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The SIS and SIR stochastic epidemic models: A maximum entropy approach

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  • Artalejo, J.R.
  • Lopez-Herrero, M.J.

Abstract

We analyze the dynamics of infectious disease spread by formulating the maximum entropy (ME) solutions of the susceptible-infected-susceptible (SIS) and the susceptible-infected-removed (SIR) stochastic models. Several scenarios providing helpful insight into the use of the ME formalism for epidemic modeling are identified. The ME results are illustrated with respect to several descriptors, including the number of recovered individuals and the time to extinction. An application to infectious data from outbreaks of extended spectrum beta lactamase (ESBL) in a hospital is also considered.

Suggested Citation

  • Artalejo, J.R. & Lopez-Herrero, M.J., 2011. "The SIS and SIR stochastic epidemic models: A maximum entropy approach," Theoretical Population Biology, Elsevier, vol. 80(4), pages 256-264.
  • Handle: RePEc:eee:thpobi:v:80:y:2011:i:4:p:256-264
    DOI: 10.1016/j.tpb.2011.09.005
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    1. zu Dohna, Heinrich & Pineda-Krch, Mario, 2010. "Fitting parameters of stochastic birth–death models to metapopulation data," Theoretical Population Biology, Elsevier, vol. 78(2), pages 71-76.
    2. Sharkey, Kieran J., 2011. "Deterministic epidemic models on contact networks: Correlations and unbiological terms," Theoretical Population Biology, Elsevier, vol. 79(4), pages 115-129.
    3. N. G. Becker & T. Britton, 1999. "Statistical studies of infectious disease incidence," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(2), pages 287-307, April.
    4. Ross, J.V. & Pagendam, D.E. & Pollett, P.K., 2009. "On parameter estimation in population models II: Multi-dimensional processes and transient dynamics," Theoretical Population Biology, Elsevier, vol. 75(2), pages 123-132.
    5. Joshua V Ross & Thomas House & Matt J Keeling, 2010. "Calculation of Disease Dynamics in a Population of Households," PLOS ONE, Public Library of Science, vol. 5(3), pages 1-9, March.
    6. Ronald Meester & Jan Koning & Mart C. M. Jong & Odo Diekmann, 2002. "Modeling and Real-Time Prediction of Classical Swine Fever Epidemics," Biometrics, The International Biometric Society, vol. 58(1), pages 178-184, March.
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    Cited by:

    1. Velarde, Carlos & Robledo, Alberto, 2021. "Statistical mechanical model for growth and spread of contagions under gauged population confinement," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
    2. Alrebdi, H.I. & Steklain, Andre & Amorim, Edgard P.M. & Zotos, Euaggelos, 2023. "Thermostated Susceptible-Infected-Susceptible epidemic model," Applied Mathematics and Computation, Elsevier, vol. 441(C).

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