Tracking the uptake and trajectory of COVID-19 vaccination coverage in 15 West African countries: an interim analysis
Bibliographic record
Abstract
The African Union Bureau of Heads of State and Government endorsed the COVID-19 Vaccine Development and Access Strategy to vaccinate at least 60% of each country's population with a safe and efficacious vaccine by 2022, to achieve the population-level immunity needed to bring the pandemic under control. Using publicly available, country-level population estimates and COVID-19 vaccination data, we provide unique insights into the uptake trends of COVID-19 vaccinations in the 15 countries that comprise the Economic Community of West Africa States (ECOWAS). Based on the vaccination rates in the ECOWAS region after three months of commencing COVID-19 vaccinations, we provide a projection of the trajectory and speed of vaccination needed to achieve a COVID-19 vaccination coverage rate of at least 60% of the total ECOWAS population. After three months of the deployment of COVID-19 vaccines across the ECOWAS countries, only 0.27% of the region's total population had been fully vaccinated. If ECOWAS countries follow this trajectory, the sub-region will have less than 1.6% of the total population fully vaccinated after 18 months of vaccine deployment. Our projection shows that to achieve a COVID-19 vaccination coverage of at least 60% of the total population in the ECOWAS sub-region after 9, 12 and 18 months of vaccine deployment; the speed of vaccination must be increased to 10, 7 and 4 times the current trajectory, respectively. West African governments must deploy contextually relevant and culturally acceptable strategies for COVID-19 vaccine procurements, distributions and implementations in order to achieve reasonable coverage and save lives, sooner rather than later.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| 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".