A spatial point pattern analysis of the 2003 SARS Epidemic in Beijing

Zhidong Cao, Pengfei Zhao, Jiayue Liu, Wei Zhong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Beijing1 was the most prevalent city of SARS in China in 2003. The study on the spatial distribution and clustering characteristics is helpful to deeply understand the epidemic of SARS in Beijing. In this paper, the home addresses of SARS patients accquired by investigation were considered as the spatial location, deriving 2321 cases of the spatial distribution and incidence rate of infected patients. Kernel estimation method is used to obtain the density distribution of SARS patients. The results indicate that the distribution density of infected people is gradually attenuated from the center of the city to the suburbs. Ripley'K function is also used to explore the spatial clustering characteristics of SARS infection. In addition, the influence of gender, contact history and SARS Beijing Xiaotangshan Hospital towards the spatial clustering of patients are analyzed and thus shows that the spatial clustering of patients is the strongest at 11km distance. Gender and history of exposure to SARS infection in the spatial clustering are of a small impact, while SARS Beijing Xiaotangshan Hospital on SARS infection in the spatial clustering are of a strong impact. The clustering characteristics are significantly weaker after the establishment of the hospital that shows the importance of the establishment of the hospital on prevent and control of SARS epidemic in Beijing.

Original languageEnglish
Title of host publicationProceedings of the 3rd ACM SIGSPATIAL International Workshop on the Use of GIS in Emergency Management, EM-GIS 2017
Place of PublicationNew York, U. S. A.
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450354936
DOIs
Publication statusPublished - 7 Nov 2017
Event3rd ACM SIGSPATIAL International Workshop on the Use of GIS in Emergency Management, EM-GIS 2017 - Redondo Beach, USA United States
Duration: 7 Nov 20177 Nov 2017

Conference

Conference3rd ACM SIGSPATIAL International Workshop on the Use of GIS in Emergency Management, EM-GIS 2017
CountryUSA United States
CityRedondo Beach
Period7/11/177/11/17

Keywords

  • Beijing
  • Kernel estimation
  • Point pattern analysis
  • Ripley'K function
  • SARS

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Geography, Planning and Development
  • Information Systems
  • Information Systems and Management

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  • Cite this

    Cao, Z., Zhao, P., Liu, J., & Zhong, W. (2017). A spatial point pattern analysis of the 2003 SARS Epidemic in Beijing. In Proceedings of the 3rd ACM SIGSPATIAL International Workshop on the Use of GIS in Emergency Management, EM-GIS 2017 [A1] Association for Computing Machinery. https://doi.org/10.1145/3152465.3152466