Excess deaths among adults in the state of Santa Catarina: an ecological study during the COVID-19 pandemic, Brazil, 2020-2021
Bibliographic record
Abstract
OBJECTIVE: to estimate excess deaths during the COVID-19 pandemic in the state of Santa Catarina and its macro-regions, Brazil, 2020-2021. METHODS: this was an ecological study, using data from the Mortality Information System; excess deaths in adults were calculated by the difference between the observed number of deaths and expected number of deaths, taking into account the average of deaths that occurred between 2015 and 2019; the variables "macro-region of residence", "quarter", "month", "sex" and "age group" were analyzed; data were analyzed in a descriptive manner. RESULTS: a total of 6,315 excess deaths in 2020 and 17,391 in 2021, mostly in males (57.4%) and those aged 60 years and older (74.0%); macro-regions and periods with the greatest excess deaths were those in which there were most deaths due to COVID-19; the greatest excess deaths occurred in March 2021 (n = 4,207), with a progressive decrease until the end of the year. CONCLUSION: there were excess deaths in the state of Santa Catarina and in all its macro-regions during the COVID-19 pandemic.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".