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Record W4414111764 · doi:10.1177/15353141251377318

Epidemiology of <i>Cyclospora cayetanensis</i> Infections in Canada: 2000–2022

2025· article· en· W4414111764 on OpenAlexaffabout
Vanessa Morton, Rachelle Janicki, Danielle Dumoulin, Brent R. Dixon, Rebecca A. Guy

Bibliographic record

VenueFoodborne Pathogens and Disease · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
TopicParasitic Infections and Diagnostics
Canadian institutionsHealth CanadaPublic Health Agency of Canada
Fundersnot available
KeywordsOutbreakEpidemiologyPublic healthIncidence (geometry)DiseasePublic health surveillanceDisease surveillanceMolecular epidemiology

Abstract

fetched live from OpenAlex

is a human-specific protozoan parasite that causes gastrointestinal illness, primarily through the ingestion of contaminated water or fresh produce. This study provides an epidemiological overview of cyclosporiasis in Canada from 2000 to 2022 using data from the Canadian Notifiable Disease Surveillance System, FoodNet Canada, and outbreak investigations. A total of 5337 cases were reported during this period, with the incidence increasing from 0.12 to 1.70 per 100,000 population. Seasonal peaks occurred between May and August of each year, and adults aged 30-59 years were disproportionately affected. Enhanced surveillance data identified international travel, particularly to resorts in Mexico, as a common exposure. National-level investigations occurred annually from 2013 to 2022, and various fresh produce items were identified as items of interest, but few investigations led to the identification of a source of illness. Advancements in molecular diagnostics since 2015 have likely contributed to the observed rise in case detection. This report underscores the burden of cyclosporiasis in Canada and highlights the need for continued surveillance, public health interventions targeting contaminated produce, and travel health messaging to mitigate outbreaks and reduce transmission. It also underscores the importance of real-time genetic typing to identify and differentiate clusters of closely related isolates that are more likely to share a common source.

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)0.001
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 score0.071
Threshold uncertainty score0.739

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.009
GPT teacher head0.239
Teacher spread0.230 · 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

Citations2
Published2025
Admission routes2
Has abstractyes

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