P5-S6.12 Control of sexually transmitted infections (STI) in Guyana: plan to integrate into existing programmes
Bibliographic record
Abstract
Background Over the last decade, Guyana has developed and strengthened surveillance, prevention and care and treatment for HIV. These interventions have resulted in a decline in HIV prevalence in antenatal as well as most at risk populations (MARPs defined as female sex workers, men who have sex with men (MSM), in and out of school youth, military and police). For non-HIV STI, a structured programme did not exist prior to 2005. From 2007 to 2009, the reported cases of STI increased significantly. In addition to HIV, non HIV STI has been identified as a priority for prevention and control by the National AIDS Program Secretariat (NAPS), Guyana Ministry of Health (MOH). Methods In conjunction with the Pan American Health Organisation and other international and local stakeholders, NAPS/MOH worked with local and external consultants to develop a STI strategy. Consultation meetings were held in Guyana and relevant documents were reviewed. Results A STI strategy for 2011–2020 has been developed. The strategy outlines activities that will build on existing HIV, antenatal and visualisation under acetic acid (VIA) programmes. In addition, activities have been outlined to build on existing second generation HIV surveillance initiatives currently in place in MARPs. Strategies to ramp up the provision of care and treatment for STI in existing primary care settings have also been addressed. The strategy highlights activities under five priority areas: (1) Programme Management and Coordination, (2) Prevention, (3) Laboratory, (4) Care and Treatment and (5) Surveillance. Under each priority area, broad goals, guiding principles, specific objectives, performance milestones and activities have been developed. A Monitoring and Evaluation plan will be a key part of the document to monitor progress during the strategy. The strategy will coordinate the activities of international and local agencies including non governmental and faith based organisations as well as persons from MARPs. Conclusions Guyana has developed a comprehensive 10-year plan for the prevention and control of non HIV sexually transmitted infections which will build on existing programmes for HIV, antenatal and VIA programmes.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.005 |
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".