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Stochastic modeling of influenza spread dynamics with recurrences

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  • John Whitman
  • Ciriyam Jayaprakash

Abstract

We present results of a study of a simple, stochastic, agent-based model of influenza A infection, simulating its dynamics over the course of one flu season. Building on an early work of Bartlett, we define a model with a limited number of parameters and rates that have clear epidemiological interpretation and can be constrained by data. We demonstrate the occurrence of recurrent behavior in the infected number [more than one peak in a season], which is observed in data, in our simulations for populations consisting of cohorts with strong intra- and weak inter-cohort transmissibility. We examine the dependence of the results on epidemiological and population characteristics by investigating their dependence on a range of parameter values. Finally, we study infection with two strains of influenza, inspired by observations, and show a counter-intuitive result for the effect of inoculation against the strain that leads to the first wave of infection.

Suggested Citation

  • John Whitman & Ciriyam Jayaprakash, 2020. "Stochastic modeling of influenza spread dynamics with recurrences," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-27, April.
    • Handle: RePEc:plo:pone00:0231521
    DOI: 10.1371/journal.pone.0231521
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    References listed on IDEAS

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    1. Carol Y. Lin, 2008. "Modeling Infectious Diseases in Humans and Animals by KEELING, M. J. and ROHANI, P," Biometrics, The International Biometric Society, vol. 64(3), pages 993-993, September.
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