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Excess deaths among adults in the state of Santa Catarina: an ecological study during the COVID-19 pandemic, Brazil, 2020-2021

2023· article· en· W4384303622 on OpenAlex
Rebeca Heyse Holzbach, Geferson Gustavo Wagner Mota da Silva, Jean Carlos Bianchi, Danúbia Hillesheim, Fabrício Augusto Menegon, Ana Luiza Curi Hallal

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEpidemiologia e Serviços de Saúde · 2023
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsnot available
Fundersnot available
KeywordsDemographyPandemicExcess mortalityResidenceCoronavirus disease 2019 (COVID-19)Quarter (Canadian coin)Ecological studyGeographySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)MacroMedicineMortality ratePopulationDiseaseInfectious disease (medical specialty)Archaeology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.111
GPT teacher head0.436
Teacher spread0.326 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it