Cryptosporidiosis in Drinking Water: Analysis of Surveillance data from Health Protection Scotland (2006 – 2012)
Bibliographic record
Abstract
Abstract- Objective: This study seeks to update understanding of the public health issues round the epidemiology of cryptosporidiosis in Scotland between 2006 and 2012. By examining the patterns, trends and seasonal effects of cases of cryptosporidiosis amongst different age groups, sex and health boards in Scotland during the reference periods. Data Sources, Design and Methods: Data on notified cases of cryptosporidiosis was supplied by Health Board Scotland between 2006-2012, based on 16 health boards, which were modified to 14 health boards. Other variable used is the population data which was sourced from the website of the General Register office for Scotland. The Harmonic Poisson Regression model was utilized in examining the potential effects of cryptosporidiosis among different age group, sex, health boards as well as their pattern of occurrence in Scotland. Results: The models predicted that the highest number of cases of cryptosporidiosis in Scotland occurs in the fourth quarter (Autumn Season). There were 4195 reported cases of cryptosporidiosis in Scotland between 2006 and 2012. Of these number of cases, those associated with the female sex was higher with 2239 (53.27%), compared to the number of cases reported for the male sex 1926(45.91%), while a total of 30 (0.72%) cases were reported as unknown sex. The Age band of all the reported number of cases during the period under consideration were 0-
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".