Acta Geographica Sinica ›› 2016, Vol. 71 ›› Issue (9): 1653-1662.doi: 10.11821/dlxb201609015

• Orginal Article • Previous Articles     Next Articles

Mixing spatial-temporal transmission patterns of metropolis dengue fever: A case study of Guangzhou, China

Haiyan TAO1,2(), Zhongzhe PAN3, Maolin PAN4, Li ZHUO1(), Yong XU5, Miao LU1   

  1. 1. Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation / Center of Integrated Geographic Information Analysis, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China
    2. Key Laboratory of Tropical Disease Control (Sun Yat-sen University), Ministry of Education, Guangzhou 510080, China
    3. Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
    4. School of Data and Computer Science, Sun Yat-Sen University, Guangzhou 510006, China
    5. Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
  • Received:2016-02-17 Revised:2016-06-10 Online:2016-11-25 Published:2016-11-25
  • Supported by:
    National Natural Science Foundation of China, No.41371499


This paper proposes a new method to model the spatial and temporal transmission network for infectious disease. Specifically, 679 cases from the early 11 weeks of the dengue fever outbreak in Guangzhou in 2014 are used to analyze the disease transmission characteristics. Three methods are adopted for the analysis. (1) We use extended Knox test to derive the main time and space interaction sectors at a distance of 1 km in two weeks and that of 5-7 km in one week. (2) We pair the cases from different areas to construct the space-time affinity transmission (STAT) network and the human daily movement transmission (HDMT) network. (3) We compare the assortativity, spatial characteristics, and the central network location between STAT and HDMT network by using complex network theories. The result shows that the percentages of overall cases included in the STAT and HDMT networks are 92.93% and 97.05%, respectively. This means that both STAT and HDMT network models imply the overall transmission of the dengue fever outbreak. STAT network is assortative, and presents the cross infection in neighboring areas. On the contrary, HDMT network is disassortative, and it displays the diffusion infection character of the dengue fever outbreak. We earmark the location of outbreak center as well as the diffusion center with the degree of closeness centrality in STAT network and the degree of betweenness centrality in HDMT network. This shows that the outbreak center approximately overlaps the spatial kernel density center of all cases, while the diffusion centers are located along the urban rapid transit routes.

Key words: extended Knox test, spatial-temporal transmission network, mixing pattern, dengue fever, Guangzhou