Public Health and Primary Health Care Collaboration in Eight High-Income Countries During the Covid-19 Pandemic
Notice bibliographique
Résumé
CONTEXT: The COVID-19 pandemic highlights the importance of strong public health (PH) and primary health care (PHC) systems to respond nimbly and effectively during times of crisis. Both play a crucial role in triage and prevention, management, vaccination, and communication. PH and PHC systems, however, often act in parallel streams, but rarely together. OBJECTIVE: This study aims to describe PH and PHC collaboration during the COVID-19 pandemic in eight high-income countries. METHODS: In-depth case study reports were generated for each country or jurisdiction. Reports searched both peer-review publications and grey literature on five dimensions identified by the World Health Organization regarding COVID-19 management. Reports included country-specific health system descriptions, PH and PHC actions during the pandemic, and an evaluation of strengths and weaknesses. Expert validation was conducted by internal country stakeholders prior to cross-jurisdiction analyses. ANALYSIS: Thematic content analysis was conducted on all reports to develop a coding framework. Codes were identified that were relevant to the research questions. The study team discussed and reconciled discrepancies in themes until consensus was reached. RESULTS: Data was collected from eight high-income countries (Belgium, Canada, Germany, Italy, Japan, the Netherlands, Norway, and Spain) from March 2020 to July 2021. Four key themes were identified along with respective strengths/weaknesses. 1) Health information systems: this played a critical role for disease containment and management when designed for efficient data management and cross-sectoral data-sharing. 2) Communication: In countries where PHC was engaged early on, PH messages were amplified; in other countries, a lack of cohesion in communication resulted in poor or delayed community-level responses. 3) Human resource capacity: Health human resources were overwhelmed, with many staff redeployed and undertrained. 4) Professional training: Health professionals who received dual training in PH and PHC acted as strong community champions and may be a bridge for future pandemics. CONCLUSION: Health system needs shifted dramatically throughout the COVID-19 pandemic. Our findings highlight four key lessons regarding PH and PHC collaboration from eight high-income countries. Future pandemic preparedness should focus on health information systems and data management, PH communication, health human resources, and education and training.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,024 | 0,035 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,003 | 0,008 |
| Études des sciences et des technologies | 0,005 | 0,004 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,001 | 0,007 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».