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Record W2007052379 · doi:10.1186/1471-2334-12-318

Environmental and demographic risk factors for campylobacteriosis: do various geographical scales tell the same story?

2012· article· en· W2007052379 on OpenAlexafffundabout
Julie Arsenault, Olaf Berke, Pascal Michel, André Ravel, Pierre Gosselin

Bibliographic record

VenueBMC Infectious Diseases · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsCentre hospitalier universitaire de QuébecInstitut National de Santé Publique du QuébecCegep de Saint HyacintheUniversity of GuelphUniversité de MontréalMinistry of Agriculture, Fisheries and FoodPublic Health Agency of Canada
FundersAgriculture and Agri-Food CanadaUniversité de MontréalCanadian Institutes of Health ResearchMinistère de l'Agriculture, des Pêcheries et de l'Alimentation
KeywordsCampylobacteriosisGeographyPopulation densityVeterinary medicinePopulationIncidence (geometry)Environmental healthDemographyEcologyCampylobacterBiologyMathematicsMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: Campylobacter is a common cause of bacterial gastro-enteritis characterized by multiple environmental sources and transmission pathways. Ecological studies can be used to reveal important regional characteristics linked to campylobacteriosis risk, but their results can be influenced by the choice of geographical units of analysis. This study was undertaken to compare the associations between the incidence of campylobacteriosis in Quebec, Canada and various environmental characteristics using seven different sets of geographical units. METHODS: For each set of geographical unit, a conditional autoregressive model was used to model the incidence of reported cases of campylobacteriosis according to environmental (poultry density, ruminant density, slaughterhouse presence, temperature, and precipitation) and demographic (population density, level of education) characteristics. Models were compared in terms of number of significant predictors, differences in direction and magnitude of predictors, and fit of the models. RESULTS: In general, the number of significant predictors was reduced as the aggregation level increased. More aggregated scales tend to show larger but less precise estimates for all variables, with the exception of slaughterhouse presence. Regional characteristics associated with an increased regional risk of campylobacteriosis, for at least some geographical units, were high ruminant density, high poultry density, high population density, and presence of a large poultry slaughterhouse, whereas a reduction in risk was associated with a lower percentage of people with diplomas, a lower level of precipitation, and warmer temperature. Two clusters of elevated residual risk were observed, with different location and size depending on the geographical unit used. CONCLUSIONS: Overall, our results suggest that the use of municipality or census consolidated subdivision were the most optimal scales for studying environmental determinants of campylobacteriosis at a regional level. This study highlights the need for careful selection and analysis of geographical units when using ecological study designs.

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 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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.604

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.012
GPT teacher head0.211
Teacher spread0.199 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations27
Published2012
Admission routes3
Has abstractyes

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