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Record W2126747114 · doi:10.1186/1476-072x-3-11

Investigation of clusters of giardiasis using GIS and a spatial scan statistic

2004· article· en· W2126747114 on OpenAlex
Agricola Odoi, S.W. Martin, Pascal Michel, Dean Middleton, John Holt, Jeff Wilson

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Health Geographics · 2004
Typearticle
Languageen
FieldImmunology and Microbiology
TopicMicrobial infections and disease research
Canadian institutionsHealth CanadaMinistry of Health and Long Term CareUniversité de MontréalUniversity of Guelph
FundersHealth CanadaOntario Ministry of Health and Long-Term Care
KeywordsScan statisticHealth geographyHealth informaticsStatisticGeospatial analysisGeographyHuman geographyPublic healthGeographic information systemSpatial analysisComputer scienceEnvironmental healthData scienceStatisticsCartographyData miningMedicineRemote sensingMathematicsPathologyEconomic geographyHealth policyInternational health

Abstract

fetched live from OpenAlex

BACKGROUND: Giardia lamblia is the most frequently identified human intestinal parasite in Canada with prevalence estimates of 4-10%. However, infection rates vary by geographical area and localized 'pockets' of high or low infection rates are thought to exist. Water-borne transmission is one of the major routes of infection. Sources of contamination of drinking water include humans, domestic and wild animals. A previous study in southern Ontario, Canada, indicated a bivariate association between giardiasis rates and livestock density and/or manure use on agricultural land; however these variables were not significant when the variable 'rural' was added to the model. In that study, urban areas were defined as those with a minimum of 1,000 persons and a population density of at least 400 persons per Km2; all other areas were considered rural. This paper investigates the presence of local giardiasis clusters and considers the extent to which livestock density and manure application on agricultural land might explain the 'rural' effect. A spatial scan statistic was used to identify spatial clusters and geographical correlation analysis was used to explore associations of giardiasis rates with manure application on agricultural land and livestock density. RESULTS: Significant (P < 0.05) high rate spatial clusters were identified in a number of areas. Results also showed significant (P < 0.05) associations between giardiasis rates and both livestock density and manure application on agricultural land. However, the associations were observed in only two regions. CONCLUSIONS: There is evidence that giardiasis clusters in space in southern Ontario. However, there is no strong evidence to suggest that either livestock density or manure application on agricultural land plays an important role in the epidemiology of giardiasis in the study area. Therefore these factors do not seem to explain the higher rates of giardiasis reported in rural areas. The spatial scan statistics methodology used in this study has an important potential use in disease surveillance for confirming or refuting cluster alarms.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.410
Threshold uncertainty score0.885

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.035
GPT teacher head0.334
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it