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On the Dynamical Complexity of a Seasonally Forced Discrete SIR Epidemic Model with a Constant Vaccination Strategy

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  • Jalil Rashidinia
  • Mehri Sajjadian
  • Jorge Duarte
  • Cristina Januário
  • Nuno Martins

Abstract

In this article, we consider the discretized classical Susceptible-Infected-Recovered (SIR) forced epidemic model to investigate the consequences of the introduction of different transmission rates and the effect of a constant vaccination strategy, providing new numerical and topological insights into the complex dynamics of recurrent diseases. Starting with a constant contact (or transmission) rate, the computation of the spectrum of Lyapunov exponents allows us to identify different chaotic regimes. Studying the evolution of the dynamical variables, a family of unimodal-type iterated maps with a striking biological meaning is detected among those dynamical regimes of the densities of the susceptibles. Using the theory of symbolic dynamics, these iterated maps are characterized based on the computation of an important numerical invariant, the topological entropy. The introduction of a degree (or amplitude) of seasonality, , is responsible for inducing complexity into the population dynamics. The resulting dynamical behaviors are studied using some of the previous tools for particular values of the strength of the seasonality forcing, . Finally, we carry out a study of the discrete SIR epidemic model under a planned constant vaccination strategy. We examine what effect this vaccination regime will have on the periodic and chaotic dynamics originated by seasonally forced epidemics.

Suggested Citation

  • Jalil Rashidinia & Mehri Sajjadian & Jorge Duarte & Cristina Januário & Nuno Martins, 2018. "On the Dynamical Complexity of a Seasonally Forced Discrete SIR Epidemic Model with a Constant Vaccination Strategy," Complexity, Hindawi, vol. 2018, pages 1-11, December.
    • Handle: RePEc:hin:complx:7191487
    DOI: 10.1155/2018/7191487
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    References listed on IDEAS

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    1. Hu, Zengyun & Teng, Zhidong & Zhang, Tailei & Zhou, Qiming & Chen, Xi, 2017. "Globally asymptotically stable analysis in a discrete time eco-epidemiological system," Chaos, Solitons & Fractals, Elsevier, vol. 99(C), pages 20-31.
    2. Willox, R. & Grammaticos, B. & Carstea, A.S. & Ramani, A., 2003. "Epidemic dynamics: discrete-time and cellular automaton models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 328(1), pages 13-22.
    3. Ramani, A. & Carstea, A.S. & Willox, R. & Grammaticos, B., 2004. "Oscillating epidemics: a discrete-time model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 333(C), pages 278-292.
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    Cited by:

    1. Noureddine Djenina & Adel Ouannas & Iqbal M. Batiha & Giuseppe Grassi & Taki-Eddine Oussaeif & Shaher Momani, 2022. "A Novel Fractional-Order Discrete SIR Model for Predicting COVID-19 Behavior," Mathematics, MDPI, vol. 10(13), pages 1-16, June.

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