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Methods Inf Med 2012; 51(01): 63-73
DOI: 10.3414/ME11-01-0001
Original Articles
Schattauer GmbH

Multidimensional Point Transform for Public Health Practice

P. AbdelMalik
1   Faculty of Health and Education, University of Plymouth, Plymouth, UK
,
M. N. Kamel Boulos
1   Faculty of Health and Education, University of Plymouth, Plymouth, UK
› Author Affiliations
Further Information

Publication History

received:11 January 2011

accepted:10 May 2011

Publication Date:
20 January 2018 (online)

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Summary

Background: With increases in spatial information and enabling technologies, location-privacy concerns have been on the rise. A commonly proposed solution in public health involves random perturbation, however consideration for individual dimensions (at-tributes) has been weak.

Objectives: The current study proposes a multidimensional point transform (MPT) that integrates the spatial dimension with other dimensions of interest to comprehensively anonymise data.

Methods: The MPT relies on the availability of a base population, a subset patient dataset, and shared dimensions of interest. Perturbation distance and anonymity thresholds are defined, as are allowable dimensional perturbations. A preliminary implementation is presented using sex, age and location as the three dimensions of interest, with a maximum perturbation distance of 1 kilometre and an anonymity threshold of 20%. A synthesised New York county population is used for testing with 1000 iterations for each of 25, 50, 100, 200 and 400 patient dataset sizes.

Results: The MPT consistently yielded a mean perturbation distance of 46 metres with no sex or age perturbation required. Displacement of the spatial mean decreased with patient dataset size and averaged 5.6 metres overall.

Conclusions: The MPT presents a flexible, customisable and adaptive algorithm for perturbing datasets for public health, allowing tweaking and optimisation of the trade-offs for different datasets and purposes. It is not, however, a substitute for secure and ethical conduct, and a public health framework for the appropriate disclosure, use and dissemination of data containing personal identifiable information is required. The MPT presents an important component of such a framework.

Keywords

Public health - geographic location - privacy - spatial transform - anonymisation