Funding and COVID-19 research in Africa: two years on, are the research needs of Africa being met?
Bibliographic record
Abstract
BACKGROUND: The Coronavirus disease 2019 (COVID-19) pandemic caused significantly lower reported mortalities on the African continent as compared to other regions. Yet, many countries on the continent are still contending with the devastating economic, social and indirect health impacts. African researchers and policy makers have identified research priority areas which take cognisance of the unique research needs of African countries. A baseline assessment of the alignment of funded research in Africa to these priorities and World Health Organization's COVID-19 research priorities was undertaken in July, 2020. We present a two-year update to this analysis of funded COVID-19 research in Africa. METHODS: Data captured in the UK Collaborative on Development Research and Global Research Collaboration for Infectious Disease Preparedness COVID-19 Research Project Tracker as of 15th July, 2022 was analysed. An additional analysis of institutions receiving funding for COVID-19 research is presented. We also analysed the change in funding for COVID-19 research in Africa since July, 2020. RESULTS: The limited COVID-19 research identified in Africa early in the pandemic has persisted over the subsequent two-year period assessed. When number of projects are considered, governmental funders based in Europe and United States supported the most research. Only nine research funders based in Africa were identified. A number of partnerships between African institutions and institutions based on other continents were identified, however, most research projects were undertaken in research institutions based in Africa only. Our findings highlight the relevance of the WHO research priorities for the pandemic response in Africa. Many research questions raised by African researchers remain unaddressed, among which are questions related to clinical management of COVID-19 infections in Africa. CONCLUSIONS: Two years after the identification of Africa's COVID-19 research priorities, the findings suggest a missed opportunity in new research funding to answer pertinent questions for the pandemic response in Africa.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.048 | 0.146 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.016 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".