Balancing geo-privacy and spatial patterns in epidemiological studies

  • Chien-Chou Chen Center for Geographic Information Science, Research Center for Humanities and Social Sciences, Academia Sinica, Taipei, Taiwan, Province of China.
  • Jen-Hsiang Chuang Centers for Disease Control, Taipei, Taiwan, Province of China.
  • Da-Wei Wang Institute of Information Science, Academia Sinica, Taipei, Taiwan, Province of China.
  • Chien-Min Wang Center for Geographic Information Science, Research Center for Humanities and Social Sciences, Academia Sinica, Taipei; Department of Geography, National Taiwan University, Taipei, Taiwan, Province of China.
  • Bo-Cheng Lin Center for Geographic Information Science, Research Center for Humanities and Social Sciences, Academia Sinica, Taipei, Taiwan, Province of China.
  • Ta-Chien Chan | dachianpig@gmail.com Center for Geographic Information Science, Research Center for Humanities and Social Sciences, Academia Sinica, Taipei, Taiwan, Province of China.

Abstract

To balance the protection of geo-privacy and the accuracy of spatial patterns, we developed a geo-spatial tool (GeoMasker) intended to mask the residential locations of patients or cases in a geographic information system (GIS). To elucidate the effects of geo-masking parameters, we applied 2010 dengue epidemic data from Taiwan testing the tool’s performance in an empirical situation. The similarity of pre- and post-spatial patterns was measured by D statistics under a 95% confidence interval. In the empirical study, different magnitudes of anonymisation (estimated Kanonymity ≥10 and 100) were achieved and different degrees of agreement on the pre- and post-patterns were evaluated. The application is beneficial for public health workers and researchers when processing data with individuals’ spatial information.

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Published
2017-11-08
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Original Articles
Keywords:
Geo-privacy, Geo-masking, Spatial epidemiology, D statistics
Statistics
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How to Cite
Chen, C.-C., Chuang, J.-H., Wang, D.-W., Wang, C.-M., Lin, B.-C., & Chan, T.-C. (2017). Balancing geo-privacy and spatial patterns in epidemiological studies. Geospatial Health, 12(2). https://doi.org/10.4081/gh.2017.573