Research initiatives of blood services worldwide in response to the covid‐19 pandemic
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: While coronavirus (COVID-19) is not transfusion-transmitted, the impact of the global pandemic on blood services worldwide is complex. Convalescent plasma may offer treatment, but efficacy and safety are not established. Measuring seroprevalence in donors would inform public health policy. Here, we survey blood services around the world to assess the different research programmes related to COVID-19 planned or in progress. MATERIALS AND METHODS: Blood collection services were surveyed in June 2020 to determine whether they were participating in serosurveys or convalescent plasma collection and clinical trials. RESULTS: A total of 48 countries (77% of those contacted) responded. Seroprevalence studies are planned or in progress in 73% of countries surveyed and in all continents, including low- and middle-income countries. Most aimed to inform public health policy. Convalescent plasma programmes have been initiated around the globe (79% of surveyed), about three quarters as clinical trials in high-, middle- and low-income countries. CONCLUSION: Blood services around the world have drawn upon their operational capacity to provide much-needed seroprevalence data to inform public health. They have rapidly implemented preparation of potential treatment when few treatments are available and mostly as clinical trials. At the same time, they must continue to provide blood products for recipients despite challenges of working in a state of emergency. It is important to track and coordinate research efforts across jurisdictions to gain a composite evidence-based view that will influence future practice and preparative strategies.
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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 | 0.036 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".