Aspectos epidemiológicos do vírus Oropouche (Orthobunyavirus) na América do Sul: uma revisão sistemática
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.
Bibliographic record
Abstract
Introduction: The Oropouche virus (OROV) is an arbovirus that belongs to the genus Orthobunyavirus and family Peribunyaviridae, responsible for causing Oropouche fever (OF) in humans. The clinical diagnosis of is doubtful due to the non-specificity of the symptoms, which can lead to a mistaken diagnosis of other arboviruses. Thus, the survey of epidemiological data on the occurrence of has been a major challenge for public health authorities, especially in of South America. Aim: To determine the general exposure rate of OROV in Brazil and other countries in South America by a systematic review. An article search was carried out in the Pubmed/ Medline, Scopus, Cochrane, Lilacs, Electronic Scientific Online Library (SciELO) and Virtual Health Library (VHL) databases. Results:18 studies were selected as eligible to compose this review on epidemiological aspects of OROV. The studies were published from 1989 to 2020. Most studies were carried out in Brazil (12/18; 66.66%) and Peru (5/18; 27.77%), only one study collected samples from Peru, Ecuador, Bolivia and Paraguay. The test for the OROV was realized mainly by serological analysis. Of the 8005 samples analyzed, 1570 tested positive for the presence of OROV thus accounting a general exposure rate in South America of 19.61%. Brazil was responsible for more than half of the cases of OROV identified in South America (855/1570; 54.46%), however Peru has the highest rate of exposure to the virus (23.43% of frequency in Peru vs. 16.77% of frequency in Brazil). Conclusion: OROV stands out as an important public health problem in Amazonian countries in South America.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 it