Effective treatment coverage for sick young infants with possible serious bacterial infection when referral not feasible in low-and middle-income countries
Systematic review and meta-analysis
Bibliographic Data
| ID | 15380387 |
|---|---|
| Authors | Wassie Negash (0000-0002-0869-9747, Addis Ababa University, corresponding author), Wassie Negash Mekonnen, Gizachew Tadele Tiruneh (0000-0002-5842-9518), Adugnaw Berhane (0000-0003-2160-958X, Addis Ababa University), Wubegzier Mekonnen (0000-0002-7153-4988, Addis Ababa University) |
| Year | 2025 |
| Volume | 26 |
| Issue | 1 |
| Pages | 404-404 |
| Publication date | 2025-12-29 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | BMC Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1471-2458 • E-ISSN: 1471-2458 |
| Publisher | BioMed Central (PUBLISHER • GB) |
| DOI | 10.1186/s12889-025-25934-9 |
| PMID | 41462174 |
| OpenAlex | W7117447540 |
| Language | EN |
| References cited | 34 |
Introduction Bacterial infections are major causes of neonatal deaths globally and about 6.9 million episodes occur among young infants in low-and middle-income countries every year. A comprehensive cascade of care from identifying the target population to outcome-adjusted coverage is essential to identify service delivery bottlenecks and take corrective action; however, the majority of studies included single treatment coverage rates. In this study, we conducted a systematic review and meta-analysis to estimate pooled coverage levels across stages of the care cascade, using a standardized framework for treatment coverage Methods We searched studies using a population, concept, and context framework combined with the Boolean terms ‘AND’ and ‘OR’ on PubMed/Medline, Cochrane, EMBASE, and Web of Science databases and grey literature. Two independent reviewers appraised eligible studies for their quality using the JBI appraisal checklist. We used a random effect model with a 95% CI in STATA 14 to estimate the treatment coverage along care cascades. We evaluated the publication bias through funnel plots and Egger's test, both of which indicated the absence of publication bias. However, we observed significant heterogeneity; consequently, subgroup analyses were conducted, taking into account the year of publication, setting, design, and location of treatment Result the overall pooled estimates of contact coverage, intervention coverage, quality-adjusted coverage, user adherence-adjusted coverage, and outcome-adjusted coverage from 16 studies were 71% (95% CI: 60%–82%; I2 = 99.85%), 67% (95% CI: 55%–78%; I2 = 99.75%), 61% (95% CI: 46%–76%; I2 = 99.84%), 60% (95% CI: 43%–76%; I2 = 99.4%), and 56% (95% CI: 43%–68%; I2 = 99.0%), respectively. In the subgroup analysis based on study settings, studies conducted in India reported lower coverage levels compared to those in Ethiopia. Specifically, the contact coverage was 65% (95% CI: 53%–77%; I2 = 97.4%), intervention coverage was 64% (95% CI: 49%–79%; I2 = 98.3%), quality-adjusted coverage was 60% (95% CI: 41%–79%; I2 = 98.9%), and outcome-adjusted coverage was 58% (95% CI: 38%–78%; I2 = 99.02%) Conclusion The pooled estimates indicate suboptimal levels of contact coverage, intervention coverage, and quality-adjusted coverage, highlighting challenges in delivering essential services. The lower levels of user adherence-adjusted coverage and outcome-adjusted coverage suggest potential issues with treatment effectiveness and patient outcomes. Therefore, targeted interventions and appropriate resource allocation to improve healthcare access, quality, and outcomes are crucial in low-resource settings. The review protocol has been registered on the International Prospective Register of Systematic Reviews (PROSPERO), (ID: CRD42024525174)
Biostatistics · MEDLINE · Public health · Referral · Antibiotic Use and Resistance · Global Maternal and Child Health · Neonatal and Maternal Infections · Epidemiology
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| Highly cited | No |
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