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Record W2885859152 · doi:10.1089/vbz.2018.2307

Q Fever in Rural Australia: Education Versus Vaccination

2018· article· en· W2885859152 on OpenAlexaff
Patrick Lindsay, Sagar Rohailla, Spiros Miyakis

Bibliographic record

VenueVector-Borne and Zoonotic Diseases · 2018
Typearticle
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCoxiella burnetiiQ feverMedicineEpidemiologyVaccinationEnvironmental healthRural areaTransmission (telecommunications)Family medicineImmunologyInternal medicineVirologyPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Q fever is an infection caused by Coxiella burnetii, a zoonotic disease acquired from both wild and domestic animals. Northern rural New South Wales (NSW) communities in Australia have an increased risk of exposure to this organism. Both the acute and chronic phases of the infection are associated with significant morbidity, which is often increased by delayed recognition and treatment. Recent termination of vaccination programs in Australia may increase the risk of infection in these populations. MATERIALS AND METHODS: This cross-sectional study evaluated the current knowledge base and overall understanding of clinicians on the epidemiology, presentation, and diagnosis of Q fever in the Northern New South Wales Local Health District. RESULTS: Forty-five participants responded to the survey. Among those, 35 participants (78%) were hospital based and 10 (22%) were from doctors working in the community. Thirty-one (72%) clinicians answered bacteria as the cause of Q fever, 34 (79.1%) participants selected animals as the reservoir of Q fever infection, and 22 (51%) identified inhalation as the form of transmission. The majority identified livestock rearing occupations (84%) as a high-risk group; however, only 65-70% identified stock yard and meat workers as groups also at risk. Furthermore, 23 (51%) of the participants considered those living in rural and remote communities as high risk. CONCLUSIONS: Our results identified gaps in knowledge of clinicians in the epidemiology and diagnosis of acute Q fever infection. With the termination of vaccination programs, this study highlights the need for education programs that can increase Q fever awareness toward prompt identification and treatment.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.205
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.016
GPT teacher head0.279
Teacher spread0.263 · 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; both teacher heads agree on what is shown here.

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

Citations7
Published2018
Admission routes1
Has abstractyes

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