9.F. Workshop: Rapid evidence synthesis to inform the national response to the COVID-19 pandemic in Ireland
Notice bibliographique
Résumé
Abstract The Health Information and Quality Authority (HIQA) is an independent statutory authority in Ireland. Since March 2020, HIQA has been conducting evidence syntheses to support decision-making by the Irish National Public Health Emergency Team (NPHET). This work has informed guidance developed by national and international agencies such as the European Centre for Disease Prevention and Control (ECDC), Newfoundland and Labrador Center for Applied Health Research, Sciensano (Belgium), Alberta Health Services and Sante Publique France. The HIQA COVID-19 Evidence Synthesis Team draws on a broad range of evidence with expert clinical and public health input from HIQA's COVID-19 Expert Advisory Group, and produces a range of outputs to best suit the evidence needs of decision-makers. Across the world, agencies have had to adapt rapidly to provide up-to-date COVID-19 research evidence to decision-makers. Similarly, evidence users, including the public, have had to assimilate information on COVID-19 generated by such agencies. Significant challenges exist given the speed at which the evidence base is evolving on COVID-19, its sometimes conflicting nature and often poor quality, and the subsequent influence of its dissemination on policy and on individual behaviour and risk perceptions. This workshop describes the work of HIQA's COVID-19 Evidence Synthesis Team in its role to support the national response to the COVID-19 pandemic. The aim of this workshop is to share learnings on the structure, methodological approaches, and impact of a COVID-19 Evidence Synthesis Team. The presenters who all work on, or are affiliated with HIQA's COVID-19 Evidence Synthesis Team, will discuss a range of topics including the establishment of the team, the conduct of rapid evidence syntheses, and the impact and media coverage of the outputs. The presenters will each present their topic in turn and will allow ample time for engagement, and will use e-voting systems, to enable shared learning. The objectives for this workshop are to: Describe the establishment and organisation of a COVID-19 Evidence Synthesis Team Provide case examples of completed rapid evidence syntheses Examine the media coverage of selected outputs Present the findings of a an in-action evaluation Share learnings on the organisation of evidence synthesis teams, the conduct of rapid evidence syntheses and the subsequent communication of findings. As the pandemic moves into a new phase it is important that agencies involved in conducting, and using the findings of, evidence syntheses reflect on processes and impact to-date. Lessons learned from the COVID-19 evidence synthesis experience can inform the development of future evidence synthesis approaches as well as support future pandemic preparedness. There is a need to remain flexible and to innovate, and this workshop presents an ideal opportunity for a European public health audience to share experiences and ideas. Key messages The challenges and opportunities associated with conducting rapid evidence synthesis during a pandemic will be explored. This workshop will provide a space to share learnings and ideas.
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 | 0,198 | 0,058 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».