Measuring behavioral and social drivers of COVID-19 vaccination in health workers in Eastern and Southern Africa
Bibliographic record
Abstract
BACKGROUND: In 2021, twenty out of twenty-one countries in the Eastern and Southern Africa (ESA) region introduced COVID-19 vaccines. With variable willingness to uptake vaccines across countries, the aim of the present study was to better understand factors that impact behavioral and social drivers of vaccination (BeSD). Using the theory-based "increasing vaccination model", the drivers Thinking & Feeling, Social Processes, Motivation, and Practical Issues were adapted to the COVID-19 context and utilized in a cross-country assessment. METHODS: Data was collected on 27.240 health workers in Kenya, Malawi, Mozambique, South Africa and South Sudan. This was done by administering a survey of seven target questions via the UNICEF Internet of Good Things (IoGT) online platform between February and August 2021. RESULTS: Findings showed a gap between perceived importance and trust in vaccines: Most health workers thought Covid-19 vaccination was very important for their health, while less than 30% trusted it very much. The pro-vaccination social and work norm was not well established since almost 66% of all respondents would take the vaccine if recommended to them, but only 49% thought most adults would, and only 48% thought their co-workers would. Access was highlighted as a crucial barrier, with less than a quarter reporting that accessing vaccination services for themselves would be very easy. Women exhibited slightly lower scores than men across the board. When testing the associations between drivers in Kenya and South Africa, it appears that when target interventions are developed for specific age groups, social norms become the main drivers of intention to get vaccinated. CONCLUSIONS: The present study revealed various key relations with demographic variables that would help immunization programmes and implementing partners to develop targeted interventions. First, there is a serious gap between perceived importance of COVID-19 vaccines and how much trust people in them. Second, problems with access are still rather serious and solving this would strongly benefit those who demand a vaccine, Third, the role of social norms is the most important predictor of willingness when considering age differences.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".