Effect of community-based newborn care implementation strategies on access to and effective coverage of possible serious bacterial infection (PSBI) treatment for sick young infants during COVID-19 pandemic
Notice bibliographique
Résumé
BACKGROUND: In Ethiopia, neonatal mortality is persistently high. The country has been implementing community-based treatment of possible serious bacterial infection (PSBI) in young infants when referral to a hospital is not feasible since 2012. However, access to and quality of PSBI services remained low and were worsened by COVID-19. From November 2020 to June 2022, we conducted implementation research to mitigate the impact of COVID-19 and improve PSBI management implementation uptake and delivery in two woredas in Ethiopia. METHODS: In April-May 2021, guided by implementation research frameworks, we conducted formative research to understand the PSBI management implementation challenges, including those due to the COVID-19 pandemic. Through a participatory process engaging stakeholders, we designed adaptive implementation strategies to bridge identified gaps using mechanism mapping to achieve implementation outcomes. Strategies included training and coaching, supportive supervision and mentorship, technical support units, improved supply of essential commodities, and community awareness creation about PSBI and COVID-19. We conducted cross-sectional household surveys in the two woredas before (April 2021) and after the implementation of strategies (June 2022) to measure changes in targeted outcomes. RESULTS: We interviewed 4,262 and 4,082 women who gave live birth 2-14 months before data collection and identified 374 and 264 PSBI cases in April 2021 and June 2022, respectively. The prevalence of PSBI significantly decreased (p-value = 0.018) from 8.7% in April 2021 to 6.4% while the mothers' care-seeking behavior from medical care for their sick newborns increased significantly from 56% to 91% (p-value <0.01). Effective coverage of severely ill young infants that took appropriate antibiotics significantly improved from 33% [95% CI: 25.5-40.7] to 62% [95% CI: 51.0-71.6]. Despite improvements in the uptake of PSBI treatment, persisting challenges at the facility and systems levels impeded optimal PSBI service delivery and uptake, including perceived low quality of service, lack of community trust, and shortage of supplies. CONCLUSION: The participatory design and implementation of adaptive COVID-19 strategies effectively improved the uptake and delivery of PSBI treatment. Support systems were critical for frontline health workers to deliver PSBI services and create a resilient community health system to provide quality PSBI care during the pandemic. Additional strategies are needed to address persistent gaps, including improvement in client-provider interactions, supply of essential drugs, and increased social mobilization strategies targeting families and communities to further increase uptake.
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 | 0,013 | 0,027 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».