Researchers evaluate 2020 Census data privacy changes

Date:
June 3, 2020
Source:
Penn State
Summary:
After the US Census Bureau announced that it was changing how
it protects the identities of individuals for the 2020 Census,
researchers began to evaluate how these changes may affect census
data integrity.



FULL STORY ========================================================================== After the U.S. Census Bureau announced that it was changing how it
protects the identities of individuals for the 2020 Census, a Penn
State-led research team began to evaluate how these changes may affect
census data integrity.


==========================================================================
The Census Bureau is proposing to use differential privacy, a new method
that attempts to protect the identities of individuals when publishing
public data.

Census data is used to distribute federal funding that impacts communities
and also determines congressional representation.

Alexis Santos, assistant professor of human development and family
studies at Penn State, along with researchers Jeffrey Howard, assistant professor at the University of Texas at San Antonio, and Ashton Verdery, assistant professor of sociology, demography, and social data analytics
at Penn State, examined mortality rates in 2010. The researchers compared
both methods of privacy protection and the implication of this change
to better understand health disparities in the United States. The work
was published recently in Proceedings of the National Academy of Sciences.

The research team discovered that when differential privacy method was
used on Census data, it produced dramatic changes in population counts
for racial and ethnic minorities compared to the traditional methods.

"We focused on mortality rate estimates because they are an essential population-level metric for which data are collected and disseminated at
the national level and because mortality rates are a critical indicator
of population health," said Santos.

The research team then explored the changes in mortality rates resulting
from the two disclosure avoidance systems by metropolitan classifications.

"We discovered that by using differential privacy, there were both
instances of under- and over-counting of the population. In rural areas,
there was undercounting of racial and ethnic minorities, while in urban
areas there was an overcounting of these populations," Santos said.

The researchers found that some discrepancies between the two methods
of data analysis exceeded a 10% difference.

"This is very concerning because it could impact how much funding
programs receive for a specific geographic area," said Santos. "These discrepancies could result in understated health risks in some areas,
and while overstating in others where there isn't a great need."
According to Santos, the findings highlight the consequences of
implementing differential privacy and demonstrate the challenges in
using the data products derived from this method.

"The Census Bureau has been very receptive to our research,
and demonstrated concern about the accuracy of the data," Santos
said. "We plan to move forward with additional research to determine
how differential privacy may affect population growth estimates and
populations changes from census year to census year. We still have time to
fine tune the differential privacy algorithm, and our research will help pinpoint areas of improvement." Santos, who is also a cofunded faculty
member of the Social Science Research Institute, and the research team
were supported by the Population Research Institute and the Administrative
Data Accelerator at Penn State. The work also is supported by the Center
for Community Based and Applied Health Research at the University of
Texas at San Antonio.


========================================================================== Story Source: Materials provided by Penn_State. Original written by
Kristie Auman-Bauer and Melissa Krug. Note: Content may be edited for
style and length.


========================================================================== Journal Reference:
1. Alexis R. Santos-Lozada, Jeffrey T. Howard, Ashton M. Verdery. How
differential privacy will affect our understanding of health
disparities in the United States. Proceedings of the National
Academy of Sciences, 2020; 202003714 DOI: 10.1073/pnas.2003714117 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2020/06/200603194440.htm https://www.sciencedaily.com/releases/2020/06/200603194440.htm

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