Pathogenic Microorganisms Associated With Childhood Diarrhea in Low-and-Middle Income Countries: Case Study of Yaoundé – Cameroon
Bibliographic record
Abstract
Notwithstanding significant advancement in the understanding of pathogenesis and management, diarrheal illnesses remain one of the principal causes of global childhood mortality and morbidity. Infections account for most illnesses, with pathogens employing ingenious mechanisms to establish disease. In 2002, an interdisciplinary program "Populations et al. Espaces à Risques SANitaires" (PERSAN) was set up under the patronage of the Development Research Institute (IRD). Focused on health in Cameroon's urban environment, the program mainly sought to identify diarrhea risk factors in Yaoundé. So for, a cross-sectional epidemiological study in children aged 6-59 months was carried out using a standardized protocol. The survey was initiated in 2002 and conducted during April to June in the year 2005. 3,034 stool samples were collected from children in twenty neighbourhoods in Yaoundé and examined at the Epidemiology and Public Health Laboratory of the Cameroon Pasteur Institute. About 60% of the patients were aged less than two years and 52% were male. Among the 437 patients with the diarrheal disease, 260 were found to be of infectious etiology, i.e. micro organism was detected in 59.5% of the cases. Out of which, 10 (03.8%), 96 (36.9%), and 154 (59.2%) were respectively caused by pathogenic viruses, pathogenic bacteria and pathogenic parasites. Higher prevalence was found in overcrowded and under supply spontaneous settlement (78.4%) than in less crowded and formal residential settlement (21.5%). Etiologic data on diarrheal diseases and their spatial distribution are important tools for public health management and control strategic planning.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".