Q Fever in Rural Australia: Education Versus Vaccination
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".