Transmissibility of the highly pathogenic avian influenza virus, subtype H5N1 in domestic poultry: a spatio-temporal estimation at the global scale
Bibliographic record
Abstract
The highly pathogenic avian influenza virus (HPAIV), subtype H5N1 poses a serious threat not only to the poultry industry and wild birds but also to humans. Despite a large number of studies conducted on various aspects of this virus, its transmissibility is still poorly understood. This study quantifies the basic reproductive number (R0) of the global HPAIV H5N1 spread within domestic poultry during December 2003 to December 2009. Three different approaches were applied to estimate R0 for HPAIV H5N1: (i) epidemic doubling time; (ii) spatial distance-based nearest neighbour; and (iii) spatio-temporal distance-based nearest neighbour. These three approaches represent temporal (tR0), spatial (sR0) and spatio-temporal transmissibility (stR0), respectively. The joint application of these three approaches provides a more complete profile by characterising the transmissibility traits of infectious diseases from different perspectives. Estimates of tR0 gradually decreased over the six sequential epidemic waves (EWs) examined, suggesting that the implemented control measures were effective in reducing the number of outbreaks. However, sR0 and stR0 increased from EW1, peaked in EW3 and then gradually decreased during EW4-EW6, reflecting different aspects of disease transmissibility compared to tR0. The application of all three methods in the final EW6 showed R0 >1, suggesting that the control measures implemented did not completely interrupt the transmission cycle, and hence were insufficient to eliminate HPAIV H5N1. Close monitoring of HPAIV H5N1 outbreaks and enhanced control policies is advised.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".