How a lack of data led to vaccine inequity
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How a lack of data led to vaccine inequity

Date
June 10, 2021 | Updated on October 22, 2021
Authors
Netanya Quino

The public health data infrastructure failed our most vulnerable communities this past year, missing many areas most affected by COVID-19. Vaccination rates in these communities are lower than the national average—partly due to inefficiencies in data systems and vaccine distribution. One reason for this was that early in the pandemic, the public health data infrastructure was missing elements. And lacking centralized guidance on data quality and communications from the federal government, state and local authorities couldn’t get accurate information about disease prevalence and spread nor recommend equitable interventions.

For instance, state and local authorities testing for COVID-19 weren’t consistently collecting demographic information. That led to incomplete demographic data on contact tracing and the virus’ spread. It was difficult to tell which communities had the highest rates of COVID-19 and needed to be prioritized for vaccination. Similar health equity issues cropped up for vaccine distribution. As of May 2021, the race and ethnicity was recorded for only about 55% of the people who got at least one vaccine.

With real-time surveillance of COVID-19 prevalence, severity and vaccination rates, community public health systems might have responded appropriately and distributed vaccines proportionately.

A network of state and federal data systems that support public health initiatives would enable officials to track disease spread, vaccination rates and other health information in different communities—and also monitor the effectiveness of interventions. Technology is needed for collecting, managing and sharing public health data effectively. But so are other efforts.

For example, federal agencies could improve how they compile data from local and state sources, to more accurately track the spread and prevalence of disease and vaccination rates. And governance and regulatory structures are needed for ethical use of data. Combined, these components make up public health data infrastructure.

Building partnerships to improve vaccine distribution

Federal agencies handling COVID-19 issues could learn from other state-federal data partnerships. In the past year, federal agencies have made critical strides in developing strong public health data infrastructure for the COVID-19 pandemic. With new federal guidance, some states have used public health data to implement more equitable vaccine distribution.

The CDC’s National Environmental Public Health Tracking Program is considered a leading example of effective collaboration on state and federal public health data. To establish an environmental health surveillance system, the program broke down data silos, developed standardized data definitions for states and delivered clear guidance on best surveillance practices. And a dynamic, easy-to-use, online platform enabling states to easily analyze data and identify interventions was also developed.

Based on HHS research, the Alaska COVID-19 Vaccine Task Force used an “area deprivation index” to identify communities needing vaccines. After analyzing the data, the task force and community-based organizations distributed vaccines in the underserved communities. If the CDC clearly laid out guidance for using tools like this one, it could help states create equitable policies and reduce health disparities.

The Partnership for Public Service is looking more closely at how federal agencies have been navigating data infrastructure challenges to quickly  adapt and respond to the public health crisis at hand. With a lens on health equity, this work will highlight use cases and cross-sector leaders in public health surveillance to identify best practices around advanced technologies, partnerships (particularly between federal agencies and state governments), data governance and more. The findings will include recommendations to help the federal government advance public health data infrastructure through ongoing government-wide reform.

Read our complete findings in the report, “Retracing steps: Reflecting on management lessons in public health data infrastructure during COVID-19.”

This post is co-authored by Netanya Quino, a former intern on the Partnership’s Research and Evaluation team. 


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