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具有非线性发病率的随机流行病模型的进化动力学

The Evolutionary Dynamics of Stochastic Epidemic Model with Nonlinear Incidence Rate.

作者信息

Li Dan, Cui Jing'an, Liu Meng, Liu Shengqiang

机构信息

Department of Mathematics, Harbin Institute of Technology, Harbin, 150001, China.

School of Science, Beijing University of Civil Engineering and Architecture, Beijing, 100044, China.

出版信息

Bull Math Biol. 2015 Sep;77(9):1705-43. doi: 10.1007/s11538-015-0101-9. Epub 2015 Sep 14.

Abstract

A stochastic SIRS epidemic model with nonlinear incidence rate and varying population size is formulated to investigate the effect of stochastic environmental variability on inter-pandemic transmission dynamics of influenza A. Sufficient conditions for extinction and persistence of the disease are established. In the case of persistence, the existence of endemic stationary distribution is proved and the distance between stochastic solutions and the endemic equilibrium of the corresponding deterministic system in the time mean sense is estimated. Based on realistic parameters of influenza A in humans, numerical simulations have been performed to verify/extend our analytical results. It is found that: (i) the deterministic threshold of the influenza A extinction R(S)0 may exist and the threshold parameter will be overestimated in case of neglecting the impaction of environmental noises; (ii) the presence of environmental noises is capable of supporting the irregular recurrence of influenza epidemic, and the average level of the number of infected individuals I(t) always decreases with the increase in noise intensity; and (iii) if R(S)0 > 1, the volatility of I(t) increases with the increase of noise intensity, while the volatility of I(t) decreases with the increase in noise intensity if R(S)0 < 1.

摘要

建立了一个具有非线性发病率和变化人口规模的随机SIRS流行病模型,以研究随机环境变化对甲型流感大流行间期传播动力学的影响。确定了疾病灭绝和持续存在的充分条件。在持续存在的情况下,证明了地方病平稳分布的存在性,并估计了随机解与相应确定性系统的地方病平衡点在时间均值意义上的距离。基于人类甲型流感的实际参数,进行了数值模拟以验证/扩展我们的分析结果。结果发现:(i)甲型流感灭绝的确定性阈值R(S)0可能存在,并且在忽略环境噪声影响的情况下阈值参数会被高估;(ii)环境噪声的存在能够支持流感疫情的不规则复发,并且感染个体数量I(t)的平均水平总是随着噪声强度的增加而降低;以及(iii)如果R(S)0>1,I(t)的波动性随着噪声强度的增加而增加,而如果R(S)0<1,I(t)的波动性随着噪声强度的增加而降低。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac97/7088780/f09d2fad6dcb/11538_2015_101_Fig1_HTML.jpg

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