Epidemiology and Outcomes of Crimean-Congo Hemorrhagic Fever in Afghanistan: A Review of 2010–2019
Bibliographic record
Abstract
Background: The study investigates the recent surge in Crimean-Congo Hemorrhagic Fever (CCHF) cases in Afghanistan, a high-risk viral disease transmitted through tick bites and livestock, and aims to identify patterns of the increase and offer prevention strategies. Methods: A systematic review of all scholarly articles published on CCHF in Afghanistan between 2010 and 2019 was conducted using a comprehensive and rigorous search strategy using the PubMed database. The quality of the included studies was assessed using the Newcastle-Ottawa Scale and the Cochrane Risk of Bias Tool. Results: During the study period, 1537 suspected cases of CCHF were reported in Afghanistan, with the highest number and deaths in the western region. The majority of cases were male, aged 16-84, and involved in animal husbandry, agriculture, and healthcare workers, with a 2:1 male-to-female ratio. The majority of cases were aged 16-84. Conclusion: This study highlights the need for effective measures to prevent CCHF transmission in Afghanistan, such as education, improved animal management, and infection control in hospitals and laboratories, to reduce outbreak risks and enhance public health.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".