Waterborne disease: an old foe re-emerging?
Bibliographic record
Abstract
In developed countries, clean and safe drinking water is taken for granted, and water treatment processes used to mass-produce drinking water have been hailed as one of the top five engineering achievements of the 20th century. However, in the last decade, several waterborne disease outbreaks have made us painfully aware of the personal, economical, societal, and public health costs associated with the impact of waterborne disease. There is evidence to suggest that the prevalence of waterborne disease may be dramatically underestimated in developed countries and that routine endemic exposure to waterborne pathogens may occur more frequently than originally perceived. A variety of demographical, societal, environmental, and physiological emergence factors likely play critical roles in enhancing the frequency of transmission of pathogens to hosts. This review focuses on the scope and impact of waterborne disease in developed countries and identifies issues surrounding the potential for rapid global emergence or re-emergence of waterborne disease. We examine relevant literature on Cryptosporidium parvum and Escherichia coli O157 as model organisms of study that support these concepts. Key words: drinking water, treatment, public health, Cryptosporidium, Escherichia coli, emergence, pathogens, transmission, waterborne disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".