Epidemiological characteristics of human infections with avian influenza A(H5N6) virus, China and Laos: A multiple case descriptive analysis, February 2014–June 2023
Bibliographic record
Abstract
Background: The first human infection with highly pathogenic avian influenza A(H5N6) virus was reported in 2014. From then until June 30, 2023, 85 human cases with confirmed A(H5N6) infection have been reported worldwide. Objective: To address the present gap in knowledge of the overall epidemiology of human A(H5N6) infections, the epidemiological characteristics of human infection with A(H5N6) in China from February 2014 to June 2023 are described. Methods: Considering the severity of human infections with A(H5N6) virus (case fatality rate: 39%), the increased frequency of case reports from 2021 to present day, and lack of comprehensive epidemiologic analysis of all cases, we conducted a multiple-case descriptive analysis and a literature review to create an epidemiologic profile of reported human cases. Case data was obtained via a literature search and using official intelligence sources captured by the Public Health Agency of Canada's International Monitoring and Assessment Tool (IMAT), including Event Information Site posts from the World Health Organization. Results: Most human A(H5N6) cases have been reported from China (China: 84; Laos: 1), with severe health outcomes, including hospitalization and death, reported among at-risk populations. The majority (84%) of cases reported contact with birds prior to illness onset. Cases were detected throughout the course of the year, with a slight decrease in illness incidence in the warmer months. Conclusion: As A(H5N6) continues to circulate and cause severe illness, surveillance and prompt information sharing is important for creating and implementing effective public health measures to reduce the likelihood of additional human infections.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".