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arXiv 2007.06636math.PR
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一个空间随机传染病模型:Law of Large Numbers和中心极限定理

A Spatial Stochastic Epidemic Model: Law of Large Numbers and Central Limit Theorem

Samuel Bowong Tsakou, Alphonse Emakoua, Etienne Pardoux

摘要:

考虑连续空间中基于个体的SIR随机传染病模型。流行病的演变涉及个人的感染率和治愈率。我们假设个体在二维环面上按照独立的布朗运动随机运动。我们定义的经验措施$μ^{S,N}$,$μ^{I,N}$和$μ^{R,N}$描述的易感,感染和删除的个人的位置的演变。证明了序列$(μ^{S,N},μ^{I,N})$向抛物型偏微分方程组的$(μ^{S},μ^{I})$解的概率收敛性,即$N\rightarrow \infty$.我们证明了序列$(U^{N}=\sqrt{N}(μ^{S,N}-μ^{S}),V^{N}=\sqrt{N}(μ^{I,N}-μ^{I}))$的收敛规律,作为$N\rightarrow\infty$,对高斯分布值的过程,解决方案的线性偏微分方程系统的高度奇异高斯驱动过程。在个体不动的情况下,我们还定义并研究了序列$(μ^{S,N},μ^{I,N})$的大数定律和中心极限定理。

英文摘要:

We consider an individual-based SIR stochastic epidemic model in continuous space. The evolution of the epidemic involves the rates of infection and cure of individuals. We assume that individuals move randomly on the two-dimensional torus according to independent Brownian motions. We define the empirical measures $μ^{S,N}$, $μ^{I,N}$ and $μ^{R,N}$ which describe the evolution of the position of the susceptible, infected and removed individuals. We prove the convergence in propbability, as $N\rightarrow \infty$, of the sequence $(μ^{S,N},μ^{I,N})$ towards $(μ^{S},μ^{I})$ solution of a system of parabolic PDEs. We show that the sequence $(U^{N}=\sqrt{N}(μ^{S,N}-μ^{S}),V^{N}=\sqrt{N}(μ^{I,N}-μ^{I}))$ converges in law, as $N\rightarrow\infty$, towards a Gaussian distribution valued process, solution of a system of linear PDEs with highly singular Gaussian driving processes. In the case where the individuals do not move we also define and study the law of large numbers and central limit theorem of the sequence $(μ^{S,N},μ^{I,N})$.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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