系统管理学报

系统管理学报 ›› 2024, Vol. 33 ›› Issue (6): 1508-1520.DOI: 10.3969/j.issn.2097-4558.2024.06.010

• 大数据与信息管理 • 上一篇    下一篇

城市社区尺度下COVID-19时空扩散特征与影响因素——以上海疫情为例

李周平1，葛如一1，郭晓爽2   

  1. 1.上海商学院商务信息学院，上海 200235；2.上海理工大学中英国际学院，上海 200093
  • 收稿日期:2022-09-08 修回日期:2023-03-15 出版日期:2024-11-28 发布日期:2024-12-03
  • 基金资助:

    国家社会科学基金支持项目（18ZDA088）；上海市“科技创新行动计划”软科学研究项目（23692106100，22692198700）

Spatiotemporal Spreading Characteristics and Influence Factors of COVID-19 in Urban Community Level: Evidence from Shanghai

LI Zhouping1, GE Ruyi1, GUO Xiaoshuang2   

  1. 1.Faculty of Business Information, Shanghai Business School, Shanghai 200235, China; 2.Sino-British College, University of Shanghai for Science and Technology, Shanghai 200093, China
  • Received:2022-09-08 Revised:2023-03-15 Online:2024-11-28 Published:2024-12-03

PDF

摘要：

针对新型突发传染病疫情在大型城市传播过程中的区域防控问题，提出了一种能够有效识别局部传播源、划分扩散边界的时空事件聚类模型。以2022年3月上海市新冠疫情为例，研究结果表明：在0.8、1.5和2.5 km这3个尺度上制定区域防控策略能有效控制疫情的近邻扩散与迁移扩散；而热点区域内公交站数量、购物点数量和是否存在三甲医院3个空间风险因子可作为区域防控决策的辅助因素，地铁站数量、有无大型商业中心和有无大型超市3个空间风险因子可辅助预判疫情的迁移扩散路径。

关键词:

疫情防控, 密度峰值聚类, 城市社区, 时空扩散

Abstract:

For the problem of regional prevention and control of infectious diseases in large cities, this paper proposes a novel spatiotemporal clustering model which can effectively identify local diffusion sources and divide diffusion boundaries. Taking the COVID-19 in Shanghai in March 2022 as an example, it is shown that developing regional prevention and control strategies at the scale of 0.8km, 1.5km, and 2.5km can effectively control the adjacent diffusion and relocation diffusion of the pandemic. The spatial risk factors of bus stop, shopping spot, and large-scale hospital can assist the formulation of regional prevention and control strategies. The spatial risk factors of metro station, shopping mall, and supermarket can help predict the migration path of the pandemic.

Key words:

pandemic prevention and control, density peak clustering, urban community, spatiotemporal diffusion

中图分类号: