A holistic approach to address female genital schistosomiasis in Ghana and Madagascar: the FGS Accelerated Scale Together Package
Bibliographic record
Abstract
Women and girls who have been infected with the blood fluke Schistosoma haematobium can experience the chronic form of urogenital schistosomiasis, called female genital schistosomiasis (FGS). Some FGS symptoms resemble sexually transmitted infections. As a result, women and girls seeking treatment are often misdiagnosed and stigmatized. The FGS Accelerated Scale Together (FAST) Package project implemented a holistic approach to address FGS combining proven interventions in training, mass drug administration, diagnosis, and treatment as well as community awareness to address FGS in four selected districts in Ghana and Madagascar. The FAST Package was supported by an FGS National Committee who provided guidance on integration at the national level. Using an implementation research design, researchers worked closely with government counterparts in the programs for neglected tropical diseases in both countries. Baseline cross-sectional surveys and qualitative methodologies collected information on schistosomiasis and FGS awareness, experience with health seeking behaviors and knowledge of schistosomiasis prevention amongst community members and teachers. FAST Package interventions included healthcare provider training delivered in online and in person formats; development of an Educators’ booklet to support schistosomiasis/FGS awareness creation among teachers, healthcare providers and community members; suspected FGS case detection; and advocacy for the provision of praziquantel in the primary health care system. Endline results included a cross-sectional survey and qualitative methodologies amongst community members and teachers, including Photovoice for women of reproductive health age exposed to FGS. This paper presents a description of the FAST Package project, the value of its holistic approach, and selected results from both countries. It discusses the lessons learnt highlighting some of the challenges and opportunities for integration within the health system.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".