Your browser doesn't support javascript.
loading
How the Timing of Annual COVID-19 Vaccination of Nursing Home Residents and Staff Affects Its Value.
Bartsch, Sarah M; Weatherwax, Colleen; Wasserman, Michael R; Chin, Kevin L; Martinez, Marie F; Velmurugan, Kavya; Singh, Raveena D; John, Danielle C; Heneghan, Jessie L; Gussin, Gabrielle M; Scannell, Sheryl A; Tsintsifas, Alexandra C; O'Shea, Kelly J; Dibbs, Alexis M; Leff, Bruce; Huang, Susan S; Lee, Bruce Y.
Afiliación
  • Bartsch SM; Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY,
  • Weatherwax C; Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY,
  • Wasserman MR; California Association of Long Term Care Medicine, Santa Clarita, CA, USA.
  • Chin KL; Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY,
  • Martinez MF; Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY,
  • Velmurugan K; Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY,
  • Singh RD; Division of Infectious Diseases, University of California Irvine School of Medicine, Irvine, CA, USA.
  • John DC; Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY,
  • Heneghan JL; Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY,
  • Gussin GM; Division of Infectious Diseases, University of California Irvine School of Medicine, Irvine, CA, USA.
  • Scannell SA; Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY,
  • Tsintsifas AC; Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY,
  • O'Shea KJ; Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY,
  • Dibbs AM; Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY,
  • Leff B; Division of Geriatric Medicine, Center for Transformative Geriatric Research, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
  • Huang SS; Division of Infectious Diseases, University of California Irvine School of Medicine, Irvine, CA, USA.
  • Lee BY; Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY,
J Am Med Dir Assoc ; 25(4): 639-646.e5, 2024 Apr.
Article en En | MEDLINE | ID: mdl-38432644
ABSTRACT

OBJECTIVES:

To evaluate the epidemiologic, clinical, and economic value of an annual nursing home (NH) COVID-19 vaccine campaign and the impact of when vaccination starts.

DESIGN:

Agent-based model representing a typical NH. SETTING AND

PARTICIPANTS:

NH residents and staff.

METHODS:

We used the model representing an NH with 100 residents, its staff, their interactions, COVID-19 spread, and its health and economic outcomes to evaluate the epidemiologic, clinical, and economic value of varying schedules of annual COVID-19 vaccine campaigns.

RESULTS:

Across a range of scenarios with a 60% vaccine efficacy that wanes starting 4 months after protection onset, vaccination was cost saving or cost-effective when initiated in the late summer or early fall. Annual vaccination averted 102 to 105 COVID-19 cases when 30-day vaccination campaigns began between July and October (varying with vaccination start), decreasing to 97 and 85 cases when starting in November and December, respectively. Starting vaccination between July and December saved $3340 to $4363 and $64,375 to $77,548 from the Centers for Medicare & Medicaid Services and societal perspectives, respectively (varying with vaccination start). Vaccination's value did not change when varying the COVID-19 peak between December and February. The ideal vaccine campaign timing was not affected by reducing COVID-19 levels in the community, or varying transmission probability, preexisting immunity, or COVID-19 severity. However, if vaccine efficacy wanes more quickly (over 1 month), earlier vaccination in July resulted in more cases compared with vaccinating later in October. CONCLUSIONS AND IMPLICATIONS Annual vaccination of NH staff and residents averted the most cases when initiated in the late summer through early fall, at least 2 months before the COVID-19 winter peak but remained cost saving or cost-effective when it starts in the same month as the peak. This supports tethering COVID vaccination to seasonal influenza campaigns (typically in September-October) for providing protection against SARS-CoV-2 winter surges in NHs.
Asunto(s)
Palabras clave

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Vacunas contra la COVID-19 / COVID-19 Límite: Aged / Humans País/Región como asunto: America do norte Idioma: En Revista: J Am Med Dir Assoc Asunto de la revista: HISTORIA DA MEDICINA / MEDICINA Año: 2024 Tipo del documento: Article

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Vacunas contra la COVID-19 / COVID-19 Límite: Aged / Humans País/Región como asunto: America do norte Idioma: En Revista: J Am Med Dir Assoc Asunto de la revista: HISTORIA DA MEDICINA / MEDICINA Año: 2024 Tipo del documento: Article