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Estimating vaccine coverage in conflict settings using geospatial methods: a case study in Borno state, Nigeria

Reliable estimates of subnational vaccination coverage are critical to track progress towards global immunisation targets and ensure equitable health outcomes for all children. However, conflict can limit the reliability of coverage estimates from traditional household-based surveys due to an inabil...

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Autores principales: Sbarra, Alyssa N., Rolfe, Sam, Haeuser, Emily, Nguyen, Jason Q., Adamu, Aishatu, Adeyinka, Daniel, Ajumobi, Olufemi, Akunna, Chisom, Amusa, Ganiyu, Dahiru, Tukur, Ekholuenetale, Michael, Esezobor, Christopher, Fowobaje, Kayode, Hay, Simon I., Ibeneme, Charles, Ibitoye, Segun Emmanuel, Ilesanmi, Olayinka, Kayode, Gbenga, Krohn, Kris, Lim, Stephen S., Medeiros, Lyla E., Mohammed, Shafiu, Nwatah, Vincent, Okoro, Anselm, Olagunju, Andrew T., Olusanya, Bolajoko O., Osarenotor, Osayomwanbo, Owolabi, Mayowa, Pickering, Brandon, Sufiyan, Mu’awiyyah Babale, Uzochukwu, Benjamin, Walker, Ally, Mosser, Jonathan F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10329660/
https://www.ncbi.nlm.nih.gov/pubmed/37422502
http://dx.doi.org/10.1038/s41598-023-37947-8
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author Sbarra, Alyssa N.
Rolfe, Sam
Haeuser, Emily
Nguyen, Jason Q.
Adamu, Aishatu
Adeyinka, Daniel
Ajumobi, Olufemi
Akunna, Chisom
Amusa, Ganiyu
Dahiru, Tukur
Ekholuenetale, Michael
Esezobor, Christopher
Fowobaje, Kayode
Hay, Simon I.
Ibeneme, Charles
Ibitoye, Segun Emmanuel
Ilesanmi, Olayinka
Kayode, Gbenga
Krohn, Kris
Lim, Stephen S.
Medeiros, Lyla E.
Mohammed, Shafiu
Nwatah, Vincent
Okoro, Anselm
Olagunju, Andrew T.
Olusanya, Bolajoko O.
Osarenotor, Osayomwanbo
Owolabi, Mayowa
Pickering, Brandon
Sufiyan, Mu’awiyyah Babale
Uzochukwu, Benjamin
Walker, Ally
Mosser, Jonathan F.
author_facet Sbarra, Alyssa N.
Rolfe, Sam
Haeuser, Emily
Nguyen, Jason Q.
Adamu, Aishatu
Adeyinka, Daniel
Ajumobi, Olufemi
Akunna, Chisom
Amusa, Ganiyu
Dahiru, Tukur
Ekholuenetale, Michael
Esezobor, Christopher
Fowobaje, Kayode
Hay, Simon I.
Ibeneme, Charles
Ibitoye, Segun Emmanuel
Ilesanmi, Olayinka
Kayode, Gbenga
Krohn, Kris
Lim, Stephen S.
Medeiros, Lyla E.
Mohammed, Shafiu
Nwatah, Vincent
Okoro, Anselm
Olagunju, Andrew T.
Olusanya, Bolajoko O.
Osarenotor, Osayomwanbo
Owolabi, Mayowa
Pickering, Brandon
Sufiyan, Mu’awiyyah Babale
Uzochukwu, Benjamin
Walker, Ally
Mosser, Jonathan F.
author_sort Sbarra, Alyssa N.
collection PubMed
description Reliable estimates of subnational vaccination coverage are critical to track progress towards global immunisation targets and ensure equitable health outcomes for all children. However, conflict can limit the reliability of coverage estimates from traditional household-based surveys due to an inability to sample in unsafe and insecure areas and increased uncertainty in underlying population estimates. In these situations, model-based geostatistical (MBG) approaches offer alternative coverage estimates for administrative units affected by conflict. We estimated first- and third-dose diphtheria-tetanus-pertussis vaccine coverage in Borno state, Nigeria, using a spatiotemporal MBG modelling approach, then compared these to estimates from recent conflict-affected, household-based surveys. We compared sampling cluster locations from recent household-based surveys to geolocated data on conflict locations and modelled spatial coverage estimates, while also investigating the importance of reliable population estimates when assessing coverage in conflict settings. These results demonstrate that geospatially-modelled coverage estimates can be a valuable additional tool to understand coverage in locations where conflict prevents representative sampling.
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spelling pubmed-103296602023-07-10 Estimating vaccine coverage in conflict settings using geospatial methods: a case study in Borno state, Nigeria Sbarra, Alyssa N. Rolfe, Sam Haeuser, Emily Nguyen, Jason Q. Adamu, Aishatu Adeyinka, Daniel Ajumobi, Olufemi Akunna, Chisom Amusa, Ganiyu Dahiru, Tukur Ekholuenetale, Michael Esezobor, Christopher Fowobaje, Kayode Hay, Simon I. Ibeneme, Charles Ibitoye, Segun Emmanuel Ilesanmi, Olayinka Kayode, Gbenga Krohn, Kris Lim, Stephen S. Medeiros, Lyla E. Mohammed, Shafiu Nwatah, Vincent Okoro, Anselm Olagunju, Andrew T. Olusanya, Bolajoko O. Osarenotor, Osayomwanbo Owolabi, Mayowa Pickering, Brandon Sufiyan, Mu’awiyyah Babale Uzochukwu, Benjamin Walker, Ally Mosser, Jonathan F. Sci Rep Article Reliable estimates of subnational vaccination coverage are critical to track progress towards global immunisation targets and ensure equitable health outcomes for all children. However, conflict can limit the reliability of coverage estimates from traditional household-based surveys due to an inability to sample in unsafe and insecure areas and increased uncertainty in underlying population estimates. In these situations, model-based geostatistical (MBG) approaches offer alternative coverage estimates for administrative units affected by conflict. We estimated first- and third-dose diphtheria-tetanus-pertussis vaccine coverage in Borno state, Nigeria, using a spatiotemporal MBG modelling approach, then compared these to estimates from recent conflict-affected, household-based surveys. We compared sampling cluster locations from recent household-based surveys to geolocated data on conflict locations and modelled spatial coverage estimates, while also investigating the importance of reliable population estimates when assessing coverage in conflict settings. These results demonstrate that geospatially-modelled coverage estimates can be a valuable additional tool to understand coverage in locations where conflict prevents representative sampling. Nature Publishing Group UK 2023-07-08 /pmc/articles/PMC10329660/ /pubmed/37422502 http://dx.doi.org/10.1038/s41598-023-37947-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Sbarra, Alyssa N.
Rolfe, Sam
Haeuser, Emily
Nguyen, Jason Q.
Adamu, Aishatu
Adeyinka, Daniel
Ajumobi, Olufemi
Akunna, Chisom
Amusa, Ganiyu
Dahiru, Tukur
Ekholuenetale, Michael
Esezobor, Christopher
Fowobaje, Kayode
Hay, Simon I.
Ibeneme, Charles
Ibitoye, Segun Emmanuel
Ilesanmi, Olayinka
Kayode, Gbenga
Krohn, Kris
Lim, Stephen S.
Medeiros, Lyla E.
Mohammed, Shafiu
Nwatah, Vincent
Okoro, Anselm
Olagunju, Andrew T.
Olusanya, Bolajoko O.
Osarenotor, Osayomwanbo
Owolabi, Mayowa
Pickering, Brandon
Sufiyan, Mu’awiyyah Babale
Uzochukwu, Benjamin
Walker, Ally
Mosser, Jonathan F.
Estimating vaccine coverage in conflict settings using geospatial methods: a case study in Borno state, Nigeria
title Estimating vaccine coverage in conflict settings using geospatial methods: a case study in Borno state, Nigeria
title_full Estimating vaccine coverage in conflict settings using geospatial methods: a case study in Borno state, Nigeria
title_fullStr Estimating vaccine coverage in conflict settings using geospatial methods: a case study in Borno state, Nigeria
title_full_unstemmed Estimating vaccine coverage in conflict settings using geospatial methods: a case study in Borno state, Nigeria
title_short Estimating vaccine coverage in conflict settings using geospatial methods: a case study in Borno state, Nigeria
title_sort estimating vaccine coverage in conflict settings using geospatial methods: a case study in borno state, nigeria
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10329660/
https://www.ncbi.nlm.nih.gov/pubmed/37422502
http://dx.doi.org/10.1038/s41598-023-37947-8
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