Mapping regional funding for COVID-19 research in the Asia-Pacific region
Bibliographic record
Abstract
INTRODUCTION: The Global Research Collaboration for Infectious Disease Preparedness (GloPID-R) is a network of funders supporting research on infectious diseases of epidemic/pandemic potential. GloPID-R is establishing regional hubs to strengthen stakeholder engagement particularly among low-income and middle-income countries. The first pilot hub, led from Republic of Korea (South Korea), has been launched in the Asia-Pacific region, a region highly prone to outbreaks of emerging infectious diseases. We present findings of mapping research undertaken in support of the hub's development. METHODS: We analysed five COVID-19 research databases in September 2022 to identify research funders and intermediary funding sources supporting research in infectious diseases in the Asia-Pacific region. This was complemented with an in-depth analysis of the UK Collaborative on Development Research (UKCDR) and GloPID-R COVID-19 Research Project Tracker to assess the alignment of funded projects in the region to the WHO COVID-19 research priorities. RESULTS: We identified 453 funders and funding sources supporting COVID-19 research in the Asia-Pacific Region including public, private and philanthropic organisations and universities. However, these organisations were clustered in few countries in the region. The in-depth analysis of the UKCDR and GloPID-R COVID-19 Research project Tracker found limited research involving Asia-Pacific countries with the 117 funders supporting these projects investing at least US$604m in COVID-19 research in the region. Social Sciences was the dominant theme on which funded projects focused whereas the priority areas with the least number of projects were research on 'animal and environmental health' and 'ethics considerations for research'. CONCLUSION: Our analyses show the diversity of funding sources for research on infectious diseases in the Asia-Pacific region. Engagement between multiple actors in the health research system is likely to promote enhanced coordination for greater research impact. GloPID-R's Asia-Pacific regional hub aims to support activities for the enhancement of preparedness for outbreaks of emerging infectious diseases in the region.
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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 | 0.018 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.014 | 0.041 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".