SARS与COVID-19时空传播差异性及影响因素分析

doi:10.12082/dqxxkx.2021.210133

地球信息科学学报 ›› 2021, Vol. 23 ›› Issue (11): 1910-1923.doi: 10.12082/dqxxkx.2021.210133

• 专栏：全球新型冠状病毒肺炎(COVID-19)疫情时空建模与决策分析 • 上一篇下一篇

SARS与COVID-19时空传播差异性及影响因素分析

崔明洁¹^,²(), 姚霞²^,⁴, 方昊然²^,⁵, 张杨成思²^,⁶, 杨德刚¹^,², 裴韬²^,³^,^*()

1. 中国科学院新疆生态与地理研究所,乌鲁木齐 830011
2. 中国科学院大学,北京 100049
3. 中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室,北京 100101
4. 中国科学院城市环境研究所城市环境与健康重点实验室,厦门 361021
5. 中国科学院空天信息创新研究院,北京 100094
6. 中国环境科学研究院,北京 100012

收稿日期:2021-03-16 修回日期:2021-05-25 出版日期:2021-11-25 发布日期:2022-01-25
通讯作者: *裴韬（1972— ）,男,江苏扬州人,研究员,研究方向为地理大数据挖掘、地统计分析。E-mail: peit@lreis.ac.cn
*裴韬（1972— ）,男,江苏扬州人,研究员,研究方向为地理大数据挖掘、地统计分析。E-mail: peit@lreis.ac.cn
作者简介:崔明洁（1997— ）,女,河南商丘人,硕士生,研究方向为区域发展。E-mail: cuimingjie19@mails.ucas.ac.cn
基金资助:
国家重点研发计划项目(2017YFB0503604);国家自然科学基金项目(41525004);国家自然科学基金项目(42041001)

Spatial and Temporal Transmission Differences between SARS and COVID-19 and Analysis of Influence Factors

CUI Mingjie¹^,²(), YAO Xia²^,⁴, FANG Haoran²^,⁵, ZHANG Yangchengsi²^,⁶, YANG Degang¹^,², PEI Tao²^,³^,^*()

1. Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
2. University of Chinese Academy of Sciences, Beijing 100049, China
3. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
4. Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
5. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
6. Chinese Research Academy of Environment Sciences, Beijing 100012, China

Received:2021-03-16 Revised:2021-05-25 Online:2021-11-25 Published:2022-01-25
Supported by:
National Key R&D Program of China, No(2017YFB0503604);National Natural Science Foundation of China, No(41525004);National Natural Science Foundation of China, No(42041001)

摘要/Abstract

摘要：

SARS和COVID-19的暴发对我国公众健康、社会经济等造成了严重影响,为揭示呼吸道烈性传染病的时空传播的共性规律和差异特征及背后原因,运用时空统计方法,系统分析并对比了SARS与COVID-19的时空传播差异性特征,并结合病毒本身传播特性及交通、温度等因子进行原因分析。研究表明：① 时间序列上,SARS从发病初始到结束经历了2个阶段,即上升期-平缓期,COVID-19经历了3个阶段,即上升期-急剧上升期-缓升期。② 空间传播模式上,COVID-19传播强度及传播范围大于SARS,且COVID-19的整体连通性较大,各省份与病毒暴发地的联系更为紧密;SARS和COVID-19的传播都存在明显的空间聚集性特征;二者均以邻近传播、远距离飞跃式为主,且SARS存在中次级传播中心,COVID-19扩散中心未发生转移。③ 空间传播方向上,SARS以北京市、香港特别行政区、广东省为中心,空间传播方向性更强,COVID-19仅以湖北省为中心向外扩散。④ 空间传播速度上,SARS各省份首例病例传播时间跨度较大,COVID-19各个省份首例病例传播时间大致以胡焕庸线为分界线,呈现出“东快西慢”的现象,传播时间跨度较短。⑤ R0是造成SARS和COVID-19空间传播范围与空间传播速度差异的主要原因;SARS和COVID-19病毒温度适宜性有所差异,但在温度接近的区域均发生了空间聚集性传播和邻近区域传播;除病毒本身传播能力、温度影响外,交通是影响SARS和COVID-19空间远距离飞跃式传播的主要原因,二者空间传播速度均与路网密度呈负相关关系。

关键词: SARS, COVID-19, 时空统计方法, 时空传播差异, 时间序列, 空间传播模式, 空间传播方向, 空间传播速度

Abstract:

The outbreaks of SARS and COVID-19 have had a serious impact on public health, social economy and so on in China, in order to reveal the common law and difference characteristics of space-time transmission of respiratory infectious diseases and the reasons behind them, using space-time statistical methods, systematically analyzed and compared the difference characteristics of space-time transmission between SARS and COVID-19, and combined with the transmission characteristics of the virus itself and temperature, traffic and other factors to analyze the causes. The study shows that, ① SARS experiences two stages, the rising period-flat phase, and the COVID-19 experiences three stages, the rising period-sharp rise-slow up period. ② In the mode of spatial transmission, the transmission intensity and range of COVID-19 is greater than that of SARS, and the overall connectivity of COVID-19 is greater and the provinces are more closely related to the outbreak of the virus. Both SARS and COVID-19 transmission have obvious spatial aggregation characteristics. They are based on proximity propagation and long-range leaps, and SARS has a secondary communication center, and COVID-19 diffusion center has not been relocated. ③ In the direction of space communication, SARS is centered in Beijing, Hong Kong and Guangdong, the direction of spatial communication is stronger, and COVID-19 is only spread outwards with Hubei as the center. ④ In terms of spatial transmission speed, the spread time of the first case in each province of SARS is relatively large, and the spread time of the first case in each province of COVID-19 is roughly divided by Hu Huanyong Line, showing a phenomenon of "fast in the east and slow in the west", and the spread time span is relatively short. ⑤ R0 is the main reason for the difference between the spatial transmission range of SARS and COVID-19 and the speed of spatial transmission. The temperature suitability of SARS and COVID-19 viruses is different, but spatial aggregation transmission and adjacent area transmission are occurring in areas with similar temperatures. Besides the virus transmission capacity and temperature impact, traffic is the main reason affecting SARS and COVID-19 space long-range leap transmission, and the spatial transmission speed of both is negatively related to the density of the road network.

Key words: SARS, COVID-19, space-time statistical method, space-time propagation differences, time series, spatial propagation model, spatial propagation direction, spatial propagation space

崔明洁, 姚霞, 方昊然, 张杨成思, 杨德刚, 裴韬. SARS与COVID-19时空传播差异性及影响因素分析[J]. 地球信息科学学报, 2021, 23(11): 1910-1923.DOI:10.12082/dqxxkx.2021.210133

CUI Mingjie, YAO Xia, FANG Haoran, ZHANG Yangchengsi, YANG Degang, PEI Tao. Spatial and Temporal Transmission Differences between SARS and COVID-19 and Analysis of Influence Factors[J]. Journal of Geo-information Science, 2021, 23(11): 1910-1923.DOI:10.12082/dqxxkx.2021.210133

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	Moran's I	p-value	z-value	E	V
SARS	0.2122	0.0167	2.3934	-0.0303	0.0103
COVID-19	0.2141	0.0330	2.1311	-0.0303	0.0131

	时间序列特征		空间传播特征
	累计确诊病例数	新增病例增长率	空间传播模式			空间传播方向	空间传播速度
	累计确诊病例数	新增病例增长率	传播中心	传播范围	各省份首例病例传播	空间传播方向	空间传播速度
SARS	上升期-平稳期	1月最高	广东—香港—北京	除新疆等7个地区,整体连通性较低	航空网占主导	有次级传播中心形成,方向显著	历时165 d
COVID-19	上升期-急剧上升期-缓升期	3月最高	湖北	全国,整体连通性较高	高铁网占主导	无次级传播中心,方向不显著	历时52 d

年份	客运量总计 /亿人	铁路客运量 /亿人		民航客运量 /亿人	铁路里程数 /万km		铁路路网密度 /(km/km²）	航线里程 /万km
年份	客运量总计 /亿人	普铁	高铁	民航客运量 /亿人	普铁	高铁	铁路路网密度 /(km/km²）	航线里程 /万km
2003	158.75	9.73	-	0.88	0.88	-	0.0076	174.95
2019	176.04	13.02	23.58	6.12	2.58	3.54	0.0145	948.22

	Ρ	单尾检验的显著水平	显著性程度
SARS	-0.48	0.05	中等程度负相关
COVID-19	-0.31	0.05	中等程度负相关

COVID-19疫情流行区	月均温/℃		SARS疫情流行区	月均温/℃
湖北武汉	4（1月）	8（2月）	广东广州	14.3（2月）
河南信阳	4（1月）	8（2月）	北京	13.6（4月）
湖南长沙	3（1月）	10（2月）	山西太原	11.7（4月）
安徽合肥	3（1月）	8（2月）	香港	15.9（2月）

SARS与COVID-19时空传播差异性及影响因素分析

Spatial and Temporal Transmission Differences between SARS and COVID-19 and Analysis of Influence Factors

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