Domestic River Water Use and Risk of Typhoid Fever: Results From a Case-control Study in Blantyre, Malawi
Bibliographic record
Abstract
BACKGROUND: Typhoid fever remains a major cause of morbidity and mortality in low- and middle-income settings. In the last 10 years, several reports have described the reemergence of typhoid fever in southern and eastern Africa, associated with multidrug-resistant H58 Salmonella Typhi. Here, we identify risk factors for pediatric typhoid fever in a large epidemic in Blantyre, Malawi. METHODS: A case-control study was conducted between April 2015 and November 2016. Cases were recruited at a large teaching hospital, and controls were recruited from the community, matched by residential ward. Stepwise variable selection and likelihood ratio testing were used to select candidate risk factors for a final logistic regression model. RESULTS: Use of river water for cooking and cleaning was highly associated with risk of typhoid fever (odds ratio [OR], 4.6 [95% confidence interval {CI}, 1.7-12.5]). Additional risk factors included protective effects of soap in the household (OR, 0.6 [95% CI, .4-.98]) and >1 water source used in the previous 3 weeks (OR, 3.2 [95% CI, 1.6-6.2]). Attendance at school or other daycare was also identified as a risk factor (OR, 2.7 [95% CI, 1.4-5.3]) and was associated with the highest attributable risk (51.3%). CONCLUSIONS: These results highlight diverse risk factors for typhoid fever in Malawi, with implications for control in addition to the provision of safe drinking water. There is an urgent need to improve our understanding of transmission pathways of typhoid fever, both to develop tools for detecting S. Typhi in the environment and to inform water, sanitation, and hygiene interventions.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".