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Optimal SARS-CoV-2 vaccine allocation using real-time seroprevalence estimates in Rhode Island and Massachusetts
Thu Nguyen-Anh Tran; Nathan Wikle; Joseph Albert; Haider Inam; Emily R Strong; Karel Brinda; Scott M Leighow; Fuhan Yang; Sajid Hossain; Justin R Pritchard; Philip Chan; William P Hanage; Ephraim M Hanks; Maciej F Boni.
Afiliação
  • Thu Nguyen-Anh Tran; Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, University Park, PA
  • Nathan Wikle; Center for Infectious Disease Dynamics, Department of Statistics, Pennsylvania State University, University Park, PA
  • Joseph Albert; Department of Physics, Pennsylvania State University, University Park, PA
  • Haider Inam; Center for Infectious Disease Dynamics, Department of Bioengineering, Pennsylvania State University, University Park, PA
  • Emily R Strong; Center for Infectious Disease Dynamics, Department of Statistics, Pennsylvania State University, University Park, PA
  • Karel Brinda; Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA
  • Scott M Leighow; Center for Infectious Disease Dynamics, Department of Bioengineering, Pennsylvania State University, University Park, PA
  • Fuhan Yang; Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, University Park, PA
  • Sajid Hossain; Yale School of Medicine, Yale University, New Haven, CT
  • Justin R Pritchard; Center for Infectious Disease Dynamics, Department of Bioengineering, Pennsylvania State University, University Park, PA
  • Philip Chan; Department of Medicine, Brown University, Providence, RI
  • William P Hanage; Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA
  • Ephraim M Hanks; Center for Infectious Disease Dynamics, Department of Statistics, Pennsylvania State University, University Park, PA
  • Maciej F Boni; Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, University Park, PA
Preprint em Inglês | medRxiv | ID: ppmedrxiv-21249694
ABSTRACT
As three SARS-CoV-2 vaccines come to market in Europe and North America in the winter of 2020-2021, distribution networks will be in a race against a major epidemiological wave of SARS-CoV-2 that began in autumn 2020. Rapid and optimized vaccine allocation is critical during this time. With 95% efficacy reported for two of the vaccines, near-term public health needs require that distribution is prioritized to the elderly, health-care workers, teachers, essential workers, and individuals with co-morbidities putting them at risk of severe clinical progression. Here, we evaluate various age-based vaccine distributions using a validated mathematical model based on current epidemic trends in Rhode Island and Massachusetts. We allow for varying waning efficacy of vaccine-induced immunity, as this has not yet been measured. We account for the fact that known COVID-positive cases may not be included in the first round of vaccination. And, we account for current age-specific immune patterns in both states. We find that allocating a substantial proportion (> 75%) of vaccine supply to individuals over the age of 70 is optimal in terms of reducing total cumulative deaths through mid-2021. As we do not explicitly model other high mortality groups, this result on vaccine allocation applies to all groups at high risk of mortality if infected. Our analysis confirms that for an easily transmissible respiratory virus, allocating a large majority of vaccinations to groups with the highest mortality risk is optimal. Our analysis assumes that health systems during winter 2020-2021 have equal staffing and capacity to previous phases of the SARS-CoV-2 epidemic; we do not consider the effects of understaffed hospitals or unvaccinated medical staff. Vaccinating only seronegative individuals avoids redundancy in vaccine use on individuals that may already be immune, and will result in 1% to 2% reductions in cumulative hospitalizations and deaths by mid-2021. Assuming high vaccination coverage (> 28%) and no major relaxations in distancing, masking, gathering size, or hygiene guidelines between now and spring 2021, our model predicts that a combination of vaccination and population immunity will lead to low or near-zero transmission levels by the second quarter of 2021.
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Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Experimental_studies / Estudo observacional / Estudo prognóstico / Rct Idioma: Inglês Ano de publicação: 2021 Tipo de documento: Preprint
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Experimental_studies / Estudo observacional / Estudo prognóstico / Rct Idioma: Inglês Ano de publicação: 2021 Tipo de documento: Preprint
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