Investigation of the Presence of Toxoplasma gondii, Giardia duodenalis, and Cryptosporidium spp. in Drinking Waters in the Region of Marrakech, Morocco
Bibliographic record
Abstract
The association between the parasitic illnesses and the consumption of contaminated water has been largely reported. However, there is still a lack of studies investigating the extent of parasitic contamination in water in Morocco. This is the first study in Morocco that aimed at assessing the presence of protozoan parasites, namely Cryptosporidium spp., Giardia duodenalis, and Toxoplasma gondii, in drinking water consumed in the region of Marrakech. Samples processing was performed by membrane filtration and qPCR detection. A total of 104 drinking water samples (tap water, well, and spring waters) was collected between 2016 and 2020. The analysis revealed an overall protozoa contamination rate of 67.3% (70/104), of which 35 samples were positive for Giardia duodenalis, 18 for Toxoplasma gondii, and 17 for both parasites, whereas no sample was positive for Cryptosporidium spp. This first study showed that drinking water in the region of Marrakech contained parasites which could represent a risk for consumers. For a better understanding and estimation of the risk encountered by local inhabitants, further studies concerned with (oo)cyst viability, infectivity, and genotype identification need to be performed.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".