A Review of Simulation Modelling Approaches Used for the Spread of Zoonotic Influenza Viruses in Animal and Human Populations
Bibliographic record
Abstract
Increasing incidences of emerging and re-emerging diseases that are mostly zoonotic (e.g. severe acute respiratory syndrome, avian influenza H5N1, pandemic influenza) has led to the need for a multidisciplinary approach to tackling these threats to public and animal health. Accordingly, a global movement of 'One-Health/One-Medicine' has been launched to foster collaborative efforts amongst animal and human health officials and researchers to address these problems. Historical evidence points to the fact that pandemics caused by influenza A viruses remain a major zoonotic threat to mankind. Recently, a range of mathematical and computer simulation modelling methods and tools have increasingly been applied to improve our understanding of disease transmission dynamics, contingency planning and to support policy decisions on disease outbreak management. This review provides an overview of methods, approaches and software used for modelling the spread of zoonotic influenza viruses in animals and humans, particularly those related to the animal-human interface. Modelling parameters used in these studies are summarized to provide references for future work. This review highlights the limited application of modelling research to influenza in animals and at the animal-human interface, in marked contrast to the large volume of its research in human populations. Although swine are widely recognized as a potential host for generating novel influenza viruses, and that some of these viruses, including pandemic influenza A/H1N1 2009, have been shown to be readily transmissible between humans and swine, only one study was found related to the modelling of influenza spread at the swine-human interface. Significant gaps in the knowledge of frequency of novel viral strains evolution in pigs, farm-level natural history of influenza infection, incidences of influenza transmission between farms and between swine and humans are clearly evident. Therefore, there is a need to direct additional research to the study of influenza transmission dynamics in animals and at the animal-human interface.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".