation of the SIR-Differential Equations

  • Author

    Bicher, Martin ; Popper, Niki

  • Author_Institution
    Inst. of Anal. ans Sci. Comput., Vienna Univ. of Technol., Vienna, Austria
  • fYear
    2013
  • fDate
    10-13 Sept. 2013
  • Firstpage
    306
  • Lastpage
    311
  • Abstract
    Due to exponentially increasing computational resources, individual-based models are getting more and more popular among epidemiologists. Inspired by SIR (Susceptible-Infected-Recovered) epidemics very complex and flexible models for diseases and vaccine strategies can be created accepting the risk, that maybe unexplained and unpredictable chaotic group-behavior could distort the results. Preventive theoretical analysis of these microscopic models is still very difficult. Based on the idea of diffusion approximation a technique is presented, how the mean value of a simple predefined agent-based SIR model can be calculated to asymptotically satisfy the classic SIR differential equations by Kermack and McKendrick. This technique can be generalized to contribute to the analysis of agent-based models and can help developing hybrid models.
  • Keywords
    chaos; differential equations; diseases; epidemics; SIR differential equations; agent-based SIR model; agent-based derivation; agent-based models; chaotic group-behavior; complex models; computational resources; diffusion approximation; diseases; flexible models; mean value; microscopic models; preventive theoretical analysis; susceptible-infected-recovered epidemics; vaccine strategies; Agent-based; Diffusionapproximation; Epidemics; Fokker-Planck equation; Kramers-Moyal decomposition; Markov-modelling; SIR;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Modelling and Simulation (EUROSIM), 2013 8th EUROSIM Congress on
  • Conference_Location
    Cardiff
  • Type

    conf

  • DOI
    10.1109/EUROSIM.2013.62
  • Filename
    7004961