Liu Zihong, He Ku, Yang Lei, Bian Chao, Wang Zhihua
Student Member, IEEE, Department of Electronic Engineering, Tsinghua University, Beijing, 100084, China.
Conf Proc IEEE Eng Med Biol Soc. 2005;2005:7463-9. doi: 10.1109/IEMBS.2005.1616238.
Severe Acute Respiratory Syndrome (SARS), the first epidemic of the 21st century, has an outbreak history of more than 2 years till today and caused tremendous damage to the human society. Accordingly, many studies on modeling the SARS epidemic have been reported, whereas deficiencies were still lying in those models because of their separate space/time methodology. In this paper, we propose novel comprehensive stochastic spatio-temporal models from both of the macro aspect and individual aspect for characterizing transmission and control of the SARS disease. Based on a new SARS spread process in consideration of "suspicious" population, we firstly establish the stochastic temporal models from two different aspects: the macro model is described with birth-death process and the individual Markov model is described with probability transition matrix (PTM). And then, we amalgamate the deterministic/stochastic population-flow model with the stochastic temporal models together to set up the comprehensive stochastic spatio-temporal models. Simulations on computer have evaluated the effect of various realistic parameters and control policies, and also have testified the accuracy and efficacy of the new models. Additionally, particular studies on the cases of Tsinghua University and Beijing City are presented. The comprehensive stochastic spatio-temporal models have considerably reduced the complexity plus errors as compared with previous works and will be able to characterize other various epidemics, e.g. Avian Flu.
严重急性呼吸综合征（SARS）作为21世纪的首次疫情，截至如今已有两年多的爆发历史，并给人类社会造成了巨大破坏。相应地，已有许多关于SARS疫情建模的研究报道，但由于这些模型采用的是分离的时空方法，仍存在不足之处。在本文中，我们从宏观和个体两个层面提出了新颖的综合随机时空模型，用于描述SARS疾病的传播与控制。基于一种考虑了“疑似”人群的新型SARS传播过程，我们首先从两个不同方面建立了随机时间模型：宏观模型用生死过程描述，个体马尔可夫模型用概率转移矩阵（PTM）描述。然后，我们将确定性/随机人口流动模型与随机时间模型合并，建立了综合随机时空模型。计算机模拟评估了各种现实参数和控制策略的效果，也验证了新模型的准确性和有效性。此外，还给出了对清华大学和北京市案例的具体研究。与以往的工作相比，综合随机时空模型大大降低了复杂性和误差，并且能够描述其他各种流行病，如禽流感。
