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Measuring populations to improve vaccination coverage
In low-income settings, vaccination campaigns supplement routine immunization but often fail to achieve coverage goals due to uncertainty about target population size and distribution. Accurate, updated estimates of target populations are rare but critical; short-term fluctuations can greatly impact...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5050518/ https://www.ncbi.nlm.nih.gov/pubmed/27703191 http://dx.doi.org/10.1038/srep34541 |
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author | Bharti, Nita Djibo, Ali Tatem, Andrew J. Grenfell, Bryan T. Ferrari, Matthew J. |
author_facet | Bharti, Nita Djibo, Ali Tatem, Andrew J. Grenfell, Bryan T. Ferrari, Matthew J. |
author_sort | Bharti, Nita |
collection | PubMed |
description | In low-income settings, vaccination campaigns supplement routine immunization but often fail to achieve coverage goals due to uncertainty about target population size and distribution. Accurate, updated estimates of target populations are rare but critical; short-term fluctuations can greatly impact population size and susceptibility. We use satellite imagery to quantify population fluctuations and the coverage achieved by a measles outbreak response vaccination campaign in urban Niger and compare campaign estimates to measurements from a post-campaign survey. Vaccine coverage was overestimated because the campaign underestimated resident numbers and seasonal migration further increased the target population. We combine satellite-derived measurements of fluctuations in population distribution with high-resolution measles case reports to develop a dynamic model that illustrates the potential improvement in vaccination campaign coverage if planners account for predictable population fluctuations. Satellite imagery can improve retrospective estimates of vaccination campaign impact and future campaign planning by synchronizing interventions with predictable population fluxes. |
format | Online Article Text |
id | pubmed-5050518 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-50505182016-10-11 Measuring populations to improve vaccination coverage Bharti, Nita Djibo, Ali Tatem, Andrew J. Grenfell, Bryan T. Ferrari, Matthew J. Sci Rep Article In low-income settings, vaccination campaigns supplement routine immunization but often fail to achieve coverage goals due to uncertainty about target population size and distribution. Accurate, updated estimates of target populations are rare but critical; short-term fluctuations can greatly impact population size and susceptibility. We use satellite imagery to quantify population fluctuations and the coverage achieved by a measles outbreak response vaccination campaign in urban Niger and compare campaign estimates to measurements from a post-campaign survey. Vaccine coverage was overestimated because the campaign underestimated resident numbers and seasonal migration further increased the target population. We combine satellite-derived measurements of fluctuations in population distribution with high-resolution measles case reports to develop a dynamic model that illustrates the potential improvement in vaccination campaign coverage if planners account for predictable population fluctuations. Satellite imagery can improve retrospective estimates of vaccination campaign impact and future campaign planning by synchronizing interventions with predictable population fluxes. Nature Publishing Group 2016-10-05 /pmc/articles/PMC5050518/ /pubmed/27703191 http://dx.doi.org/10.1038/srep34541 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Bharti, Nita Djibo, Ali Tatem, Andrew J. Grenfell, Bryan T. Ferrari, Matthew J. Measuring populations to improve vaccination coverage |
title | Measuring populations to improve vaccination coverage |
title_full | Measuring populations to improve vaccination coverage |
title_fullStr | Measuring populations to improve vaccination coverage |
title_full_unstemmed | Measuring populations to improve vaccination coverage |
title_short | Measuring populations to improve vaccination coverage |
title_sort | measuring populations to improve vaccination coverage |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5050518/ https://www.ncbi.nlm.nih.gov/pubmed/27703191 http://dx.doi.org/10.1038/srep34541 |
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