Cargando…
Estimating the Potential Effects of a Vaccine Program Against an Emerging Influenza Pandemic—United States
Background. Human illness from influenza A(H7N9) was identified in March 2013, and candidate vaccine viruses were soon developed. To understand factors that may impact influenza vaccination programs, we developed a model to evaluate hospitalizations and deaths averted considering various scenarios....
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4610126/ https://www.ncbi.nlm.nih.gov/pubmed/25878298 http://dx.doi.org/10.1093/cid/ciu1175 |
_version_ | 1782395906003304448 |
---|---|
author | Biggerstaff, Matthew Reed, Carrie Swerdlow, David L. Gambhir, Manoj Graitcer, Samuel Finelli, Lyn Borse, Rebekah H. Rasmussen, Sonja A. Meltzer, Martin I. Bridges, Carolyn B. |
author_facet | Biggerstaff, Matthew Reed, Carrie Swerdlow, David L. Gambhir, Manoj Graitcer, Samuel Finelli, Lyn Borse, Rebekah H. Rasmussen, Sonja A. Meltzer, Martin I. Bridges, Carolyn B. |
author_sort | Biggerstaff, Matthew |
collection | PubMed |
description | Background. Human illness from influenza A(H7N9) was identified in March 2013, and candidate vaccine viruses were soon developed. To understand factors that may impact influenza vaccination programs, we developed a model to evaluate hospitalizations and deaths averted considering various scenarios. Methods. We utilized a model incorporating epidemic curves with clinical attack rates of 20% or 30% in a single wave of illness, case hospitalization ratios of 0.5% or 4.2%, and case fatality ratios of 0.08% or 0.53%. We considered scenarios that achieved 80% vaccination coverage, various starts of vaccination programs (16 or 8 weeks before, the same week of, or 8 or 16 weeks after start of pandemic), an administration rate of 10 or 30 million doses per week (the latter rate is an untested assumption), and 2 levels of vaccine effectiveness (2 doses of vaccine required; either 62% or 80% effective for persons aged <60 years, and either 43% or 60% effective for persons aged ≥60 years). Results. The start date of vaccination campaigns most influenced impact; 141 000–2 200 000 hospitalizations and 11 000–281 000 deaths were averted when campaigns started before a pandemic, and <100–1 300 000 hospitalizations and 0–165 000 deaths were averted for programs beginning the same time as or after the introduction of the pandemic virus. The rate of vaccine administration and vaccine effectiveness did not influence campaign impact as much as timing of the start of campaign. Conclusions. Our findings suggest that efforts to improve the timeliness of vaccine production will provide the greatest impacts for future pandemic vaccination programs. |
format | Online Article Text |
id | pubmed-4610126 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-46101262016-05-01 Estimating the Potential Effects of a Vaccine Program Against an Emerging Influenza Pandemic—United States Biggerstaff, Matthew Reed, Carrie Swerdlow, David L. Gambhir, Manoj Graitcer, Samuel Finelli, Lyn Borse, Rebekah H. Rasmussen, Sonja A. Meltzer, Martin I. Bridges, Carolyn B. Clin Infect Dis Cdc Modeling Efforts in Response to a Potential Public Health Emergency: Influenza A (H7N9) as an Example Background. Human illness from influenza A(H7N9) was identified in March 2013, and candidate vaccine viruses were soon developed. To understand factors that may impact influenza vaccination programs, we developed a model to evaluate hospitalizations and deaths averted considering various scenarios. Methods. We utilized a model incorporating epidemic curves with clinical attack rates of 20% or 30% in a single wave of illness, case hospitalization ratios of 0.5% or 4.2%, and case fatality ratios of 0.08% or 0.53%. We considered scenarios that achieved 80% vaccination coverage, various starts of vaccination programs (16 or 8 weeks before, the same week of, or 8 or 16 weeks after start of pandemic), an administration rate of 10 or 30 million doses per week (the latter rate is an untested assumption), and 2 levels of vaccine effectiveness (2 doses of vaccine required; either 62% or 80% effective for persons aged <60 years, and either 43% or 60% effective for persons aged ≥60 years). Results. The start date of vaccination campaigns most influenced impact; 141 000–2 200 000 hospitalizations and 11 000–281 000 deaths were averted when campaigns started before a pandemic, and <100–1 300 000 hospitalizations and 0–165 000 deaths were averted for programs beginning the same time as or after the introduction of the pandemic virus. The rate of vaccine administration and vaccine effectiveness did not influence campaign impact as much as timing of the start of campaign. Conclusions. Our findings suggest that efforts to improve the timeliness of vaccine production will provide the greatest impacts for future pandemic vaccination programs. Oxford University Press 2015-05-01 2015-04-10 /pmc/articles/PMC4610126/ /pubmed/25878298 http://dx.doi.org/10.1093/cid/ciu1175 Text en Published by Oxford University Press on behalf of the Infectious Diseases Society of America 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections. |
spellingShingle | Cdc Modeling Efforts in Response to a Potential Public Health Emergency: Influenza A (H7N9) as an Example Biggerstaff, Matthew Reed, Carrie Swerdlow, David L. Gambhir, Manoj Graitcer, Samuel Finelli, Lyn Borse, Rebekah H. Rasmussen, Sonja A. Meltzer, Martin I. Bridges, Carolyn B. Estimating the Potential Effects of a Vaccine Program Against an Emerging Influenza Pandemic—United States |
title | Estimating the Potential Effects of a Vaccine Program Against an Emerging Influenza Pandemic—United States |
title_full | Estimating the Potential Effects of a Vaccine Program Against an Emerging Influenza Pandemic—United States |
title_fullStr | Estimating the Potential Effects of a Vaccine Program Against an Emerging Influenza Pandemic—United States |
title_full_unstemmed | Estimating the Potential Effects of a Vaccine Program Against an Emerging Influenza Pandemic—United States |
title_short | Estimating the Potential Effects of a Vaccine Program Against an Emerging Influenza Pandemic—United States |
title_sort | estimating the potential effects of a vaccine program against an emerging influenza pandemic—united states |
topic | Cdc Modeling Efforts in Response to a Potential Public Health Emergency: Influenza A (H7N9) as an Example |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4610126/ https://www.ncbi.nlm.nih.gov/pubmed/25878298 http://dx.doi.org/10.1093/cid/ciu1175 |
work_keys_str_mv | AT biggerstaffmatthew estimatingthepotentialeffectsofavaccineprogramagainstanemerginginfluenzapandemicunitedstates AT reedcarrie estimatingthepotentialeffectsofavaccineprogramagainstanemerginginfluenzapandemicunitedstates AT swerdlowdavidl estimatingthepotentialeffectsofavaccineprogramagainstanemerginginfluenzapandemicunitedstates AT gambhirmanoj estimatingthepotentialeffectsofavaccineprogramagainstanemerginginfluenzapandemicunitedstates AT graitcersamuel estimatingthepotentialeffectsofavaccineprogramagainstanemerginginfluenzapandemicunitedstates AT finellilyn estimatingthepotentialeffectsofavaccineprogramagainstanemerginginfluenzapandemicunitedstates AT borserebekahh estimatingthepotentialeffectsofavaccineprogramagainstanemerginginfluenzapandemicunitedstates AT rasmussensonjaa estimatingthepotentialeffectsofavaccineprogramagainstanemerginginfluenzapandemicunitedstates AT meltzermartini estimatingthepotentialeffectsofavaccineprogramagainstanemerginginfluenzapandemicunitedstates AT bridgescarolynb estimatingthepotentialeffectsofavaccineprogramagainstanemerginginfluenzapandemicunitedstates |