Prevalence and seasonal transmission of Schistosoma haematobium infection among school-aged children in Kaedi town, southern Mauritania
Bibliographic record
Abstract
BACKGROUND: Mauritania is at the fringe of transmission of human schistosomiasis, which mainly occurs in the southern and southeastern parts of the country. This study aimed to assess the influence of rainfall seasonality on the prevalence of Schistosoma haematobium infection among school-aged children in Kaedi, southern Mauritania. METHODS: Cross-sectional surveys (i.e. parasitological, malacological and observations on water-related human activities) were carried out in Kaedi between September 2014 and May 2015, during both the wet and dry seasons. A total of 2162 children aged 5-15 years provided a single urine sample that was subjected to S. haematobium diagnosis. Snails were sampled and checked for cercarial shedding. Water contact patterns of the local population were recorded by direct observation. RESULTS: The prevalence of S. haematobium was 4.0% (86/2162, 95% confidence interval (CI): 3.2-4.9%) with a geometric mean egg count per 10 ml of urine of 3.7 (95% CI: 2.8-4.3). Being male (adjusted odds ratio (aOR) 1.78, 95% CI: 1.13-2.80), being at primary school (aOR 1.73, 95% CI: 1.04-2.87) and dry season (aOR 0.56, 95% CI: 0.35-0.89) were significantly associated with S. haematobium. Among 284 potential intermediate host snail specimens collected over the rainy and dry seasons, three species were identified: Bulinus senegalensis (n = 13) and B. forskalii (n = 161) in the rainy season, and B. truncatus (n = 157) in the wet season. No snail was shedding cercariae. On average, seven human water contacts were recorded per hour per observer over a 28-day observation period. Twelve types of water contact activities were identified among which, swimming/bathing was predominant (n = 3788, 36.9%), followed by washing clothes (n = 2016, 19.7%) and washing dishes (n = 1322, 12.9%). Females (n = 5270, 51.4%) were slightly more in contact with water than males (n = 4983, 48.6%). The average time spent in the water per person per day was 14.2 min (95% CI: 13.8-14.6 min). The frequency and duration of water contact followed a seasonal pattern. CONCLUSION: Our findings demonstrate a low prevalence and intensity of S. haematobium among school-aged children in Kaedi. Appropriate integrated control measures, including health education among at-risk communities and snail control may help to interrupt transmission of S. haematobium in Kaedi.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".