Shi Yaolin
Computational Geodynamics Laboratory of Graduate School of Chinese Academy of Sciences, 100039 Beijing, China.
Chin Sci Bull. 2003;48(13):1287-1292. doi: 10.1007/BF03184164.
Based upon the simulation of the stochastic process of infection, onset and spreading of each SARS patient, a system dynamic model of SRAS spreading is constructed. Data from Vietnam is taken as an example for Monte Carlo test. The preliminary results indicate that the time-dependent infection rate is the most inportant control factor for SARS spreading. The model can be applied to prediction of the course with fluctuations of the epidemics, if the previous history of the epidemics and the future infection rate under control measures are known.
基于对每位SARS患者感染、发病和传播随机过程的模拟，构建了SARS传播的系统动力学模型。以越南的数据为例进行蒙特卡罗检验。初步结果表明，随时间变化的感染率是SARS传播最重要的控制因素。如果已知疫情的既往历史以及控制措施下未来的感染率，该模型可用于预测疫情波动的过程。
