Epidemiology of sexually transmitted infections: trends among patients screened for sexually transmitted infections in rwandan health facilities 2014–2020
Bibliographic record
Abstract
BACKGROUND: Sexually Transmitted Infections (STIs) are of great global health concern. Currently, there are limited epidemiological data characterizing STIs in the general population in Rwanda. We assessed the national and regional epidemiology of STIs in Rwanda from 2014-2020 among patients syndromically screened for STIs in all health facilities in Rwanda. METHODS: This is a retrospective analysis of the trend of STIs epidemiology among screened patients at all health facilities in Rwanda using data from the Health Management Information System (HMIS) reporting. Adult patients (15 years and over) screened for STIs between July 2014 and June 2020 were included in the analysis. Outcomes of interest were the number of individuals screened for STIs and individuals diagnosed with at least one STI with a syndromic approach only or plus a test together. RESULTS: Overall, the number of individuals screened for STIs over the study period was 5.3 million (M) in 2014-2015, 6.6 M in 2015-2016, 6.3 M in 2016-2017, 6.7 M in 2017-2018, 6.2 M in 2018-2019, and 4.9 M in 2019-2020. There was a modest increase in the number of individuals diagnosed and treated for STIs from 139,357 in 2014-15 to 202,294 (45% increase) in 2019-2020. At the national level, the prevalence of STI syndromes amongst individuals screened at health facilities in Rwanda varied between 2.37% to 4.16% during the study period. Among the provinces, Kigali city had the highest prevalence for the whole 6 years ranging from 3.46% (95%CI: 3.41, 3.51) in 2014-2015 to 8.23% (95%CI: 8.15, 8.31) in 2019-2020. CONCLUSION: From 2014 to 2020, the number of patients screened for STI syndromes in Rwanda varied between 4.9 M and 6.7 M. However, the prevalence of STIs among screened patients increased considerably over time, which could be associated with public awareness and improved data recording. The highest prevalence of all STIs was observed in urban areas and near borders, and private clinics reported more cases, suggesting the need to improve awareness in these settings and increase confidentiality and trust in public health clinics.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".