Balancing geo-privacy and spatial patterns in epidemiological studies

Submitted: 6 April 2017
Accepted: 10 August 2017
Published: 8 November 2017
Abstract Views: 3460
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Authors

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

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