The University of Southampton
University of Southampton Institutional Repository

A zero-dose vulnerability index for equity assessment and spatial prioritization in low- and middle-income countries

A zero-dose vulnerability index for equity assessment and spatial prioritization in low- and middle-income countries
A zero-dose vulnerability index for equity assessment and spatial prioritization in low- and middle-income countries

Many low- and middle-income countries (LMICs) continue to experience substantial inequities in vaccination coverage despite recent efforts to reach missed communities and reduce zero-dose prevalence. Geographic inequities in vaccination coverage are often characterized by a multiplicity of risk factors which should be operationalized through data integration to inform more effective and equitable vaccination policies and programmes. Here, we explore approaches for integrating information from multiple risk factors to create a zero-dose vulnerability index to improve the identification and prioritization of vulnerable communities and understanding of inequities in vaccination coverage. We assembled geolocated data on vaccination coverage and associated risk factors in six LMICs, focusing on the coverage of DTP1, DTP3 and MCV1 vaccines as indicators of zero dose and under-vaccination. Using geospatial modelling techniques built on a suite of geospatial covariate information, we produced 1 × 1 km and district level maps of the previously unmapped risk factors and vaccination coverage. We then integrated data from the maps of the risk factors using different approaches to construct a zero-dose vulnerability index to classify districts within the countries into different vulnerability groups, ranging from the least vulnerable (1) to the most vulnerable (5) areas. Through integration with population data, we estimated numbers of children aged under 1 living within the different vulnerability classes. Our results show substantial variation in the spatial distribution of the index, revealing the most vulnerable areas despite little variation in coverage in some cases. We found that the most distinguishing characteristics of the most vulnerable areas cut across the different subdomains (health, socioeconomic, demographic and geographic) of the risk factors included in our study. We also demonstrated that the index can be robustly estimated with fewer risk factors and without linkage to information on vaccination coverage. The index constitutes a practical and effective tool to guide targeted vaccination strategies in LMICs.

Bayesian inference, Demographic and Health Surveys, INLA-SPDE approach, Multiple Indicator Cluster Surveys, Vaccination coverage
2211-6753
Utazi, C.E.
e69ca81e-fb23-4bc1-99a5-25c9e0f4d6f9
Chan, H.M.T.
5bf76c72-ef36-45cb-990e-d6a00d8781f0
Olowe, I.
8dd36b44-77b7-4dbc-ad86-81dc51da3f9c
Wigley, A.
21b38ae2-ffd3-4d45-bf29-843e6d62807f
Tejedor-Garavito, N.
26fd242c-c882-4210-a74d-af2bb6753ee3
Cunningham, A.
d67452a2-f592-4784-80b2-1bfd8e5f76ae
Bondarenko, M.
1cbea387-2a42-4061-9713-bbfdf4d11226
Lorin, J.
f415115e-b83f-4430-a3e8-e553b8b641bf
Boyda, D.
f1044c7f-cd7b-424b-9813-52283ebb3f25
Hogan, D.
6c1b0552-bb30-445b-8928-228d94199782
Tatem, A.J.
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Utazi, C.E.
e69ca81e-fb23-4bc1-99a5-25c9e0f4d6f9
Chan, H.M.T.
5bf76c72-ef36-45cb-990e-d6a00d8781f0
Olowe, I.
8dd36b44-77b7-4dbc-ad86-81dc51da3f9c
Wigley, A.
21b38ae2-ffd3-4d45-bf29-843e6d62807f
Tejedor-Garavito, N.
26fd242c-c882-4210-a74d-af2bb6753ee3
Cunningham, A.
d67452a2-f592-4784-80b2-1bfd8e5f76ae
Bondarenko, M.
1cbea387-2a42-4061-9713-bbfdf4d11226
Lorin, J.
f415115e-b83f-4430-a3e8-e553b8b641bf
Boyda, D.
f1044c7f-cd7b-424b-9813-52283ebb3f25
Hogan, D.
6c1b0552-bb30-445b-8928-228d94199782
Tatem, A.J.
6c6de104-a5f9-46e0-bb93-a1a7c980513e

Utazi, C.E., Chan, H.M.T., Olowe, I., Wigley, A., Tejedor-Garavito, N., Cunningham, A., Bondarenko, M., Lorin, J., Boyda, D., Hogan, D. and Tatem, A.J. (2023) A zero-dose vulnerability index for equity assessment and spatial prioritization in low- and middle-income countries. Spatial Statistics, 57, [100772]. (doi:10.1016/j.spasta.2023.100772).

Record type: Article

Abstract

Many low- and middle-income countries (LMICs) continue to experience substantial inequities in vaccination coverage despite recent efforts to reach missed communities and reduce zero-dose prevalence. Geographic inequities in vaccination coverage are often characterized by a multiplicity of risk factors which should be operationalized through data integration to inform more effective and equitable vaccination policies and programmes. Here, we explore approaches for integrating information from multiple risk factors to create a zero-dose vulnerability index to improve the identification and prioritization of vulnerable communities and understanding of inequities in vaccination coverage. We assembled geolocated data on vaccination coverage and associated risk factors in six LMICs, focusing on the coverage of DTP1, DTP3 and MCV1 vaccines as indicators of zero dose and under-vaccination. Using geospatial modelling techniques built on a suite of geospatial covariate information, we produced 1 × 1 km and district level maps of the previously unmapped risk factors and vaccination coverage. We then integrated data from the maps of the risk factors using different approaches to construct a zero-dose vulnerability index to classify districts within the countries into different vulnerability groups, ranging from the least vulnerable (1) to the most vulnerable (5) areas. Through integration with population data, we estimated numbers of children aged under 1 living within the different vulnerability classes. Our results show substantial variation in the spatial distribution of the index, revealing the most vulnerable areas despite little variation in coverage in some cases. We found that the most distinguishing characteristics of the most vulnerable areas cut across the different subdomains (health, socioeconomic, demographic and geographic) of the risk factors included in our study. We also demonstrated that the index can be robustly estimated with fewer risk factors and without linkage to information on vaccination coverage. The index constitutes a practical and effective tool to guide targeted vaccination strategies in LMICs.

Text
1-s2.0-S2211675323000477-main - Version of Record
Available under License Creative Commons Attribution.
Download (3MB)

More information

Accepted/In Press date: 15 August 2023
e-pub ahead of print date: 21 August 2023
Published date: 5 September 2023
Additional Information: Funding Information: This work was supported by the Bill & Melinda Gates Foundation, United States and Gavi, the Vaccine Alliance [Grant Number INV-002397 awarded to A.J.T, C.E.U and N.T.-G.]. Publisher Copyright: © 2023 The Author(s)
Keywords: Bayesian inference, Demographic and Health Surveys, INLA-SPDE approach, Multiple Indicator Cluster Surveys, Vaccination coverage

Identifiers

Local EPrints ID: 482222
URI: http://eprints.soton.ac.uk/id/eprint/482222
ISSN: 2211-6753
PURE UUID: d5dc4b17-444e-48f7-a4d8-262f81b76710
ORCID for N. Tejedor-Garavito: ORCID iD orcid.org/0000-0002-1140-6263
ORCID for M. Bondarenko: ORCID iD orcid.org/0000-0003-4958-6551
ORCID for A.J. Tatem: ORCID iD orcid.org/0000-0002-7270-941X

Catalogue record

Date deposited: 21 Sep 2023 16:51
Last modified: 18 Mar 2024 03:32

Export record

Altmetrics

Contributors

Author: C.E. Utazi
Author: H.M.T. Chan
Author: I. Olowe
Author: A. Wigley
Author: A. Cunningham
Author: M. Bondarenko ORCID iD
Author: J. Lorin
Author: D. Boyda
Author: D. Hogan
Author: A.J. Tatem ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×