Unmet need for COVID-19 vaccination coverage in Kenya

Muchiri, Samuel K.; Muthee, Rose; Kiarie, Hellen; Sitienei, Joseph; Agweyu, Ambrose; Atkinson, Peter M.; Utazi, C. Edson; Tatem, Andrew J.; Alegana, Victor

doi:10.1016/j.vaccine.2022.02.035

Cited by 20 publications

(20 citation statements)

References 54 publications

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“…These included procedures such as standardisation of continuous covariates using the z-transform15 22 23 and logarithmic transformation of variables that were not normally distributed 15 23. In two studies, georeferenced data were resampled at appropriate spatial resolutions,23 24 for example, 1 km by 1 km spatial resolution (table 2).…”

Section: Resultsmentioning

confidence: 99%

“…Three independent studies used multiple formulations of spatial-temporal conditional autoregressive models implemented within a Bayesian framework incorporating unmeasured factors of COVID-19 and the subtle influence of time and space. Specifically, a discrete spatial binomial regression model was used to model vaccination coverage subnationally, and semiparametric spatial-temporal models were used to model the monthly confirmed COVID-19 cases 21 27 28. Spatial regression models were also used to model spatial dependent data.…”

Section: Resultsmentioning

confidence: 99%

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Spatial and spatio-temporal epidemiological approaches to inform COVID-19 surveillance and control: a systematic review of statistical and modelling methods in Africa

et al. 2023

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ObjectiveVarious studies have been published to better understand the underlying spatial and temporal dynamics of COVID-19. This review sought to identify different spatial and spatio-temporal modelling methods that have been applied to COVID-19 and examine influential covariates that have been reportedly associated with its risk in Africa.DesignSystematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.Data sourcesThematically mined keywords were used to identify refereed studies conducted between January 2020 and February 2022 from the following databases: PubMed, Scopus, MEDLINE via Proquest, CINHAL via EBSCOhost and Coronavirus Research Database via ProQuest. A manual search through the reference list of studies was also conducted.Eligibility criteria for selecting studiesPeer-reviewed studies that demonstrated the application of spatial and temporal approaches to COVID-19 outcomes.Data extraction and synthesisA standardised extraction form based on critical appraisal and data extraction for systematic reviews of prediction modelling studies checklist was used to extract the meta-data of the included studies. A validated scoring criterion was used to assess studies based on their methodological relevance and quality.ResultsAmong 2065 hits in five databases, title and abstract screening yielded 827 studies of which 22 were synthesised and qualitatively analysed. The most common socioeconomic variable was population density. HIV prevalence was the most common epidemiological indicator, while temperature was the most common environmental indicator. Thirteen studies (59%) implemented diverse formulations of spatial and spatio-temporal models incorporating unmeasured factors of COVID-19 and the subtle influence of time and space. Cluster analyses were used across seven studies (32%) to explore COVID-19 variation and determine whether observed patterns were random.ConclusionCOVID-19 modelling in Africa is still in its infancy, and a range of spatial and spatio-temporal methods have been employed across diverse settings. Strengthening routine data systems remains critical for generating estimates and understanding factors that drive spatial variation in vulnerable populations and temporal variation in pandemic progression.PROSPERO registration numberCRD42021279767.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Spatial and spatio-temporal epidemiological approaches to inform COVID-19 surveillance and control: a systematic review of statistical and modelling methods in Africa

et al. 2023

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“…In Kenya, vaccination uptake is far lower than that observed in other countries, and it continues to be a serious problem that necessitates attention 15,16 . It is critical to understand the underlying reasons and factors for the hesitancy and apprehension of individuals from uptaking these approved vaccines.…”

Section: Coronavirus Disease 2019 (Covid-19mentioning

confidence: 99%

An empirical assessment of the factors influencing acceptance of COVID-19 vaccine uptake between Kenyan and Hungarian residing populations: A cross-sectional study

Macharia

Gakenye

Rozmann

et al. 2022

Sci Rep

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The development of effective, safe, and acceptable vaccines is a long process. COVID-19 vaccine hesitancy continues to elicit mixed reactions among different quarters despite numerous evidence of their effectiveness. This study aimed to determine the availability and acceptance rates of SARS-CoV-2 vaccines, among Kenyan and Hungarian residing populations and the underlying reasons contributing to the hesitancy of uptake. A non-probability, snowball sampling design was employed, and a survey questionnaire tool link was expeditiously disseminated. Data were carefully analyzed descriptively. Demographic variables, COVID-19 awareness, possible exposure, reasons associated with hesitancy in taking up a vaccine, choice of a vaccine, and availability of vaccines among other important variables were tested to explore their associations with vaccine acceptance rates between the two distinct countries. A total of 1960 participants were successfully enrolled in the research study, while 67 participants were excluded based on the inclusion criterion set. There was, however, no significant difference in COVID-19 public awareness between the Kenyan and Hungarian-residing participants, p = 0.300. Of the respondents, 62.4% were willing and ready to receive vaccines against COVID-19 disease. There was a significant difference (p = 0.014) between the Kenyan and Hungarian-residing respondents concerning vaccine uptake and acceptance rates. The vaccine acceptance rates in Hungary were higher than in Kenya, with mean = 0.27, SD = 0.446, S. E = 0.045 for the Hungarian population sample and mean = 0.40, SD = 0.492, S. E = 0.026, for the Kenyan sample respectively. Concerning gender and vaccine acceptance, there was a notable significant difference between males and females, p = 0.001, where the mean for males and females were 0.29 and 0.46 respectively. Acceptance rates among males were higher than among females. The functions of One-Way ANOVA and Chi-square were used to establish any significant differences and associations between means and variables respectively. Concerns regarding the safety, efficacy, and accuracy of information about the developed vaccines are significant factors that must be promptly addressed, to arrest crises revolving around COVID-19 vaccine hesitancy, especially in Kenya and among females in both populations, where acceptance rates were lower. Expansion of the screening program to incorporate antibody (serology) tests, is also highly recommended in the present circumstance. Equitable distribution of vaccines globally should be encouraged and promoted to adequately cover low- and middle-income countries. To enhance effective combat on vaccination hesitancy and apprehension in different countries, mitigation techniques unique to those countries must be adopted.

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“…The data used in this analysis were taken from the daily press releases on the Factors affecting the vaccination programme in Kenya include: i) funding, ii) the availability of vaccines, iii) storage requirements, iv) vaccine hesitancy among the population [22] and geographical inequalities in accessing vaccines in hardto-reach areas [24]. The government aims to vaccinate 15.91 million people by June 2023 in a 3-phased roll-out approach initially targeting 1.25 million people by June 2021 in phase one.…”

Section: Covid-19 Vaccination Analysis For Kenyamentioning

confidence: 99%

Modelling the impact of vaccination on the COVID-19 pandemic in African countries

Mathebula¹,

Amankwah²,

Amouzouvi³

et al. 2022

Preprint

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The rapid development of vaccines to combat COVID-19 is a great scientific achievement. In addition to non-pharmaceutical measures put in place to contain of the pandemic, pharmacological measures have been incorporated in the battle against the SARS-CoV-2, especially with the commencement of vaccination in early December 2020. This study used the SIDARTHE-V model, i.e.an extension of the SIDARTHE model with the impact of vaccination roll outs.We assessed the potential impact of vaccination in reducing the severity (deadly nature) of the virus in African countries. Model parameters were extracted by fitting simultaneously the COVID-19 cumulative data of active cases, recoveries, deaths and full vaccinations reported by the governments of Ghana, Kenya,

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Unmet need for COVID-19 vaccination coverage in Kenya

Cited by 20 publications

References 54 publications

Spatial and spatio-temporal epidemiological approaches to inform COVID-19 surveillance and control: a systematic review of statistical and modelling methods in Africa

Spatial and spatio-temporal epidemiological approaches to inform COVID-19 surveillance and control: a systematic review of statistical and modelling methods in Africa

An empirical assessment of the factors influencing acceptance of COVID-19 vaccine uptake between Kenyan and Hungarian residing populations: A cross-sectional study

Modelling the impact of vaccination on the COVID-19 pandemic in African countries

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