Balancing Data Provision and Data Protection: A Natural Experiment With HIV and Syphilis Surveillance Data in the United States.

ABSTRACT

BACKGROUND: Public release of health data typically requires statistical disclosure limitation (SDL), but scant research demonstrates how real-world SDL affects data usability. Recent changes of federal data re-release policy allow a pseudo-counterfactual comparison of HIV and syphilis data suppression rules. METHODS: Incident counts (2019) of HIV and syphilis infections by county for Black and White populations were downloaded from the US Centers for Disease Control and Prevention. We quantified and compared suppression status by disease and county between Black and White populations and calculated incident rate ratios for counties with statistically reliable counts. RESULTS: Approximately 50% of US counties have incident HIV counts suppressed for Black and White populations compared with only 5% for syphilis, which has an alternative suppression strategy. The county population sizes protected by a numerator disclosure rule (<4) spans several orders of magnitude. Calculations of incident rate ratios, used as a measure of health disparity, were impossible in the 220 counties most susceptible to an HIV outbreak. CONCLUSIONS: Balancing tradeoffs between providing and protecting data are key to health initiatives worldwide. We encourage an increase in empirical research on the impact of SDL, especially in the context of health disparities, and recommend new approaches to avoid the "oppression of data suppression."