P3.151 The routes of the aids and hiv infection epidemic in the state of sÃo paulo, brazil, between 2000 and 2015
Bibliographic record
Abstract
Introduction This study analysed the HIV/AIDS epidemic trends in the state of Sao Paulo, in adults, during the period of 2000 to 2015. Methods Trends study performed by polynomial regression model, with AIDS and HIV positive cases notification comparing by age group and exposure categories. The dependent variable were the annual number of cases, in each of the studied categories, and the independent variable was the time, (calendar years), concerning the study period. The goodness of fit via r2 and p<0.05 were used to determine which models and data were most appropriate. Results It was analysed 142,015 AIDS cases and 70 761 cases of HIV. The AIDS cases trends declined in the entire period, with speed=243 cases/year (p=0.001), but the HIV+ cases trends increased with speed=325 cases/year (p=0.003). From 2000 to 2007 AIDS decreased 30 cases/year (p=0.024) in the man who have sex with man (MSM) category, and only the 30–39 years group falled 26 cases/year (p=0.003). From 2007 to 2012 there was a growth of MSM with speed=116 cases/year (p<0.001) and the 20–24 years group showed the fastest growth=38 cases/year (p=0.001). From 2012 to 2015, the MSM decreased 118 cases/year (p=0.043) and the 30–39 years group showed a greater fall rate=43 cases/year (p=0.039). Among the HIV infection cases in the period 2000 to 2003, the trend was increasing among MSM with speed=201 cases/year (p<0.001) with the group 30–39 years growing faster=79 cases/year (p=0.006). Between 2003 and 2007 MSM increased 25 cases/year (p=0.048) and the age group 40–49 presented the highest velocity=8 cases/year (p=0.006). Between 2007 and 2015 the trend was increasing among MSM with speed=337 cases/year (p=0.001) and the main age group was 20–24 with speed=106 cases/year, (p=0.045). Conclusion There was a decreasing trend of AIDS cases and growth in HIV+, with expressive speed among young MSM. This analysis points to the need for discussions of unprotected sexual practices, combined prevention and other actions aimed to controlling the epidemic in greater vulnerability groups.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".