The use of temporal-spatial analyses in the epidemiological investigation of endemic and epidemic waterborne gastroenteritis
Bibliographic record
Abstract
Few approaches are available to study the relationship between drinking water and gastroenteritis in communities served by one common water source, or multiple sources where water undergoes extensive mixing within a distribution system. When the majority of the population is exposed to a common risk factor, it is very difficult, if not impossible, to assess the relationship between a disease and a risk factor of interest using traditional epidemiological techniques (cross-sectional study, case-control study, etc.). In this thesis, the results of two endemic studies and one epidemic study demonstrate the utility of temporal-spatial analytical techniques in the investigation of waterborne gastroenteritis. Endemic waterborne disease investigations were conducted in two cities with vastly different approaches to drinking water supply management: Vancouver, British Columbia and Edmonton, Alberta. Whereas Vancouver's drinking water originates from protected watersheds and undergoes minimal treatment, Edmonton's drinking water is drawn from a river with much poorer water quality, but undergoes full conventional treatment. Using time-series analysis, evidence for a relationship between the daily turbidity of unfiltered drinking water and endemic gastroenteritis was identified in Greater Vancouver from 1992 to 1998. Statistically significant associations were found between daily visits to emergency rooms, physician offices', and hospitalizations, for gastroenteritis and daily water turbidity among consumers of each of Vancouver's three water supplies. Lag-times (i.e. time from the turbidity increase to the increase in health care utilisation) observed were both biologically plausible and relatively consistent across water supply areas, age groups, and health service data sets. The inclusion of a formal control group in a comparative logistic (case-control) regression approach added strength to the study findings, and supported the underlying hypothesis of causality. Results of temporal-spatial analyses suggested very little impact, if any, of filtered drinking water from Edmonton's two water treatment plants on the level of endemic gastroenteritis among Edmonton residents from 1993 to 1999. The lack of significant temporal relationships between daily drinking water quality and health care utilisation associated with gastroenteritis, together with the lack of obvious spatial relationships between gastroenteritis and the two Edmonton water service areas, support the opinion that the high quality of Edmonton's drinking water adequately minimises the risk of waterborne endemic gastroenteritis. Furthermore, the lack of significant relationships between raw water turbidity and faecal coliform counts, and endemic gastroenteritis, support the effectiveness of the treatment processes utilised. Analyses of a waterborne 'E. coli' O157:H7/'Campylobacter ' outbreak in Walkerton, Ontario in May 2000, demonstrated an association between water originating from one of three wells supplying the town at the time of the outbreak (Well 5), and the risk of developing gastroenteritis. The results of the Walkerton investigation provided strong evidence to support what is now considered the most likely series of events leading up to the infection of an estimated 1286 Walkerton residents with 'E. coli' O157:H7 and/or 'Campylobacter'. The results of the temporal-spatial analyses strongly support the theory that Well 5 was the primary, if not the only well involved in the outbreak.
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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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".