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Spatial Accessibility Modeling of Vaccine Deserts as Barriers to Controlling SARS-CoV-2 Transmission
Benjamin Rader; Christina M Astley; Kara Sewalk; Paul L Delamater; Kathryn Cordiano; Laura Wronski; Jessica Malaty Rivera; Kai Hallberg; Megan F Pera; Jonathan Cantor; Christopher Whaley; Dena Bravata; John S Brownstein.
Afiliación
  • Benjamin Rader; Boston University
  • Christina M Astley; Boston Children's Hospital
  • Kara Sewalk; Boston Children's Hospital
  • Paul L Delamater; University of North Carolina at Chapel Hill
  • Kathryn Cordiano; Boston Children's Hospital
  • Laura Wronski; SurveyMonkey
  • Jessica Malaty Rivera; The COVID Tracking Project at The Atlantic
  • Kai Hallberg; Castlight Health
  • Megan F Pera; Castlight Health
  • Jonathan Cantor; RAND Corporation
  • Christopher Whaley; RAND Corporation
  • Dena Bravata; Castlight Health
  • John S Brownstein; Boston Children's Hospital
Preprint en En | PREPRINT-MEDRXIV | ID: ppmedrxiv-21252858
ABSTRACT
SARS-CoV-2 vaccine distribution is at risk of further propagating the inequities of COVID-19, which in the United States (US) has disproportionately impacted the elderly, people of color, and the medically vulnerable. We identify vaccine deserts - US Census tracts with localized, geographic barriers to vaccine-associated herd immunity - using a comprehensive supply database (VaccineFinder) and an empirically parameterized model of spatial access to essential resources. Incorporating high-resolution COVID-19 burden and time-willing-to-travel for vaccination, we show that early (February - March 2021) vaccine allocation disadvantaged rural and medically vulnerable populations. Data-driven vaccine distribution to vaccine deserts may improve immunization in the hesitant and control SARS-CoV-2.
Licencia
cc_by_nc_nd
Texto completo: 1 Colección: 09-preprints Base de datos: PREPRINT-MEDRXIV Tipo de estudio: Prognostic_studies Idioma: En Año: 2021 Tipo del documento: Preprint
Texto completo: 1 Colección: 09-preprints Base de datos: PREPRINT-MEDRXIV Tipo de estudio: Prognostic_studies Idioma: En Año: 2021 Tipo del documento: Preprint