Impacts of climate change on the global spread and habitat suitability of Coxiella burnetii: Future projections and public health implications
Bibliographic record
Abstract
Coxiella burnetii , an intracellular zoonotic bacterium, affectsing various livestock and wildlife species and poses significant risks to human health. This study aims to assess how climate change could impact the global distribution and habitat suitability of Coxiella burnetii , the pathogen responsible for Q fever. An ensemble species distribution modelling approach, integrating regression-based and machine-learning algorithms (GLM, GBM, RF, MaxEnt), was used to project habitat suitability (Current time and by 2050, 2070, and 2090). Climate variables were obtained from five global circulation models (GCMs) under two climate change scenarios (SSP2-4.5 and SSP5-8.5). The study evaluated the models’ performance using the area under the curve (AUC) and true skill statistics (TSS). Results show that under current climate conditions, C. burnetii is widespread across regions like North and South America, Europe, and parts of Africa, Asia, and Australia. Future projections indicate a northward shift in habitat suitability, especially under the severe SSP5-8.5 scenario, with significant expansions into Russia, northern Europe, and Canada. Conversely, regions in South America, Africa, and Australia may see declines in suitable habitats. By 2090, a 44.56 % (range: 33–57.9 %) across the models, increase in suitable habitat is predicted, accompanied by a 27.66 % (range: 22.4–31.7 %) loss of current habitats. Findings indicate that temperature seasonality and precipitation of the driest month are the most influential climatic variables shaping the distribution of C. burnetii . These results underscore the importance of climate variability in influencing the pathogen's global distribution and highlight the critical role of environmental factors in predicting future habitat shifts. The study highlights the profound impact climate change could have on the global distribution of C. burnetii . It underscores the need for proactive public health strategies in emerging high-risk areas and emphasizes the importance of mitigating risks in regions experiencing habitat declines. These findings offer valuable insights for public health planning and livestock management under future climate scenarios. In interpreting these results, it is important to consider modelling uncertainties, including assumptions and data limitations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".