PROGRESS IN GEOGRAPHY ›› 2020, Vol. 39 ›› Issue (11): 1798-1808.doi: 10.18306/dlkxjz.2020.11.002

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Clustering characteristics of COVID-19 cases and influencing factors in Chongqing Municipality

CHEN Xiao1,2(), HUANG Yujin2,3, LI Jiahui2,4, WANG Shiyang5, PEI Tao1,2,*()   

  1. 1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    2. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
    3. Key Laboratory of Regional Sustainable Development Modeling, CAS, Beijing 100101, China
    4. Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    5. School of Computer Science and Technology, University of Chinese Academy of Sciences, CAS, Beijing 100049, China
  • Received:2020-07-22 Revised:2020-09-13 Online:2020-11-28 Published:2021-01-28
  • Contact: PEI Tao;
  • Supported by:
    National Natural Science Foundation of China(42041001);National Natural Science Foundation of China(41525004);National Natural Science Foundation of China(41421001)


Clustering characteristics of COVID-19 cases within cities and influencing factors are of significant referential value for epidemic prevention and control. In this study, we conducted spatial clustering analysis, factor analysis, and regression analysis on 458 COVID-19 confirmed cases from 21 January to 24 February 2020, and we used mobile phone signaling data, and environmental data to analyze the spatiotemporal variability of epidemic characteristics in Chongqing Municipality at the residential community scale and the influencing factors. The results show that: 1) Temporally, the number of confirmed cases showed a rapid increasing trend in the beginning, and most of the cases were imported cases. In the late stage, the increase rate lowered, and the main trend turned into local transmission (including inter-community, intra-community, and intra-family transmissions), among which intra-family transmissions made up the largest portion (23%). 2) Spatially, the cases showed significant clustering characteristics, and aggregation level increased with time. The hot spots of all cases were distributed in the west and northeast Chongqing. The hot spots of local cases were mainly concentrated in the northwestern and southwestern regions where population density and economic development level were higher, while the hot spots of imported cases were mainly concentrated in the central and northeastern regions adjacent to Hubei Province. 3) The regression results between the density of all cases, local cases, imported cases and four factors obtained by factor analysis (urban traffic factor, intra-community activity factor, service provision factor, and residents' distribution factor) provide some insights. Transportation facility level was closely related to the density of confirmed cases. Service places such as stores, supermarkets, and restaurants significantly contributed to the spread of the virus. Inter-community transmission was an important factor in local clustering of cases, while imported cases mostly occurred in densely populated areas. Hence, targeted measures should be adopted for future epidemic prevention and control according to various epidemic transmission patterns in different regions, such as paying attention to imported cases in the central and northeastern parts of Chongqing, and focusing on avoidance of local transmission in northwest and southwest. Moreover, measures should be strengthened in the areas with dense urban traffic and resident population to effectively prevent the outbreak from rebounding.

Key words: COVID-19, clustering characteristics, residential community scale, Chongqing Municipality