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Challenges to estimating vaccine impact using hospitalization data

Because the real-world impact of new vaccines cannot be known before they are implemented in national programs, post-implementation studies at the population level are critical. Studies based on analysis of hospitalization rates of vaccine-preventable outcomes are typically used for this purpose. Ho...

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Autores principales: Schuck-Paim, Cynthia, Taylor, Robert J., Simonsen, Lone, Lustig, Roger, Kürüm, Esra, Bruhn, Christian A.W., Weinberger, Daniel M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5664940/
https://www.ncbi.nlm.nih.gov/pubmed/27899227
http://dx.doi.org/10.1016/j.vaccine.2016.11.030
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author Schuck-Paim, Cynthia
Taylor, Robert J.
Simonsen, Lone
Lustig, Roger
Kürüm, Esra
Bruhn, Christian A.W.
Weinberger, Daniel M.
author_facet Schuck-Paim, Cynthia
Taylor, Robert J.
Simonsen, Lone
Lustig, Roger
Kürüm, Esra
Bruhn, Christian A.W.
Weinberger, Daniel M.
author_sort Schuck-Paim, Cynthia
collection PubMed
description Because the real-world impact of new vaccines cannot be known before they are implemented in national programs, post-implementation studies at the population level are critical. Studies based on analysis of hospitalization rates of vaccine-preventable outcomes are typically used for this purpose. However, estimates of vaccine impact based on hospitalization data are particularly prone to confounding, as hospitalization rates are tightly linked to changes in the quality, access and use of the healthcare system, which often occur simultaneously with introduction of new vaccines. Here we illustrate how changes in healthcare delivery coincident with vaccine introduction can influence estimates of vaccine impact, using as an example reductions in infant pneumonia hospitalizations after introduction of the 10-valent pneumococcal conjugate vaccine (PCV10) in Brazil. To this end, we explore the effect of changes in several metrics of quality and access to public healthcare on trends in hospitalization rates before (2008–09) and after (2011–12) PCV10 introduction in 2010. Changes in infant pneumonia hospitalization rates following vaccine introduction were significantly associated with concomitant changes in hospital capacity and the fraction of the population using public hospitals. Importantly, reduction of pneumonia hospitalization rates after PCV10 were also associated with the expansion of outpatient services in several Brazilian states, falling more sharply where primary care coverage and the number of health units offering basic and emergency care increased more. We show that adjustments for unrelated (non-vaccine) trends commonly employed by impact studies, such as use of single control outcomes, are not always sufficient for accurate impact assessment. We discuss several ways to identify and overcome such biases, including sensitivity analyses using different denominators to calculate hospitalizations rates and methods that track changes in the outpatient setting. Employing these practices can improve the accuracy of vaccine impact estimates, particularly in evolving healthcare settings typical of low- and middle-income countries.
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spelling pubmed-56649402017-11-01 Challenges to estimating vaccine impact using hospitalization data Schuck-Paim, Cynthia Taylor, Robert J. Simonsen, Lone Lustig, Roger Kürüm, Esra Bruhn, Christian A.W. Weinberger, Daniel M. Vaccine Article Because the real-world impact of new vaccines cannot be known before they are implemented in national programs, post-implementation studies at the population level are critical. Studies based on analysis of hospitalization rates of vaccine-preventable outcomes are typically used for this purpose. However, estimates of vaccine impact based on hospitalization data are particularly prone to confounding, as hospitalization rates are tightly linked to changes in the quality, access and use of the healthcare system, which often occur simultaneously with introduction of new vaccines. Here we illustrate how changes in healthcare delivery coincident with vaccine introduction can influence estimates of vaccine impact, using as an example reductions in infant pneumonia hospitalizations after introduction of the 10-valent pneumococcal conjugate vaccine (PCV10) in Brazil. To this end, we explore the effect of changes in several metrics of quality and access to public healthcare on trends in hospitalization rates before (2008–09) and after (2011–12) PCV10 introduction in 2010. Changes in infant pneumonia hospitalization rates following vaccine introduction were significantly associated with concomitant changes in hospital capacity and the fraction of the population using public hospitals. Importantly, reduction of pneumonia hospitalization rates after PCV10 were also associated with the expansion of outpatient services in several Brazilian states, falling more sharply where primary care coverage and the number of health units offering basic and emergency care increased more. We show that adjustments for unrelated (non-vaccine) trends commonly employed by impact studies, such as use of single control outcomes, are not always sufficient for accurate impact assessment. We discuss several ways to identify and overcome such biases, including sensitivity analyses using different denominators to calculate hospitalizations rates and methods that track changes in the outpatient setting. Employing these practices can improve the accuracy of vaccine impact estimates, particularly in evolving healthcare settings typical of low- and middle-income countries. 2016-11-26 2017-01-03 /pmc/articles/PMC5664940/ /pubmed/27899227 http://dx.doi.org/10.1016/j.vaccine.2016.11.030 Text en This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Schuck-Paim, Cynthia
Taylor, Robert J.
Simonsen, Lone
Lustig, Roger
Kürüm, Esra
Bruhn, Christian A.W.
Weinberger, Daniel M.
Challenges to estimating vaccine impact using hospitalization data
title Challenges to estimating vaccine impact using hospitalization data
title_full Challenges to estimating vaccine impact using hospitalization data
title_fullStr Challenges to estimating vaccine impact using hospitalization data
title_full_unstemmed Challenges to estimating vaccine impact using hospitalization data
title_short Challenges to estimating vaccine impact using hospitalization data
title_sort challenges to estimating vaccine impact using hospitalization data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5664940/
https://www.ncbi.nlm.nih.gov/pubmed/27899227
http://dx.doi.org/10.1016/j.vaccine.2016.11.030
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