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Record W2117332274 · doi:10.1089/fpd.2011.1065

Case-Control Studies of Sporadic Enteric Infections: A Review and Discussion of Studies Conducted Internationally from 1990 to 2009

2012· review· en· W2117332274 on OpenAlexaff
Kathleen E. Fullerton, Elaine Scallan, Martyn Kirk, Barbara E. Mahon, Frederick J. Angulo, Henriette de Valk, Wilfrid van Pelt, Charmaine Gauci, Anja M. Hauri, Shannon E. Majowicz, S. O’Brien

Bibliographic record

VenueFoodborne Pathogens and Disease · 2012
Typereview
Languageen
FieldMedicine
TopicViral gastroenteritis research and epidemiology
Canadian institutionsPublic Health Agency of Canada
FundersNational Institutes of Health
KeywordsOutbreakDiseaseEnteric virusMedicineEnvironmental healthPopulationControl (management)Case-control studyPathologyComputer scienceVirology

Abstract

fetched live from OpenAlex

Epidemiologists have used case-control studies to investigate enteric disease outbreaks for many decades. Increasingly, case-control studies are also used to investigate risk factors for sporadic (not outbreak-associated) disease. While the same basic approach is used, there are important differences between outbreak and sporadic disease settings that need to be considered in the design and implementation of the case-control study for sporadic disease. Through the International Collaboration on Enteric Disease "Burden of Illness" Studies (the International Collaboration), we reviewed 79 case-control studies of sporadic enteric infections caused by nine pathogens that were conducted in 22 countries and published from 1990 through to 2009. We highlight important methodological and study design issues (including case definition, control selection, and exposure assessment) and discuss how approaches to the study of sporadic enteric disease have changed over the last 20 years (e.g., making use of more sensitive case definitions, databases of controls, and computer-assisted interviewing). As our understanding of sporadic enteric infections grows, methods and topics for case-control studies are expected to continue to evolve; for example, advances in understanding of the role of immunity can be used to improve control selection, the apparent protective effects of certain foods can be further explored, and case-control studies can be used to provide population-based measures of the burden of disease.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.735
Threshold uncertainty score0.796

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
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 head0.129
GPT teacher head0.413
Teacher spread0.283 · 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 designOther design
Domainnot available
GenreReview

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

Citations16
Published2012
Admission routes1
Has abstractyes

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