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Measuring the Performance of Vaccination Programs Using Cross-Sectional Surveys: A Likelihood Framework and Retrospective Analysis

BACKGROUND: The performance of routine and supplemental immunization activities is usually measured by the administrative method: dividing the number of doses distributed by the size of the target population. This method leads to coverage estimates that are sometimes impossible (e.g., vaccination of...

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Autores principales: Lessler, Justin, Metcalf, C. Jessica E., Grais, Rebecca F., Luquero, Francisco J., Cummings, Derek A. T., Grenfell, Bryan T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3201935/
https://www.ncbi.nlm.nih.gov/pubmed/22039353
http://dx.doi.org/10.1371/journal.pmed.1001110
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author Lessler, Justin
Metcalf, C. Jessica E.
Grais, Rebecca F.
Luquero, Francisco J.
Cummings, Derek A. T.
Grenfell, Bryan T.
author_facet Lessler, Justin
Metcalf, C. Jessica E.
Grais, Rebecca F.
Luquero, Francisco J.
Cummings, Derek A. T.
Grenfell, Bryan T.
author_sort Lessler, Justin
collection PubMed
description BACKGROUND: The performance of routine and supplemental immunization activities is usually measured by the administrative method: dividing the number of doses distributed by the size of the target population. This method leads to coverage estimates that are sometimes impossible (e.g., vaccination of 102% of the target population), and are generally inconsistent with the proportion found to be vaccinated in Demographic and Health Surveys (DHS). We describe a method that estimates the fraction of the population accessible to vaccination activities, as well as within-campaign inefficiencies, thus providing a consistent estimate of vaccination coverage. METHODS AND FINDINGS: We developed a likelihood framework for estimating the effective coverage of vaccination programs using cross-sectional surveys of vaccine coverage combined with administrative data. We applied our method to measles vaccination in three African countries: Ghana, Madagascar, and Sierra Leone, using data from each country's most recent DHS survey and administrative coverage data reported to the World Health Organization. We estimate that 93% (95% CI: 91, 94) of the population in Ghana was ever covered by any measles vaccination activity, 77% (95% CI: 78, 81) in Madagascar, and 69% (95% CI: 67, 70) in Sierra Leone. “Within-activity” inefficiencies were estimated to be low in Ghana, and higher in Sierra Leone and Madagascar. Our model successfully fits age-specific vaccination coverage levels seen in DHS data, which differ markedly from those predicted by naïve extrapolation from country-reported and World Health Organization–adjusted vaccination coverage. CONCLUSIONS: Combining administrative data with survey data substantially improves estimates of vaccination coverage. Estimates of the inefficiency of past vaccination activities and the proportion not covered by any activity allow us to more accurately predict the results of future activities and provide insight into the ways in which vaccination programs are failing to meet their goals. Please see later in the article for the Editors' Summary
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spelling pubmed-32019352011-10-28 Measuring the Performance of Vaccination Programs Using Cross-Sectional Surveys: A Likelihood Framework and Retrospective Analysis Lessler, Justin Metcalf, C. Jessica E. Grais, Rebecca F. Luquero, Francisco J. Cummings, Derek A. T. Grenfell, Bryan T. PLoS Med Research Article BACKGROUND: The performance of routine and supplemental immunization activities is usually measured by the administrative method: dividing the number of doses distributed by the size of the target population. This method leads to coverage estimates that are sometimes impossible (e.g., vaccination of 102% of the target population), and are generally inconsistent with the proportion found to be vaccinated in Demographic and Health Surveys (DHS). We describe a method that estimates the fraction of the population accessible to vaccination activities, as well as within-campaign inefficiencies, thus providing a consistent estimate of vaccination coverage. METHODS AND FINDINGS: We developed a likelihood framework for estimating the effective coverage of vaccination programs using cross-sectional surveys of vaccine coverage combined with administrative data. We applied our method to measles vaccination in three African countries: Ghana, Madagascar, and Sierra Leone, using data from each country's most recent DHS survey and administrative coverage data reported to the World Health Organization. We estimate that 93% (95% CI: 91, 94) of the population in Ghana was ever covered by any measles vaccination activity, 77% (95% CI: 78, 81) in Madagascar, and 69% (95% CI: 67, 70) in Sierra Leone. “Within-activity” inefficiencies were estimated to be low in Ghana, and higher in Sierra Leone and Madagascar. Our model successfully fits age-specific vaccination coverage levels seen in DHS data, which differ markedly from those predicted by naïve extrapolation from country-reported and World Health Organization–adjusted vaccination coverage. CONCLUSIONS: Combining administrative data with survey data substantially improves estimates of vaccination coverage. Estimates of the inefficiency of past vaccination activities and the proportion not covered by any activity allow us to more accurately predict the results of future activities and provide insight into the ways in which vaccination programs are failing to meet their goals. Please see later in the article for the Editors' Summary Public Library of Science 2011-10-25 /pmc/articles/PMC3201935/ /pubmed/22039353 http://dx.doi.org/10.1371/journal.pmed.1001110 Text en Lessler et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Lessler, Justin
Metcalf, C. Jessica E.
Grais, Rebecca F.
Luquero, Francisco J.
Cummings, Derek A. T.
Grenfell, Bryan T.
Measuring the Performance of Vaccination Programs Using Cross-Sectional Surveys: A Likelihood Framework and Retrospective Analysis
title Measuring the Performance of Vaccination Programs Using Cross-Sectional Surveys: A Likelihood Framework and Retrospective Analysis
title_full Measuring the Performance of Vaccination Programs Using Cross-Sectional Surveys: A Likelihood Framework and Retrospective Analysis
title_fullStr Measuring the Performance of Vaccination Programs Using Cross-Sectional Surveys: A Likelihood Framework and Retrospective Analysis
title_full_unstemmed Measuring the Performance of Vaccination Programs Using Cross-Sectional Surveys: A Likelihood Framework and Retrospective Analysis
title_short Measuring the Performance of Vaccination Programs Using Cross-Sectional Surveys: A Likelihood Framework and Retrospective Analysis
title_sort measuring the performance of vaccination programs using cross-sectional surveys: a likelihood framework and retrospective analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3201935/
https://www.ncbi.nlm.nih.gov/pubmed/22039353
http://dx.doi.org/10.1371/journal.pmed.1001110
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