A Qualitative Risk Assessment for the Introduction of Crimean-Congo Haemorrhagic Fever (CCHF) in Bhutan
Bibliographic record
Abstract
Purpose: Crimean-Congo Haemorrhagic Fever (CCHF) has been widely reported in India but no cases have been reported in humans in Bhutan. However, a serological study conducted in 2015, detected CCHF virus specific IgG antibodies in imported goats from the southern parts of Bhutan. The disease is often non-clinical in animals but can cause severe haemorrhagic fever in humans. CCHF is transmitted through the bites of an infected tick, crushing infected ticks, and direct contact with infected blood and tissues of viraemic livestock and humans. The porous border with the neighboring states of India facilitates free and unregulated movement of animals, posing continuous risk of disease incursion into the country. Furthermore, due to anthropogenic factors, such as increasing human travel, increased import of animal and meat from India, there is a risk of CCHF introduction into Bhutan. Methods & Materials: In this study we estimated the risk of CCHF introduction into Bhutan by performing a qualitative risk assessment based on an import risk assessment method developed by World Organization for Animal Health (OIE). Our assessment identified five risk pathways (meat, ticks, livestock, wildlife and human pathway) under the current risk mitigation measures. The current control and mitigation measures include 14 days quarantine to screen for notifiable animal diseases in imported livestock and regular inspection of imported meat in laboratories. The likelihood of events in this study was determined using available literature on risk pathways and knowledge gaps were addressed by soliciting expert opinion. Results: The risk of CCHF introduction was estimated to be negligible for the human pathway, low for meat and tick pathways, medium for wildlife pathway, and high for the livestock pathway. Farmers working with animals in Bhutan are found to be at higher risk than any other occupational groups to contract CCHF if the virus becomes endemic. Conclusion: Early detection of CCHF in domestic animals is of utmost importance in reducing epidemiological and economical consequences in humans. These findings highlight the importance of enhancing surveillance in domestic animals in Bhutan, instituting CCHF screening in imported animals and adopting a One Health approach to mitigate public health risk.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".