Unmet need for COVID-19 vaccination coverage in Kenya

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.

Keywords: Bayesian conditional autoregressive; COVID-19; Spatial inequalities; Vaccination coverage.

Fig. 1

(A) Distribution of the approved vaccination sites categorized according to their KEPH levels (n = 622). (B) Population density distribution for >18 years per 1 km². (C) Spatial accessibility to the COVID-19 vaccination sites.

Fig. 2

Proportion of population living within 1hr travel time to a COVID-19 vaccination site. The error bars represent the uncertainty intervals, derived by varying the mean speeds by ±20%. The dotted line represents the national average percentage of population living within 1 hr to a COVID-19 vaccination site.

Fig. 3

Weekly average SARS CoV-2 cases superimposed with (A) COVID-19 stringency index (NPI) and (B) the predicted (red solid line) and the forecasted (red dashed line) any dose COVID-19 vaccination coverage rates with 95% Bayesian credible intervals (shaded grey region) (pharmaceutical interventions). The black dashed lines show the beginning (1^st January 2022) and the end (31^st March 2022) of the forecast period. The red horizontal dot-dashed line indicates the 70% COVID-19 vaccination coverage required to achieve herd immunity .

Fig. 4

Modelled mean COVID-19 vaccination coverage at sub-national level; (A) before the forecast period and (B) at the end of the forecast period. The population unvaccinated (unmet need) (C) before forecast and (D) after forecast.