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Mapping the distribution of zero-dose children to assess the performance of vaccine delivery strategies and their relationships with measles incidence in Nigeria

Mapping the distribution of zero-dose children to assess the performance of vaccine delivery strategies and their relationships with measles incidence in Nigeria
Mapping the distribution of zero-dose children to assess the performance of vaccine delivery strategies and their relationships with measles incidence in Nigeria
Geographically precise identification and targeting of populations at risk of vaccine-preventable diseases has gained renewed attention within the global health community over the last few years. District level estimates of vaccination coverage and corresponding zero-dose prevalence constitute a potentially useful evidence base to evaluate the performance of vaccination strategies. These estimates are also valuable for identifying missed communities, hence enabling targeted interventions and better resource allocation. Here, we fit Bayesian geostatistical models to map the routine coverage of the first doses of diphtheria-tetanus-pertussis vaccine (DTP1) and measles-containing vaccine (MCV1) and corresponding zero-dose estimates in Nigeria at 1x1 km resolution and the district level using geospatial data sets. We also map MCV1 coverage before and after the 2019 measles vaccination campaign in the northern states to further explore variations in routine vaccine coverage and to evaluate the effectiveness of both routine immunization (RI) and campaigns in reaching zero-dose children. Additionally, we map the spatial distributions of reported measles cases during 2018 to 2020 and explore their relationships with MCV zero-dose prevalence to highlight the public health implications of varying performance of vaccination strategies across the country. Our analysis revealed strong similarities between the spatial distributions of DTP and MCV zero dose prevalence, with districts with the highest prevalence concentrated mostly in the northwest and the northeast, but also in other areas such as Lagos state and the Federal Capital Territory. Although the 2019 campaign reduced MCV zero-dose prevalence substantially in the north, pockets of vulnerabilities remained in areas that had among the highest prevalence prior to the campaign. Importantly, we found strong correlations between measles case counts and MCV RI zero-dose estimates, which provides a strong indication that measles incidence in the country is mostly affected by RI coverage. Our analyses reveal an urgent and highly significant need to strengthen the country’s RI program as a longer-term measure for disease control, whilst ensuring effective campaigns in the short term.
MCV1 coverage, DTP1 coverage, Zero-dose prevalence, Measles incidence, Bayesian geostatistical modelling
0264-410X
170-181
Utazi, Chigozie
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Aheto, Justice
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Wigley, Adelle
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Tejedor Garavito, Natalia
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Bonnie, Amy
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Nnanatu, Chibuzor Christopher
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Wagai, John
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Williams, Cheryl
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Setayesh, Hamidreza
adf13c0f-c782-485b-bba6-0fe2ffa14be5
Tatem, Andrew
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Cutts, Felicity T.
25ed9d13-371b-4f1a-a15d-ca20f7e0d502
Utazi, Chigozie
e69ca81e-fb23-4bc1-99a5-25c9e0f4d6f9
Aheto, Justice
dfdbcbd6-229b-4af8-86b5-e698e62fe29f
Wigley, Adelle
21b38ae2-ffd3-4d45-bf29-843e6d62807f
Tejedor Garavito, Natalia
26fd242c-c882-4210-a74d-af2bb6753ee3
Bonnie, Amy
2f08b4e7-768a-4aa0-8c4c-4d23f0b01311
Nnanatu, Chibuzor Christopher
24be7c1b-a677-4086-91b4-a9d9b1efa5a3
Wagai, John
49841d59-cef4-4775-b3a7-0b076a4c4969
Williams, Cheryl
8a5dd0f6-bd0c-4c60-be62-6b9754e138e5
Setayesh, Hamidreza
adf13c0f-c782-485b-bba6-0fe2ffa14be5
Tatem, Andrew
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Cutts, Felicity T.
25ed9d13-371b-4f1a-a15d-ca20f7e0d502

Utazi, Chigozie, Aheto, Justice, Wigley, Adelle, Tejedor Garavito, Natalia, Bonnie, Amy, Nnanatu, Chibuzor Christopher, Wagai, John, Williams, Cheryl, Setayesh, Hamidreza, Tatem, Andrew and Cutts, Felicity T. (2023) Mapping the distribution of zero-dose children to assess the performance of vaccine delivery strategies and their relationships with measles incidence in Nigeria. Vaccine, 41 (1), 170-181. (doi:10.1016/j.vaccine.2022.11.026).

Record type: Article

Abstract

Geographically precise identification and targeting of populations at risk of vaccine-preventable diseases has gained renewed attention within the global health community over the last few years. District level estimates of vaccination coverage and corresponding zero-dose prevalence constitute a potentially useful evidence base to evaluate the performance of vaccination strategies. These estimates are also valuable for identifying missed communities, hence enabling targeted interventions and better resource allocation. Here, we fit Bayesian geostatistical models to map the routine coverage of the first doses of diphtheria-tetanus-pertussis vaccine (DTP1) and measles-containing vaccine (MCV1) and corresponding zero-dose estimates in Nigeria at 1x1 km resolution and the district level using geospatial data sets. We also map MCV1 coverage before and after the 2019 measles vaccination campaign in the northern states to further explore variations in routine vaccine coverage and to evaluate the effectiveness of both routine immunization (RI) and campaigns in reaching zero-dose children. Additionally, we map the spatial distributions of reported measles cases during 2018 to 2020 and explore their relationships with MCV zero-dose prevalence to highlight the public health implications of varying performance of vaccination strategies across the country. Our analysis revealed strong similarities between the spatial distributions of DTP and MCV zero dose prevalence, with districts with the highest prevalence concentrated mostly in the northwest and the northeast, but also in other areas such as Lagos state and the Federal Capital Territory. Although the 2019 campaign reduced MCV zero-dose prevalence substantially in the north, pockets of vulnerabilities remained in areas that had among the highest prevalence prior to the campaign. Importantly, we found strong correlations between measles case counts and MCV RI zero-dose estimates, which provides a strong indication that measles incidence in the country is mostly affected by RI coverage. Our analyses reveal an urgent and highly significant need to strengthen the country’s RI program as a longer-term measure for disease control, whilst ensuring effective campaigns in the short term.

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Accepted/In Press date: 14 November 2022
Published date: 4 January 2023
Additional Information: Funding Information: This work was supported by funding from the Bill & Melinda Gates Foundation (Investment ID INV-003287 ). Publisher Copyright: © 2022 The Author(s)
Keywords: MCV1 coverage, DTP1 coverage, Zero-dose prevalence, Measles incidence, Bayesian geostatistical modelling

Identifiers

Local EPrints ID: 472717
URI: http://eprints.soton.ac.uk/id/eprint/472717
ISSN: 0264-410X
PURE UUID: d444e590-32d6-4229-b4f2-1247f510a57f
ORCID for Justice Aheto: ORCID iD orcid.org/0000-0003-1384-2461
ORCID for Natalia Tejedor Garavito: ORCID iD orcid.org/0000-0002-1140-6263
ORCID for Amy Bonnie: ORCID iD orcid.org/0000-0002-8814-3828
ORCID for Chibuzor Christopher Nnanatu: ORCID iD orcid.org/0000-0002-5841-3700
ORCID for Andrew Tatem: ORCID iD orcid.org/0000-0002-7270-941X

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Date deposited: 15 Dec 2022 17:43
Last modified: 13 Jun 2024 02:02

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Contributors

Author: Chigozie Utazi
Author: Justice Aheto ORCID iD
Author: Adelle Wigley
Author: Amy Bonnie ORCID iD
Author: Chibuzor Christopher Nnanatu ORCID iD
Author: John Wagai
Author: Cheryl Williams
Author: Hamidreza Setayesh
Author: Andrew Tatem ORCID iD
Author: Felicity T. Cutts

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