The application of advanced statistical approaches to investigate the epidemiology and improve the surveillance of non-Typhoid salmonellosis associated with Salmonella Heidelberg and Salmonella Typhimurium in Ontario
Bibliographic record
Abstract
In this thesis, I investigated the epidemiology of non-typhoid salmonellosis in Ontario in 2015, with a specific focus on Salmonella Typhimurium and S. Heidelberg. Data for each reported human case of S. Typhimurium and S. Heidelberg in Ontario in 2015 were analyzed through a series of research projects. Overall thesis objectives were to compare risk factors associated with each serotype, and to explore clusters and potential outbreaks in space, time, and space-time. Where relevant, human case data were combined with population and agricultural census data, and data for licensed meat plants (abattoirs) in Ontario. The application of various statistical models was explored to further understand the epidemiology of each of these serotypes, and to identify potential improvements to current processes for surveillance, cluster detection, and public health case and outbreak investigations. \nIn comparing the epidemiology of these serotypes, several key findings were identified: 1) Using a case-case study design, consumption of sprouts was found to increase the odds of infection due to S. Heidelberg, relative to S. Typhimurium. Conversely, recent travel or contact with reptiles each increased the odds of infection with S. Typhimurium, relative to S. Heidelberg. \n2) Using scan statistics, clusters of S. Heidelberg and S. Typhimurium were identified in space, time, and space-time, independent of molecular laboratory data. Clusters were validated and potential outbreaks identified using molecular and risk factor data. \n3) Using scan statistics and focused spatial tests, clusters of S. Heidelberg were identified around several meat plants. Risk factor and molecular laboratory data provided evidence in support of implicated meat plants as a source of exposure. \n4) Using mixed regression models, rates of S. Typhimurium and S. Heidelberg were found to be associated with agricultural and socioeconomic variables such as agricultural animal density, the proportion of married individuals, and labour participation, each of which may influence animal exposure and food consumption patterns, impacting the risk of exposure to Salmonella. \nThis thesis demonstrates how identification and consideration of serotype-specific differences for Salmonella, and the use of geospatial methods for cluster detection, can be used to optimize and inform public health surveillance and disease prevention efforts.
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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 | 0.015 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".