Prevalence of symptoms of vaginal fistula in 19 sub-Saharan Africa countries: a meta-analysis of national household survey data
Bibliographic record
Abstract
BACKGROUND: Vaginal fistula is a serious medical disorder characterised by an abnormal opening between the vagina and the bladder or rectum, which results in continuous leakage of urine or stool. The burden of this disorder in sub-Saharan Africa is uncertain. We estimated the lifetime and point prevalence of symptoms of vaginal fistula in this region using national household surveys based on self-report of symptoms. METHODS: We considered all Demographic and Health Surveys (DHS) and Multiple Indicators Cluster Surveys (MICS) from sub-Saharan Africa and included data for women of reproductive age (15-49 years). We estimated lifetime prevalence and point prevalence of vaginal fistula with use of Bayesian hierarchical meta-analysis. FINDINGS: We included 19 surveys in our analysis, including 262,100 respondents. Lifetime prevalence was 3.0 cases (95% credible interval 1.3-5.5) per 1000 women of reproductive age. After imputation of missing data, point prevalence was 1.0 case (0.3-2.4) per 1000 women of reproductive age. Ethiopia had the largest number of women who presently have symptoms of vaginal fistula. INTERPRETATION: This study is the first to estimate the burden of vaginal fistula in 19 sub-Saharan Africa countries using nationally representative survey data. Point prevalence was slightly lower than previously estimated but these earlier estimates are within the prevalence's credible intervals. Although vaginal fistula is relatively rare, it is still too common in sub-Saharan Africa. FUNDING: None.
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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 | 0.019 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.033 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".