One Health/EcoHealth capacity building programs in South and South East Asia: a mixed method rapid systematic review
Notice bibliographique
Résumé
BACKGROUND: Although One Health (OH) or EcoHealth (EH) have been acknowledged to provide comprehensive and holistic approaches to study complex problems, like zoonoses and emerging infectious diseases, there remains multiple challenges in implementing them in a problem-solving paradigm. One of the most commonly encountered barriers, especially in low- and middle-income countries, is limited capacity to undertake OH/EH inquiries. A rapid review was undertaken to conduct a situation analysis of the existing OH/EH capacity building programs, with a focused analysis of those programs with extensive OH engagement, to help map the current efforts in this area. METHODS: A listing of the OH/EH projects/initiatives implemented in South Asia (SA) and South East Asia (SEA) was done, followed by analysis of documents related to the projects, available from peer-reviewed or grey literature sources. Quantitative data was extracted using a data extraction format, and a free listing of qualitative themes was undertaken. RESULTS: In SEA, 13 unique OH/EH projects, with 37 capacity building programs, were identified. In contrast, in SA, the numbers were 8 and 11 respectively. In SA, programs were oriented to develop careers in program management, whereas, in SEA, the emphasis was on research. Two thirds of the programs in SEA had extensive OH engagement, whereas only one third of those in SA did. The target for the SEA programs was wider, including a population more representative of OH stakes. SEA program themes reveal utilization of multiple approaches, usually in shorter terms, and are growing towards integration with the traditional curricula. Such convergence of themes was lacking in SA programs. In both regions, the programs were driven by external donor agencies, with minimal local buy-in. CONCLUSIONS: There is limited investment in research capacity building in both SA and SEA. The situation appears to be more stark in SA, whilst SEA has been able to use the systematic investment and support to develop the OH/EH agenda and strategize capacity building in the core competencies. In order to effectively address the disease emergence hotspots in these regions, there needs to be strategic funding decisions targeting capacity building in the core OH/EH competencies especially related to transdisciplinarity, systems thinking, and adaptive management.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,016 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,014 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».