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 language | English |
|---|---|
| Article number | 2 |
| Journal | Journal of Mathematical Biology |
| Volume | 88 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Exponential ergodicity
- Hospital capacity
- Nonlinear treatment rate
- SIR epidemic model
- Stochastic fluctuations
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