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Analyzing the Patterns of Space-Time Distances for Tracking the Diffusion of an Epidemic

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Space-Time Integration in Geography and GIScience

Abstract

Understanding the dynamics of how infectious diseases spread in time and space is the primary concern of epidemic control and prevention. Spatial methods of tracking the possible sources of infection have not been well developed. The objective of this study is to propose an innovative methodology that combines exploratory spatial-temporal analysis and network topological analysis to identify diffusion patterns and track possible sources of an epidemic. The methodology is composed of two stages. The first stage involves establishing case-to-case distances in space and time. Using a diagram of space-time distances, the space-time clustering of cases can be identified. In the second stage, the network topology of space-time distances is further analyzed. We use two network indicators, degree centrality and network clustering coefficient, to measure the risk of epidemic diffusion. The feasibility of our proposed methodology is assessed by a case study on a dengue epidemic in Kaohsiung, Taiwan. . Our results show that this method can be used to detect the possible origin of an epidemic and to differentiate patterns of spatial diffusion. Spatial-temporal transitions in epidemic progression from local to large-scale transmission are also determined. This study contributes a methodology on modeling spatial-temporal epidemic dynamics.

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Acknowledgements

The research was supported by the grants of National Science Council in Taiwan (NSC 98-2410-H-002-168-MY2, NSC 101-2119-M-002-020). The authors also acknowledge the financial support provided by Infectious Diseases Research and Education Center, Department of Health and National Taiwan University. The funder had no role in study design, data collection and analysis, or preparation of the manuscript.

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Authors and Affiliations

  1. Department of Geography, National Taiwan University, Room #501, Geography Building, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei, 10617, Taiwan

    Tzai-Hung Wen & Yu-Shiuan Tsai

Authors
  1. Tzai-Hung Wen
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  2. Yu-Shiuan Tsai
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Corresponding author

Correspondence to Tzai-Hung Wen .

Editor information

Editors and Affiliations

  1. Department of Geography and Geographic Information Science, University of Illinois, Urbana-Champaign, Illinois, USA

    Mei-Po Kwan

  2. Association of American Geographers, Washington, District of Columbia, USA

    Douglas Richardson

  3. Department of Geography, Hong Kong Baptist University, Hong Kong, China

    Donggen Wang

  4. Institute of Geographical Sciences and Natural Resources, Chinese Academy of Sciences, Beijing, China

    Chenghu Zhou

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Wen, TH., Tsai, YS. (2015). Analyzing the Patterns of Space-Time Distances for Tracking the Diffusion of an Epidemic. In: Kwan, MP., Richardson, D., Wang, D., Zhou, C. (eds) Space-Time Integration in Geography and GIScience. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-9205-9_15

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