Objective Differential privacy is a relatively new method for data privacy that has seen
growing use due its strong protections that rely on added noise. This study assesses the …

In this article, we chronicle the US Census Bureau's development of the Disclosure
Avoidance System (DAS) for the publicly released products of the 2020 Census of …

The US Census Bureau will implement a modernized privacy-preserving disclosure
avoidance system (DAS), which includes application of differential privacy, on publicly …

Background Scant research has analyzed contemporary US cancer incidence rates in
relation to historical redlining (ie, 1930s US federally imposed residential segregation) …

Objective To investigate how county and state‐level estimates of Medicaid enrollment
among the total, non‐Hispanic White, non‐Hispanic Black or African American, and …

Abstract Across the United States public health community in 2020, in the midst of a
pandemic and increased concern regarding racial/ethnic health disparities, there is …

The age distribution of a population is important for understanding the demand and
provision of labor and services, and as a denominator for calculating key age-specific rates …

Census data are vital to health care research but must also protect respondents'
confidentiality. The 2020 decennial Census employs a new Differential Privacy framework; …

For the application of mapping area health outcome rates, georeferenced data are made up
of three components: health outcome counts, population estimates, and the geographic …

Background: There is a need for rigorous and standardized methods of privacy protection for
shared data in the health sciences. Differential privacy is one such method that has gained …