Unmet need for COVID-19 vaccination coverage in Kenya
Unmet need for COVID-19 vaccination coverage in Kenya
COVID-19 has impacted the health and livelihoods of billions of people since it emerged in 2019. Vaccination for COVID-19 is a critical intervention that is being rolled out globally to end the pandemic. Understanding the spatial inequalities in vaccination coverage and access to vaccination centres is important for planning this intervention nationally. Here, COVID-19 vaccination data, representing the number of people given at least one dose of vaccine, a list of the approved vaccination sites, population data and ancillary GIS data were used to assess vaccination coverage, using Kenya as an example. Firstly, physical access was modelled using travel time to estimate the proportion of population within 1 hour of a vaccination site. Secondly, a Bayesian conditional autoregressive (CAR) model was used to estimate the COVID-19 vaccination coverage and the same framework used to forecast coverage rates for the first quarter of 2022. Nationally, the average travel time to a designated COVID-19 vaccination site (n = 622) was 75.5 min (Range: 62.9 – 94.5 min) and over 87% of the population >18 years reside within 1 hour to a vaccination site. The COVID-19 vaccination coverage in December 2021 was 16.70% (95% CI: 16.66 – 16.74) – 4.4 million people and was forecasted to be 30.75% (95% CI: 25.04 – 36.96) – 8.1 million people by the end of March 2022. Approximately 21 million adults were still unvaccinated in December 2021 and, in the absence of accelerated vaccine uptake, over 17.2 million adults may not be vaccinated by end March 2022 nationally. Our results highlight geographic inequalities at sub-national level and are important in targeting and improving vaccination coverage in hard-to-reach populations. Similar mapping efforts could help other countries identify and increase vaccination coverage for such populations.
Bayesian conditional autoregressive, COVID-19, Spatial inequalities, Vaccination coverage
2011-2019
Muchiri, Samuel K.
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Muthee, Rose
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Kiarie, Hellen
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Sitienei, Joseph
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Agweyu, Ambrose
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Atkinson, Peter M.
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Utazi, C. Edson
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Tatem, Andrew J.
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Alegana, Victor A.
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18 March 2022
Muchiri, Samuel K.
e6686c47-e08d-44b6-bd3a-345d1c9eb471
Muthee, Rose
cf92c6f0-92b6-40f3-9d5a-acbb479239ab
Kiarie, Hellen
5822028c-abc6-4ab6-b9b2-ac705cf364e6
Sitienei, Joseph
b1421400-28b6-4ed4-9f00-84e0865130f7
Agweyu, Ambrose
5bfc69de-791c-48dc-bd91-6f1abcc52efc
Atkinson, Peter M.
96e96579-56fe-424d-a21c-17b6eed13b0b
Utazi, C. Edson
91982e3d-d79b-4e0e-ba23-7bdfa417b10b
Tatem, Andrew J.
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Alegana, Victor A.
f5bd6ab7-459e-4122-984f-2bdb5f906d82
Muchiri, Samuel K., Muthee, Rose, Kiarie, Hellen, Sitienei, Joseph, Agweyu, Ambrose, Atkinson, Peter M., Utazi, C. Edson, Tatem, Andrew J. and Alegana, Victor A.
(2022)
Unmet need for COVID-19 vaccination coverage in Kenya.
Vaccine, 40 (13), .
(doi:10.1016/j.vaccine.2022.02.035).
Abstract
COVID-19 has impacted the health and livelihoods of billions of people since it emerged in 2019. Vaccination for COVID-19 is a critical intervention that is being rolled out globally to end the pandemic. Understanding the spatial inequalities in vaccination coverage and access to vaccination centres is important for planning this intervention nationally. Here, COVID-19 vaccination data, representing the number of people given at least one dose of vaccine, a list of the approved vaccination sites, population data and ancillary GIS data were used to assess vaccination coverage, using Kenya as an example. Firstly, physical access was modelled using travel time to estimate the proportion of population within 1 hour of a vaccination site. Secondly, a Bayesian conditional autoregressive (CAR) model was used to estimate the COVID-19 vaccination coverage and the same framework used to forecast coverage rates for the first quarter of 2022. Nationally, the average travel time to a designated COVID-19 vaccination site (n = 622) was 75.5 min (Range: 62.9 – 94.5 min) and over 87% of the population >18 years reside within 1 hour to a vaccination site. The COVID-19 vaccination coverage in December 2021 was 16.70% (95% CI: 16.66 – 16.74) – 4.4 million people and was forecasted to be 30.75% (95% CI: 25.04 – 36.96) – 8.1 million people by the end of March 2022. Approximately 21 million adults were still unvaccinated in December 2021 and, in the absence of accelerated vaccine uptake, over 17.2 million adults may not be vaccinated by end March 2022 nationally. Our results highlight geographic inequalities at sub-national level and are important in targeting and improving vaccination coverage in hard-to-reach populations. Similar mapping efforts could help other countries identify and increase vaccination coverage for such populations.
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Accepted/In Press date: 7 February 2022
e-pub ahead of print date: 14 February 2022
Published date: 18 March 2022
Keywords:
Bayesian conditional autoregressive, COVID-19, Spatial inequalities, Vaccination coverage
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Local EPrints ID: 456314
URI: http://eprints.soton.ac.uk/id/eprint/456314
ISSN: 0264-410X
PURE UUID: 37a14fad-35e1-4372-b8a0-54bd7145b7a8
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Date deposited: 27 Apr 2022 02:18
Last modified: 17 Mar 2024 03:29
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Contributors
Author:
Samuel K. Muchiri
Author:
Rose Muthee
Author:
Hellen Kiarie
Author:
Joseph Sitienei
Author:
Ambrose Agweyu
Author:
Peter M. Atkinson
Author:
C. Edson Utazi
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