Live Poultry Trade in Southern China Provinces and HPAIV H5N1 Infection in Humans and Poultry: The Role of Chinese New Year Festivities
Bibliographic record
Abstract
BACKGROUND: The number of outbreaks of highly pathogenic avian influenza virus of the H5N1 subtype (HPAIV H5N1) over the past 5 years has been drastically reduced in China but sporadic infections in poultry and humans are still occurring. In this study, we aimed to investigate seasonal patterns in the association between the movement of live poultry originating from southern China and HPAIV H5N1 infection history in humans and poultry in China. METHODOLOGY/PRINCIPAL FINDINGS: During January to April 2010, longitudinal questionnaire surveys were carried out monthly in four wholesale live bird markets (LBMs) in Hunan and Guangxi provinces of South China. Using social network analysis, we found an increase in the number of observed links and degree centrality between LBMs and poultry sources in February and March compared to the months of January and April. The association of some live poultry traders (LPT's) with a limited set of counties (within the catchment area of LBMs) in the months of February and March may support HPAIV H5N1 transmission and contribute to perpetuating HPAIV H5N1 virus circulation among certain groups of counties. The connectivity among counties experiencing human infection was significantly higher compared to counties without human infection for the months of January, March and April. Conversely, counties with poultry infections were found to be significantly less connected than counties without poultry infection for the month of February. CONCLUSIONS/SIGNIFICANCE: Our results show that temporal variation in live poultry trade in Southern China around the Chinese New Year festivities is associated with higher HPAIV H5N1 infection risk in humans and poultry. This study has shown that capturing the dynamic nature of poultry trade networks in Southern China improves our ability to explain the spatiotemporal dissemination in avian influenza viruses in China.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".