Vaccine market and production capabilities in the Americas
Bibliographic record
Abstract
Abstract In the Americas, The United States of America, Canada, Mexico, and Brazil are the top vaccine producers and the countries with the leading infrastructure for biological manufacturing. The North American countries have the most demanding legislation regulating and controlling these pharmaceuticals' distribution and production. Some Latin American countries rank in the top 20 of worldwide vaccine manufacturers, with Cuba, Brazil, México and Colombia have a self-sufficient vaccine production of 72.7%, 54,2%; 25%; and 7.7%, respectively, of the national vaccine demand. On the other hand, the rest of Latin American countries cannot satisfy their demand for vaccines, and most of their efforts are associated with the distribution within their health systems rather than in transferring technology. Based on this literature review, the results suggest an increasing growth vaccine demand, not only for their growing populations and previously established demand but also for the recently exerted pressure due to the COVID-19 pandemic. Because the American continent has a marked inequality between the hegemonic producers of vaccines, the exporters, and those that depend heavily on importing these products, this could assert technological dependence in countries with rapid population growth and jeopardize the effectiveness of the two vaccination plans.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 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".