Threshold behavior and exponential ergodicity of an sir epidemic model: the impact of random jamming and hospital capacity

Guijie Lan, Sanling Yuan, Baojun Song

Research output: Contribution to journalArticlepeer-review

Abstract

This article uses hospital capacity to determine the treatment rate for an infectious disease. To examine the impact of random jamming and hospital capacity on the spread of the disease, we propose a stochastic SIR model with nonlinear treatment rate and degenerate diffusion. Our findings demonstrate that the disease’s persistence or eradication depends on the basic reproduction number R0s . If R0s<1 , the disease is eradicated with a probability of 1, while R0s>1 results in the disease being almost surely strongly stochastically permanent. We also demonstrate that if R0s>1 , the Markov process has a unique stationary distribution and is exponentially ergodic. Additionally, we identify a critical capacity which determines the minimum hospital capacity required.

Original languageEnglish
Article number2
JournalJournal of Mathematical Biology
Volume88
Issue number1
DOIs
StatePublished - Jan 2024

Keywords

  • Exponential ergodicity
  • Hospital capacity
  • Nonlinear treatment rate
  • SIR epidemic model
  • Stochastic fluctuations

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