Defunciones por COVID-19: distribución por edad y universalidad de la cobertura médica en 22 países
Bibliographic record
Abstract
OBJECTIVE: Relate standardized age distribution of COVID-19 deaths in 22 countries in the Americas and Europe to different indicators of population characteristics and health systems. METHODS: Distributions of COVID-19 deaths by age group in 22 countries of the Americas and Europe were standardized based on the age pyramid of the world's population. Correlations were calculated between the standardized proportion of people aged <60 years among the deceased and each of six indicators. RESULTS: Standardization based on the world age pyramid revealed considerable differences in age distribution among countries; the proportion of people aged <60 years was higher in Latin America and the United States than in Canada or Western Europe. The standardized proportion of people aged <60 years among persons who died of COVID-19 is strongly correlated to the existence of universal quality medical coverage (r=-0.92, p<0.01). This relationship remained significant after being adjusted for the other indicators. CONCLUSION: We propose that weaknesses in medical coverage of the population may have created higher case-fatality in populations aged <60 years in Latin America and the United States.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".