The risk and associated control problems of Human African Trypanosomosis (HAT) in the endemic foci of Greater Equatoria Region, South Sudan
Bibliographic record
Abstract
This study aims to analyze, map, and identify the prevalence of, service provision for, and risk distribution and control for Human African Trypanosomosis (HAT), or sleeping sickness, in the endemic areas of Greater Equatoria Region (GER), including Eastern, Central, and Western Equatoria States of South Sudan. Passive and active screening data, detection data, and existing facilities and centers for sleeping sickness were used to assess the prevalence, screening coverage, and overall risk in the region for the 2016–2018 period. In addition, historical literature and surveillance information were used. The results show that 0.43% (N = 14,552) of the total at-risk population (N = 3,399,400) of GER were subjected to passive or active screening for Gambian HAT (gHAT), which showed an infection rate of 0.30%. Out of the total area of 196,211 km2, 58.77% of the region (115,311 km2) was found to be endemic to HAT. The population remains at high or very high risk for the disease in Western Equatoria State due to a number of active historic gHAT foci. With relative peace currently prevailing in the region, there is need to reinforce the leadership of South Sudan’s health ministry with sufficient internal and external resources to support its activities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".