Genetic characterization of influenza A viruses circulating in Hong Kong, China, 2023: the first influenza epidemic after the lifting of 2.5 years of COVID-19 non-pharmaceutical interventions
Bibliographic record
Abstract
During the COVID-19 pandemic, stringent public health measures led to historically low influenza activity in Hong Kong. However, after these interventions were relaxed in 2023, Influenza A viruses (IAV), including A(H1N1)pdm09 and A(H3N2), rapidly resurfaced. In this study, 1,046 clinical cases collected throughout 2023 underwent comprehensive genomic analysis using Oxford Nanopore Technologies (ONT). Phylogenetic analyses of the assembled genome segments were conducted alongside several global public sequences for comparison. The dataset is comprised of 593 A(H1N1)pdm09 sequences, predominantly of hemagglutinin (HA) subclade 5a.2a and neuraminidase (NA) subclade C.5.3, and 453 A(H3N2) sequences classified mainly as HA subclade 2a.3a.1 and NA subclade B.4.3. Phylogenetic comparisons revealed close genetic relationships between the studied viruses and 30 A(H1N1)pdm09 and 27 A(H3N2) sequences published in other regions during the same time. Additionally, identified amino acid substitutions may affect antigenicity and viral fitness. These findings underscore Hong Kong's high post-COVID-19 influenza diversity and the need for ongoing molecular surveillance to monitor emerging viral variants.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".