A Systematic Review and Meta‐Analysis of Phase I Inactivated Vaccines to Reduce Shedding of<i>Coxiella burnetii</i>From Sheep and Goats From Routes of Public Health Importance
Bibliographic record
Abstract
Q fever in humans and coxiellosis in livestock are both caused by Coxiella burnetii. The public health importance of vaccination against C. burnetii shedding from sheep and goats was evaluated using systematic review and meta-analysis to provide evidence for policy direction to prevent potential zoonotic spread. Publications reporting shedding of C. burnetii in vaginal and uterine secretions, milk, placenta and faeces were included. A single observational (one goat) and seven experimental (four goat and three sheep) vaccine studies were included in the review. No relevant publications on other interventions were identified. Random effects meta-analyses were performed for the risk of shedding in individuals in the control and vaccinated groups and for the mean difference in the level of bacterial shedding in sheep and goats stratified by age and previous exposure status. Limited data were available for further analytic evaluation. From the pooled analysis, an inactivated phase I vaccine significantly reduced the risk of shedding from uterine (RR = 0.10; 95%CI 0.05-0.20) secretions in previously sensitized goats. Individual studies reported significant risk reduction in milk (RR = 0.03; 95%CI 0.01-0.26), vaginal secretions (RR = 0.40; 95%CI 0.22-0.75) and faeces (RR = 0.79; 95%CI 0.63-0.97) from naïve goats. The pooled mean levels of bacteria shed from placental [mean difference (MD = -5.24 Log10 ; 95%CI -6.75 to -3.7)] and vaginal (MD = -1.78 Log10 ; 95%CI -2.19 to -1.38) routes were significantly decreased in vaccinated naïve goats compared with controls. Shedding through all other routes from vaccinated goats was not significantly different than shedding from control goats. No effect of vaccination was found on the risk of shedding or the mean level of shedding in vaccinated sheep compared with control sheep. Our conclusions are based on a limited amount of data with variable risk of systematic error.
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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 | 0.011 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.037 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".