Prevalence of Bluetongue and the distribution of Culicoides species in northern and southern regions of Kazakhstan in 2023–2024
Bibliographic record
Abstract
Introduction Bluetongue virus (BTV) is a significant vector-borne pathogen affecting ruminants, leading to substantial economic losses, and adversely impacting livestock production worldwide. Recently, Bluetongue (BT) has emerged as a growing concern for European and Asian countries, including Kazakhstan. This study examines the prevalence and distribution of BTV in Kazakhstan during 2023-2024, providing up-to-date information on its occurrence in livestock and Culicoides species. The findings aim to contribute to better understanding and management of BT in the region. Methods A total of 972 whole blood and 972 serum samples were collected from cattle, sheep, and goats in the southern and northern regions of Kazakhstan, alongside 11,859 Culicoides midges in the autumn of 2023 and Spring of 2024. The serum samples were tested for BT virus (BTV)-specific antibodies using ELISA, while the whole blood and Culicoides specimens were analyzed for BTV RNA by Real-time RT-PCR (rRT-PCR). Morphological and molecular identification of Culicoides species was also conducted. Result The overall seroprevalence of BTV in Southern Kazakhstan increased across all animal species in 2024 compared to 2023, with goats showing the most notable rise (from 3.8% to 29.5%). In the northern regions, seroprevalence remained zero in 2023 but reached 10.0% in cattle by 2024. rRT-PCR results confirmed active virus circulation, with rRT-PCR-positive samples significantly higher in 2024, especially among goats (from 4.2% in 2023 to 62.0% in 2024) and cattle (from 9.2% to 34.4%). Based on morphology, nine species of Culicoides midges were identified, including C. obsoletus a known BTV vector in European countries. Four of them were genetically confirmed, and BTV RNA was detected in all four species ( C. miutissimus, C. sphagnumensis, C. newsteadi , and C. pectipennis ), suggesting their potential vectorial role in BTV transmission. Discussion This study provides new insights into the epidemiology of BT in Kazakhstan and serves as a valuable resource for veterinary professionals. The findings emphasize the need for continued surveillance and vector control strategies to mitigate the spread of BTV in the region.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| 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".