Spatial analysis of campylobacter infection in the Canadian province of Manitoba
Bibliographic record
Abstract
BACKGROUND: The study describes population level variations in campylobacter incidence within the Canadian province of Manitoba, and the relationship to sociodemographic and landscape related characteristics. Using data derived from the Manitoba Health Public Health Branch communicable disease surveillance database, the study applied a number of spatial and ecological techniques to visualize, explore and model campylobacter incidence for the years 1996 to 2004. Analytical techniques used in the study included spatial smoothing, the spatial scan statistic, the Gini coefficient, and Poisson regression analysis. RESULTS: The study demonstrated marked and statistically significant geographic variability in the rates of campylobacter incidence in Manitoba.. The incidence of campylobacter was observed to be significantly higher in populations living in rural and agricultural areas of the province, with the highest rates occurring in populations living in proximity to high densities of farm animals (cows, pigs, chickens). The study also observed that the age specific pattern of campylobacter incidence in rural Manitoba was very different than the urban pattern, with the incidence rate in the 0-4 year age group seven times higher in rural Manitoba than in the City of Winnipeg. CONCLUSION: The study demonstrates the value of a deploying a diverse set of spatial techniques to better understand the dynamics of an enteric disease such as campylobacter infection. The study concludes that there may be three distinct mechanisms for the transmission of campylobacter in Manitoba which are operating simultaneously. These include broad population exposure to a centralized food system endemically infected with the campylobacter organism, exposure to local level factors such as farm animals or contaminated water, and exposure to campylobacter infection through foreign travel.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".