Full Citation

Title: Differential Privacy in the 2020 Census Will Distort COVID-19 Rates

Citation Type: Journal Article

Publication Year: 2021

ISBN:

ISSN:

DOI: 10.1177/2378023121994014

NSFID:

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PMID:

Abstract: Scholars rely on accurate population and mortality data to inform efforts regarding the coronavirus disease 2019 (COVID-19) pandemic, with age-specific mortality rates of high importance because of the concentration of COVID-19 deaths at older ages. Population counts, the principal denominators for calculating age-specific mortality rates, will be subject to noise infusion in the United States with the 2020 census through a disclosure avoidance system based on differential privacy. Using empirical COVID-19 mortality curves, the authors show that differential privacy will introduce substantial distortion in COVID-19 mortality rates, sometimes causing mortality rates to exceed 100 percent, hindering our ability to understand the pandemic. This distortion is particularly large for population groupings with fewer than 1,000 persons: 40 percent of all county-level age-sex groupings and 60 percent of race groupings. The U.S. Census Bureau should consider a larger privacy budget, and data users should consider pooling data to minimize differential privacy’s distortion.

Url: https://journals.sagepub.com/doi/full/10.1177/2378023121994014

User Submitted?: No

Authors: Hauer, Mathew E.; Santos-Lozada, Alexis R.

Periodical (Full): Socius: Sociological Research for a Dynamic World

Issue:

Volume: 7

Pages: 1-6

Data Collections: IPUMS NHGIS

Topics: Health, Methodology and Data Collection

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