TY - JOUR
T1 - A stochastic SIRS epidemic model with nonlinear incidence rate
AU - Cai, Yongli
AU - Kang, Yun
AU - Wang, Weiming
N1 - Funding Information:
This research was supported by the National Science Foundation of China (61672013, 11601179 & 61373005), the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (16KJB110003). The research of Y. Kang was partially supported by NSF-DMS (1313312) and the research scholarship from School of Letters and Sciences.
Publisher Copyright:
© 2017 Elsevier Inc.
PY - 2017/7/15
Y1 - 2017/7/15
N2 - In this paper, we investigate the global dynamics of a general SIRS epidemic model with a ratio-dependent incidence rate and its corresponding stochastic differential equation version. For the deterministic model, we show that the basic reproduction number R0 determines whether there is an endemic outbreak or not: if R0<1, the disease dies out; while if R0>1, the disease persists. For the stochastic model, we show that its related reproduction number R0S can determine whether there is a unique disease-free stationary distribution or a unique endemic stationary distribution. In addition, we provide analytic results regarding the stochastic boundedness and permanence/extinction. One of the most interesting findings is that random fluctuations introduced in our stochastic model can suppress disease outbreak, which can provide us some useful control strategies to regulate disease dynamics.
AB - In this paper, we investigate the global dynamics of a general SIRS epidemic model with a ratio-dependent incidence rate and its corresponding stochastic differential equation version. For the deterministic model, we show that the basic reproduction number R0 determines whether there is an endemic outbreak or not: if R0<1, the disease dies out; while if R0>1, the disease persists. For the stochastic model, we show that its related reproduction number R0S can determine whether there is a unique disease-free stationary distribution or a unique endemic stationary distribution. In addition, we provide analytic results regarding the stochastic boundedness and permanence/extinction. One of the most interesting findings is that random fluctuations introduced in our stochastic model can suppress disease outbreak, which can provide us some useful control strategies to regulate disease dynamics.
KW - Basic reproduction number
KW - Epidemic model
KW - Global stability
KW - Permanence
KW - Stationary distribution
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U2 - 10.1016/j.amc.2017.02.003
DO - 10.1016/j.amc.2017.02.003
M3 - Article
AN - SCOPUS:85013657162
SN - 0096-3003
VL - 305
SP - 221
EP - 240
JO - Applied Mathematics and Computation
JF - Applied Mathematics and Computation
ER -