Bridging the Access Gap for Comprehensive Sickle Cell Disease Management Across Sub-Saharan Africa: Learnings for Other Global Health Interventions?
Notice bibliographique
Résumé
Background: Sickle cell disease (SCD) is a major unresolved global health issue, with the highest disease burden in sub-Saharan African countries; yet, SCD care has not proportionally reached patients in these regions, and the disease has received limited attention in the past. Addressing the burden of SCD in sub-Saharan Africa requires a holistic, collaborative approach to ensure solutions are both comprehensive - i.e., cover the entire continuum of care from early diagnosis to treatment - and sustainable - i.e., are co-created and co-owned with local partners and integrated into existing local systems to enable long-term independence without the need for continuous external support. Objective: We outline a set of recommendations for enhancing the provision of comprehensive healthcare for prevalent diseases in resource-constraint settings, gathered from the Novartis Africa SCD Program, that could serve as 'blueprint' for public-private partnerships to tackle global health priorities. Methods: The Novartis Africa SCD program was initiated with the aim to bridge access gaps to SCD care and provide comprehensive and innovative treatment solutions for SCD, especially in SSA where the disease burden is highest. The Program was first inaugurated in 2019 in Ghana through a public-private partnership with the Ministry of Health of the Government of Ghana, the Ghana Health Service, and the Sickle Cell Foundation of Ghana. Through engagement with these partners, as well as with support from other organizations with complementary competencies and resources, several targeted solutions were implemented to help strengthen the healthcare ecosystem to allow for comprehensive SCD management. Learnings from these interventions are highlighted as best practice consideration as a catalyst and to activate more public-private actors for this neglected global health issue. Findings and Conclusions: A solid understanding of the access barriers to comprehensive care has to be acquired by listening to and learning from patients, civil society, and local experts. Access barriers need to be addressed at multiple levels, i.e., by not only making medicines available and affordable, but also by strengthening healthcare systems, building capacity, and fostering local research and development. Partnerships across governmental, public, academic, non-profit, and private organizations are needed to secure political will, pool resources, gather expertise with understanding of the local context, and allow integration into all levels of existing local healthcare structures and the wider society.
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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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».