Collapse of the public health system and the emergence of new variants during the second wave of the COVID-19 pandemic in Brazil
Bibliographic record
Abstract
The worldwide spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the most severe public health crisis since the 1918 Spanish influenza pandemic. After the introduction of public health interventions aimed at reducing the number of COVID-19 cases, many countries across the world obtained success at containing the fast spread of SARS-CoV-2 during the first wave of the pandemic. However, the SARS-CoV-2 has resurged in many countries causing a even more devastating second wave. Brazil is one the most affected countries and currently is facing one of the worst public health crises in its history. Here, we discuss the unprecedented challenges faced by the Brazilian public health system in the midst of the second wave of the COVID-19 pandemic, particularly regarding the collapse of the Brazilian health system and the emergence of new variants of concern (VOCs). Finally, we suggest some insights using a one health approach that will help the country to face and overcome the current COVID-19 crisis.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 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".