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Prevalence and individual level enablers and barriers for COVID-19 vaccine uptake among adult tuberculosis patients attending selected clinics in Nairobi County, Kenya

Cite this dataset

Boru, Waqo; Makalliwa, George; Musita, Caroline (2024). Prevalence and individual level enablers and barriers for COVID-19 vaccine uptake among adult tuberculosis patients attending selected clinics in Nairobi County, Kenya [Dataset]. Dryad. https://doi.org/10.5061/dryad.zcrjdfnms

Abstract

Although vaccination is a cost-effective, equitable, and impactful public health intervention in curbing the spread of infectious disease, low uptake is a significant concern, especially among high-risk population groups. Nearly half of the population is unvaccinated in Nairobi, yet there is a shortage of vaccination information on vulnerable tuberculosis (TB) patients. The interplay of factors influences uptake, and protecting this vulnerable group and the general population from severe disease, hospitalization, and deaths is worthy. The purpose of this study is to determine the prevalence and individual-level enablers and barriers to COVID-19 vaccine uptake among adult TB patients attending selected clinics in Nairobi County, Kenya. This cross-sectional mixed-method study was conducted at TB clinics across six sub-counties in Nairobi County. It included 388 participants sampled from each clinic’s TB register. Quantitative data was collected using a questionnaire, and qualitative data was collected through key informant interviews and focus group discussions. Quantitative data was analyzed using descriptive statistics (frequencies and percentages for categorical variables and mean standard deviation for continuous variables) and inferential statistics (logistic regression). Qualitative data was analyzed through deductive coding and thematic analysis. The prevalence of COVID-19 vaccination was 46.1%, with 38.1% receiving complete vaccination. Mistrust in vaccine management (adjusted odds ratio (aOR)= 0.075, 95% confidence interval (CI): 0.025-0.229, p <0.001) was a significant barrier to COVID-19 vaccine uptake. Perceived covid-19 susceptibility (aOR = 2.901, 95% CI: 1.258-6.688, p = 0.012) and perceived covid-19 seriousness (aOR = 3.294, 95% CI: 1.130-9.604, p = 0.029) were significant enablers of COVID-19 vaccine uptake. Qualitative themes related to individual-level barriers and enablers of COVID-19 vaccine uptake were fear of side effects, stigma, myths, and mistrust in the messaging for barriers and desire to protect others and risk perception as enablers. The study revealed critical individual-level factors related to COVID-19 vaccine uptake.

README: Prevalence and individual level enablers and barriers for COVID-19 vaccine uptake among adult tuberculosis patients attending selected clinics in Nairobi County, Kenya


https://doi.org/10.5061/dryad.zcrjdfnms

The main parts of the data

  • General information including Questionnaire number, date of interview, name of interviewer, facility name, sub-county name, facility level, and facility type
  • Socio-demographic factors like gender, employment status, and level of education
  • Vaccination detail (heard of vaccine, trusted source, tested for COVID-19, hospitalized and received any dose, how many doses, type of vaccine, and status of vaccination)
  • Individual-level factors and uptake of covid-19 vaccine (fear of side effects, risk perception, protection of others, etc.)
  • Health facility level factors and uptake of COVID-19 vaccination (supply chain, accessibility, way government handled control measures)
Data
Value Label
What_is_your_gender 1 Female
2 Male
What_is_your_hig_t_level_of_education 1 No Formal
2 Primary
3 Secondary
4 Tertiary
What_is_your_employment_st 1 Unemployed
2 Self-employed
3 Formal Employment
Have_you_heard_about_Covid_vaccination 1 No
2 Yes
Ever_been_Diagnosed_of_Covid_19_disease 1 Yes
2 No
Ever_been_Hospitalized_for_Covid_19 1 Yes
2 No
What_do_you_con_9_Vaccination_status 1 Not Vaccinated
2 Partially Vaccinated
3 Fully Vaccinated
QB1_Extent_of_concern_with_side_effects_fears 1 Not at All
2 Small Extent
3 Large Extent
QB2_Extent_myths_have_influence_Vaccintion_decision 1 Not at All
2 Small Extent
3 Large Extent
QB3_To_what_extent_h_on_COVID_19_vaccine 1 Not at All
2 Small Extent
3 Large Extent
Vaccine_Mistrust 1 Not at All
2 Small Extent
3 Large Extent
Worries_over_Unforeseen_side_effects 1 Not at All
2 Small Extent
3 Large Extent
Concerns_about_commercial_profiteering_of_vaccines 1 Not at All
2 Small Extent
3 Large Extent
Preference_for_natural_immunity 1 Not at All
2 Small Extent
3 Large Extent
Positive_attitudes_towards_alternative_medicine 1 Not at All
2 Small Extent
3 Large Extent
Mistrust_in_government_management_of_COVID19 1 Not at All
2 Small Extent
3 Large Extent
QB5_Opinion_to_protect_others_influence_Vaccination 1 Not at All
2 Small Extent
3 Large Extent
Perceived_susceptibility_to_infectious_diseases 1 Not at All
2 Small Extent
3 Large Extent
Perceived_seriousness_of_Covid19 1 Not at All
2 Small Extent
3 Large Extent
Perceived_likelihood_of_more_COVID19_waves 1 Not at All
2 Small Extent
3 Large Extent
Tested_positive_for_COVID19 1 Not at All
2 Small Extent
3 Large Extent
Someone_close_tested_Positive_for_covid19 1 Not at All
2 Small Extent
3 Large Extent
Feeling_TB_increase_Covid19_risks 1 Not at All
2 Small Extent
3 Large Extent
Variety_of_Vaccines_available 1 Not at All
2 Small Extent
3 Large Extent
Preferred_vaccine_type 1 Not at All
2 Small Extent
3 Large Extent
Opening_hours_of_Vaccination_center 1 Not at All
2 Small Extent
3 Large Extent
QC2_Extent_HCP_Influeneced_decision_on_COVID_19_vaccine 1 Always Referred
2 Decline Referral
3 Never Referred
QC3_Extent_distance_to_vaccination 1 Not at All
2 Small Extent
3 Large Extent
Awaiting 1 Not at All
2 Small Extent
3 Large Extent
Requirements_before_registration 1 Not at All
2 Small Extent
3 Large Extent
Privacy_and_confidentiality 1 Not at All
2 Small Extent
3 Large Extent
Health_talks_before_vaccination 1 Not at All
2 Small Extent
3 Large Extent
Post_vaccination_observations 1 Not at All
2 Small Extent
3 Large Extent
Reassurance_of_Vaccine_importance 1 Not at All
2 Small Extent
3 Large Extent
Consistent_andaccurate_reporting_of_vaccine_safety 1 Not at All
2 Small Extent
3 Large Extent
Emphasis_on_social_benefits 1 Not at All
2 Small Extent
3 Large Extent
Communicating_and_education_of_public_on_Covid19 1 Not at All
2 Small Extent
3 Large Extent
Mandatory_prove_of_certifiacte_at_workORTravel 1 Not at All
2 Small Extent
3 Large Extent
Curfews_and_lockdown 1 Not at All
2 Small Extent
3 Large Extent
Closure_of_hotels_and_bars 1 Not at All
2 Small Extent
3 Large Extent
Isolation_and_quarantine 1 Not at All
2 Small Extent
3 Large Extent
Burials_by_government_personnel 1 Not at All
2 Small Extent
3 Large Extent

Note that columns BB through BK (labeled _id to _index) are data from Kobocollects tools which indicate that information was submitted by various research assistants from different study sites and phones.

  • id and uiid- the specific number generated by Kobocollect for specific senders (research assistants)
  • submission time- time data submitted to Kobo collect
  • validation status- whether data was validated by the investigator
  • submitted by- a research assistant
  • version, tags, and index- information generated by Kobo collect tool per submission

Sharing/Access information

NA

Methods

Design and setting

The study was an analytical cross-sectional study based on a mixed method (quantitative and qualitative) approach. Research assistants started with collecting quantitative data and later assisted investigators in conducting the interviews. The study was conducted at six sites in Nairobi County, Kenya. 

Sample and sampling

The study targeted adult TB patients receiving treatment between certain months in 2023, EPI logisticians, and TB coordinators. Those eligible consented participants were helped to fill out the electronic questionnaires and focus group discussions (FGD) with different participants later. The EPI logisticians and TB coordinators were the main targets for key informant interviews. The study excluded newly diagnosed TB patients or those initiated on TB treatment on the day of data collection, patients who refused or were unable to state their vaccination status, and patients who were too unwell to participate. The Cochran formula was used to calculate the sample size. Proportion sampling (PPS) was used to allocate proportions to health facilities in Nairobi County. Purposive sampling was employed to identify facilities with high TB patient numbers across the six sub-counties. Proportion sampling (PPS) was used to allocate proportions to each health facility. Simple random sampling was used to select participants for the FGDs, and purposive sampling for the Key Informant Interview (KII).

Data collection tools

A semi-structured electronic questionnaire was used to collect quantitative data. It had sections A (social demographic information and vaccination details) and B (individual-level factors and COVID-19 vaccine uptake). Pre-testing of the tool was done using 12 TB patients at [redacted] which assisted in the re-ordering of questions, replacement of ambiguous words, and kobo installations on research assistants' phones. This site had population characteristics similar to those of the study sites. A KII guide and an FGD guide were used to collect qualitative data. Both guides have open-ended questions focusing on themes related to the study objectives.

Data collection

Eight research assistants administered the semi-structured electronic questionnaire face-to-face with participants during their clinic visits. Two research assistants were allocated to [redacted] and [redacted] because of the number of participants, and one research assistant was assigned to the other four facilities. Participants provided informed consent before answering the questionnaire. Each research assistant had their smartphone with the questionnaire accessed via the Kobo collect application and responses were entered as provided by the participants. Six KIIs were conducted with managers and leaders in charge of the selected TB clinics, and six FGDs were held with adult TB patients from the six TB clinics. A series of open-ended questions guided the KIIs and FGDs. The interviews and FDGs took between 20-60 minutes and were audio-recorded. The verbatim recordings were manually transcribed and organized for a thematic analysis approach. The results of the interviews were triangulated with quantitative data.

Funding

Jomo Kenyatta University of Agriculture and Technology, Award: CSA2020E-3129-SCEPRESSA, SCEPRESSA PROJECT