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非典给亚洲许多国家, 尤其中国, 带来了巨大损失. 有关其暴发流行规律尚不完全清楚. 拟通过根据政府发布的SARS病例信息, 寻找能揭示其暴发流行规律的数学模型, 并分析地区间差异. 鉴于非典病例数随着防治措施的加强应逐渐减少, 我们假设病人累积数可能符合种群动态研究中著名的逻辑斯蒂模型(Logistic model), 即病例数增长率应与病人累积数呈线性负相关. 研究结果表明, 中国大陆(包括北京、河北、天津、山西、内蒙古)、香港以及新加坡的非典病例数增长率与病人累积数呈显著线性负相关. 各地基本传染指数(R0)为2~5.6. 河北、天津的R0显著高于山西、内蒙古、北京、香港、新加坡. 亚洲地区非典暴发流行规律可用逻辑斯蒂模型描述. 非典病例数与病人累积数呈显著线性负相关的主要因素是政府有利的防控措施. 使用该模型, 基本传染指数(R0)和最大病例数可以较好地提前估计.
SARS has caused huge losses to many Asian countries, especially China, and the epidemic rules of its outbreak are not yet fully understood. According to the SARS case information released by the government, it is proposed to find a mathematical model that can reveal the epidemic regularity of outbreak and analyze the inter-regional In view of the fact that the number of SARS cases should gradually decrease as the prevention and control measures increase, we assume that the cumulative number of patients may be in line with the well-known Logistic model in population dynamics research, ie the growth rate of cases should be linear with the cumulative number of patients Negative correlation.The results showed that there was a significant linear negative correlation between the growth rate of SARS cases in mainland China (including Beijing, Hebei, Tianjin, Shanxi, Inner Mongolia), Hong Kong and Singapore and the cumulative number of patients.The basic infection index (R0) ~ 5.6. R0 in Hebei and Tianjin was significantly higher than that in Shanxi, Inner Mongolia, Beijing, Hong Kong and Singapore. The epidemic rule of SARS in Asia could be described by Logistic model. The main factor of significant linear negative correlation between the number of SARS patients and the cumulative number of patients was The government’s favorable prevention and control measures, using the model, the basic infection index (R0) and the largest case Can better advance estimate.