摘要
2003年SARS是高传染性的公众健康危机，我国铁路旅客运输出现严重“滑坡”并蒙受巨大损失。本文依据本底趋势线理论，对此次危机造成铁路客运量损失、危机生命周期及全国28个省市区差异进行了定量分析与估算。结果显示：①2003年SARS共造成铁路客运量损失1．043亿人，占全国客运量总损失的10．22％，相对损失率为9．69％；②2003年3～4月危机开始生成显现，5～6月全面爆发并达到鼎盛，7～10月为衰减恢复期，SARS危机对铁路客运的影响持续8个月；③SARS危机对全国各省份铁路客运量所造成的损失差异较大，其中，北京、辽宁、广东、四川、黑龙江、河北的客运量损失在686万～867万人，江苏、河南、浙江、陕西、吉林、上海、山西的客运量损失在417万～607万人；④剔除青海和广东两省，26个省份铁路客运量损失与客运量基数、sARs确诊人数具有显著的相关性，其中，SARS确诊人数的边际系数为11．4％。
SARS in 2003 is a public health crisis with high infectiousness. The railway passenger traffic volumes in China went steadily downhill and suffered a heavy loss. Based on the theory of the background trend line, the loss of railway passenger traffic volumes, the lifecycle of the SARS crisis and the distribution of passenger traffic volume losses in 28 provinces are estimated. The results are as following： （1） There occurred a loss of 104.3 million railway passengers in 2003, the relative loss ratio being 9.69% and its proportion of the total loss of passengers in China amounting to 10.22%; （2） the crisis appeared from March to April, broke out on an all - round scale and up to the apex from May to June, and attenuated from July to October, lasting for 8 months to affect railway transportation; （3） the railway passenger traffic volume losses in 28 provinces differed greatly from one another, the losses for Beijing, Liaoning, Guangdong, Sichuan, Heilongjiang and Hebei falling into the range of 6.86 - 8.67 million persons whereas the losses for Jiangsu, Henan, Zhejiang, Shaanxi, jilin, Shanghai and Shanxi into the range of 4.17-6.07 million persons; （4） excluding the Qinghai and Guangdong Provinces, the marked exponential relation was demonstrated between the railway passenger traffic volume losses and the cardinal numbers of railway passenger traffic volumes and numbers of diagnosed SARS patients in the other 26 provinces, the boundary coefficient of diagnosed SARS patients being 11.4%.
出处
《铁道学报》
EI
CAS
CSCD
北大核心
2006年第6期28-34,共7页
Journal of the China Railway Society
基金
国家社会科学基金资助项目(03BJY0088)
关键词
SARS危机
本底趋势线
客运量损失
地域分布
空间模型
SARS crisis
background trend line
loss of passenger traffic volume
terrain distribution
spatial model
