Importance of the animal/human interface in events of international concern for the Americas
Bibliographic record
Abstract
Background: Diseases have increased their potential to cross geopolitical boundaries through international travel and trade. Zoonoses represent 75% of human pathogens emerging during the past decade. The International Health Regulations (IHR) are a binding global legal instrument that includes all the World Health Organization (WHO) Member States, which aim to ensure public health through prevention and respond to acute public health risks. The objective of this study is to understand the importance of diseases common to man and animals in events of public health importance reported to, or identified for follow up by the Organization, in an effort to reduce the risk of infectious diseases at the human/animal interface. Methods: This study analyzes events recorded in the databases for the Americas region from the implementation of the IHR (June 2007) until the end of 2008. The main source of data was the WHO Event Management System (EMS). The criterion for inclusion in human/animal interface was, “considered a zoonoses or communicable disease common to man and animals,” using the third edition of the book, Zoonoses and Communicable Diseases Common to Man and Animals published by the Pan American Health Organization. Subgroups were also created and percentages were calculated. Results: During the period studied, 110 events were recorded in the EMS for the region of the Americas. 86/110 were communicable diseases. Among these, 77/110 (70.0%) were zoonoses and communicable diseases common to man and animals (human/animal interface); 9/110 (8.2%) were considered not common to animals; 16/110 (14.5%) were syndromes with unknown etiologies; 8/110 (7.3%) were related to products. Among the 77 events considered human/animal interface related, 48 were designated “substantiated” at time of event closure. Conclusion: This analysis demonstrates approximately 70% of events are either zoonoses or communicable diseases common to man and animals, confirming previous publications and the importance of the animal/human interface. Analysis also supports “One World, One Health” framework, and the necessity of collaboration between science and other sectors. An early warning system that quickly identifies events that pose a risk to international public health may also support the countries in identifying events that are exceeding expected numbers and require an emergency response. Abstracts for SupplementInternational Journal of Infectious DiseasesVol. 14Preview Full-Text PDF Open Archive
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".