COVID-19 in West Africa: regional resource mobilisation and allocation in the first year of the pandemic
Bibliographic record
Abstract
The world continues to battle the ongoing COVID-19 pandemic. Whereas many countries are currently experiencing the second wave of the outbreak; Africa, despite being the last continent to be affected by the virus, has not experienced as much devastation as other continents. For example, West Africa, with a population of 367 million people, had confirmed 412 178 cases of COVID-19 with 5363 deaths as of 14 March 2021; compared with the USA which had recorded almost 30 million cases and 530 000 deaths, despite having a slightly smaller population (328 million). Several postulations have been made in an attempt to explain this phenomenon. One hypothesis is that African countries have leveraged on experiences from past epidemics to build resilience and response strategies which may be contributing to protecting the continent's health systems from being overwhelmed. This practice paper from the West African Health Organization presents experience and data from the field on how countries in the region mobilised support to address the pandemic in the first year, leveraging on systems, infrastructure, capacities developed and experiences from the 2014 Ebola virus disease outbreak.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".