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Can vaccine prioritization reduce disparities in COVID-19 burden for historically marginalized populations?
Rosenstrom, Erik T; Mele, Jessica; Ivy, Julie S; Mayorga, Maria E; Patel, Mehul D; Lich, Kristen Hassmiller; Johnson, Karl; Delamater, Paul; Keskinocak, Pinar; Boyce, Ross; Smith, Raymond; Swann, Julie L.
Afiliación
  • Rosenstrom ET; Department of Industrial and Systems Engineering, North Carolina State University, 915 Partners Way, Campus Box 7906, Raleigh, NC 27606, USA.
  • Mele J; Department of Industrial and Systems Engineering, North Carolina State University, 915 Partners Way, Campus Box 7906, Raleigh, NC 27606, USA.
  • Ivy JS; Department of Industrial and Systems Engineering, North Carolina State University, 915 Partners Way, Campus Box 7906, Raleigh, NC 27606, USA.
  • Mayorga ME; Department of Industrial and Systems Engineering, North Carolina State University, 915 Partners Way, Campus Box 7906, Raleigh, NC 27606, USA.
  • Patel MD; Department of Emergency Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
  • Lich KH; Department of Health Policy and Management, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
  • Johnson K; Department of Health Policy and Management, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
  • Delamater P; Department of Geography, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
  • Keskinocak P; Department of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.
  • Boyce R; Division of Infectious Diseases, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
  • Smith R; Department of Engineering, East Carolina University, Greenville, NC 27834, USA.
  • Swann JL; Department of Industrial and Systems Engineering, North Carolina State University, 915 Partners Way, Campus Box 7906, Raleigh, NC 27606, USA.
PNAS Nexus ; 1(1): pgab004, 2022 Mar.
Article en En | MEDLINE | ID: mdl-36712803
ABSTRACT
SARS-CoV-2 vaccination strategies were designed to reduce COVID-19 mortality, morbidity, and health inequities. To assess the impact of vaccination strategies on disparities in COVID-19 burden among historically marginalized populations (HMPs), e.g. Black race and Hispanic ethnicity, we used an agent-based simulation model, populated with census-tract data from North Carolina. We projected COVID-19 deaths, hospitalizations, and cases from 2020 July 1 to 2021 December 31, and estimated racial/ethnic disparities in COVID-19 outcomes. We modeled 2-stage vaccination prioritization scenarios applied to sub-groups including essential workers, older adults (65+), adults with high-risk health conditions, HMPs, or people in low-income tracts. Additionally, we estimated the effects of maximal uptake (100% for HMP vs. 100% for everyone), and distribution to only susceptible people. We found strategies prioritizing essential workers, then older adults led to the largest mortality and case reductions compared to no prioritization. Under baseline uptake scenarios, the age-adjusted mortality for HMPs was higher (e.g. 33.3%-34.1% higher for the Black population and 13.3%-17.0% for the Hispanic population) compared to the White population. The burden on HMPs decreased only when uptake was increased to 100% in HMPs; however, the Black population still had the highest relative mortality rate even when targeted distribution strategies were employed. If prioritization schemes were not paired with increased uptake in HMPs, disparities did not improve. The vaccination strategies publicly outlined were insufficient, exacerbating disparities between racial and ethnic groups. Strategies targeted to increase vaccine uptake among HMPs are needed to ensure equitable distribution and minimize disparities in outcomes.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: PNAS Nexus Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: PNAS Nexus Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos