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Record W4416342274 · doi:10.3389/frhs.2025.1609056

A qualitative analysis exploring barriers and enablers to distribution, delivery, and access to COVID-19 vaccines in Botswana

2025· article· en· W4416342274 on OpenAlexafffund
John Thato Tlhakanelo, John E. Ataguba, Vincent Pagiwa, Nankie Ramabu, Khutsafalo Kadimo, Grace Njeri Muriithi, Daniel Malik Achala, Elizabeth Naa Adukwei Adote, Chinyere Mbachu, Senait Alemayehu Beshah, Nyasha Masuka, Chijioke O. Nwosu, James Akazili, Chikezie Ifeanyi, Dintle Molosiwa

Bibliographic record

VenueFrontiers in Health Services · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsUniversity of Manitoba
FundersInternational Development Research Centre
KeywordsQualitative researchPopulationDiversity (politics)Qualitative analysisFocus groupUniversal design

Abstract

fetched live from OpenAlex

Introduction: The COVID-19 pandemic highlighted pre-existing weaknesses, revealing deep-rooted issues in infrastructure, access, and resource allocation that have long impeded African countries' ability to effectively meet population health needs. It also became evident during the pandemic that there were discrepancies in how vaccines were distributed, delivered and accessed in these countries. We aimed to identify vaccine distribution, service delivery processes and related barriers in Botswana to contextually explore practices that either enhance or hinder access and equity in vaccine distribution and delivery. Methods: We conducted in-depth interviews, using a semi-structured interview guide, with a purposive sample of 18 key informants, including public health sector officials, non-state actors, policy makers, regulatory bodies and other stakeholders. Interviews were audio-recorded and transcribed verbatim. Thematic analysis was conducted following a deductive approach according to the six-step analysis framework by Braun and Clarke: (i) familiarization with the data; (ii) generation of initial codes; (iii) searching for themes; (iv) reviewing themes; (v) refining and naming themes; and finally, (vi) producing the report. Steps i-iii were conducted by two researchers. Attention was given to aspects of credibility, dependability, and transferability of the findings through key strategies, including team data review, coding, consensus on themes and review of both secondary and grey literature on vaccine roll-out in the country. Results: Seven primary themes emerged from the findings. COVID-19 vaccine distribution and delivery in Botswana followed the existing primary health care system structures for routine vaccine delivery. Traditional mechanisms such as static public health facilities, private facilities, outreach campaigns, and mobile stops, were augmented through different roles played by stakeholders in the private sector, civil society organizations and non-governmental organizations. Religious and cultural norms were reported to affect vaccine uptake centered around smaller population groups that are historically known to be anti-vaccines. There is no deliberate gender and the disabled population programming for vaccine distribution and delivery in Botswana. The private sector improved access to vaccines by supporting supply chain logistics with transportation, especially to hard-to-reach areas. Discussions: Achieving equitable vaccine access involves not only logistical and infrastructural considerations, but also coordination and collaboration across several sectors, enhancing gender diversity and inclusivity in planning, coordination, and decision making and implementation of strategies tailored to the needs of a wide range of vulnerable population groups.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.372
Threshold uncertainty score0.909

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.050
GPT teacher head0.416
Teacher spread0.366 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

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