Original Articles
8 November 2017
Vol. 12 No. 2 (2017)
https://doi.org/10.4081/gh.2017.573

Balancing geo-privacy and spatial patterns in epidemiological studies

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Geo-privacy, Geo-masking, Spatial epidemiology, D statistics
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Authors

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.
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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Supporting Agencies

National Science Council, R.O.C. (NSC-102-2314-B-001-001)

How to Cite



Balancing geo-privacy and spatial patterns in epidemiological studies. (2017). Geospatial Health, 12(2). https://doi.org/10.4081/gh.2017.573

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