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COVID-19 Vaccine Update for Homeless Service Providers – Equity Series

COVID-19 has deeply impacted already marginalized communities within the United States in both unprecedented and historically familiar ways. The disproportionate impacts of the pandemic on Black, Indigenous, and People of Color (BIPOC) communities, undocumented immigrants, Asian American and Pacific Islander (AAPI) communities, and LGBTQ+ communities are symptoms of inequities that are embedded in our systems and institutions. This is a critical moment for our nation.

Efforts to increase vaccination rates are growing more urgent as the dangerous Delta variant spreads quickly through communities. To decrease community transmission, all communities must have equitable and easy access to COVID-19 vaccines. Access to the vaccine requires addressing the mistrust that marginalized populations can have in the health care system so that they feel confident in trusting the vaccine and the people administering it.

Each section of the Vaccine Equity Series focuses on the unique ways in which the histories and lived experiences of each specific group can be barriers to vaccine access. The four sections are:

  1. BIPOC Communities
  2. AAPI Communities
  3. Undocumented Immigrants
  4. LGBTQ+ Communities

This series can expand providers' understanding of:

  • The historical and current experiences of the communities and the impact of these experiences on trust, health, and access
  • Common concerns and needs of marginalized communities
  • The ways in which inequities in these communities can be further magnified when they intersect with homelessness and each other
  • How to use a framework for establishing trust by leading with equity and centering vaccine distribution work on cultural humility and a trauma-informed approach

COVID-19 HMIS Data Usage Series

The Data Collection Options for COVID-19 Vaccines resource released in February 2021 provides data collection recommendations to help communities measure and provide equitable access to the vaccine. The COVID-19 HMIS Data Usage Series intends to support communities’ efforts to leverage local data to improve vaccine rollout strategies. Grounded by a performance improvement framework, the three scenarios featured in the series illustrate how a community navigates the four stages of a performance improvement strategy:

  • Analyzing data
  • Drawing sound conclusions about the story that the data is telling
  • Designing data-informed improvement strategies
  • Monitoring and evaluating strategies to assess whether the intended results have been achieved and are equitable

Collecting vaccine-related data alongside HUD’s required Data Elements gives communities the ability to disaggregate by population groups including race, ethnicity, gender, age groups, geography, people with disabilities, or any other groups identified by your community. The resulting data set gives communities the ability to conduct an intersectional analysis of groups to: 1) ensure they are not overlooking any specific population; and 2) better equip them to examine their systems for effective and equitable vaccine outreach and distribution. We lead with race, the largest predictive factor of inequitable outcomes in homelessness response systems.

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This material is based upon work supported by funding under an award with the U.S. Department of Housing and Urban Development. The substance and findings of the work are dedicated to the public. Neither the United States Government, nor any of its employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately-owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the U.S. Government or any agency thereof. Opinions expressed on the HUD Exchange are those of the authors and do not necessarily reflect the official position of, or a position that is endorsed by, HUD or by any HUD program.