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Abstract:
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We discuss how statistical methods from the field of disease mapping can be used in the area of data privacy with an application to county-level stroke death counts from 1973-2013 across multiple age groups, data which are plagued with low counts. Our primary goal is to identify and summarize spatiotemporal trends in stroke mortality across these age groups. This will require flexible models which account for not only spatiotemporal associations, but also the correlation between age groups to achieve reliable rate estimates. Our second objective pertains to the release of public-use data and data privacy, where NCHS guidelines suggest that death counts less than 10 should be suppressed to protect the confidentiality of data-subjects. For these data, however, this criterion results in nearly 70% of the over 380,000 data points being suppressed. As high suppression rates can significantly reduce the utility of the publicly available data, the secondary goal of this work is to generate so-called "synthetic data" that preserve the complex dependence structure of the original data while avoiding the disclosure risks associated with releasing unsuppressed confidential data.
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