Background:High maternal mortality in sub-Saharan Africa has been linked to inadequate medical care for pregnant women due to limited health facility delivery utilization. In Somalia, many births still take place at home, most often without a skilled birth attendant. This study aimed to identify the prevalence and determinants of facility delivery among pregnant women in Somalia using data from the 2020 Somalia Demographic and Health Survey (SDHS). Methods:This cross-sectional study analyzed SDHS 2020 data for 18,561 women aged 15-49 years. Descriptive statistics summarized participant characteristics and delivery location. Binary logistic regression was used to identify determinants of facility delivery. Variables with p < 0.05 were considered statistically significant, and adjusted odds ratios (AORs) with 95% confidence intervals (CIs) were reported. Results:The prevalence of facility delivery was 20.8%, indicating high utilization of home delivery. Several factors were significantly associated with increased odds of facility delivery. Women in the highest wealth had over five times higher odds of delivering at a health facility (AOR = 5.63; 95% CI: 4.56-6.97). Women who attended ANC had four times higher odds of facility delivery (AOR = 4.42; 95% CI: 3.99-4.89). Women who perceived the distance between their home and the nearest health facility as a barrier had 75% lower odds of facility delivery (AOR = 0.25; 95% CI: 0.23-0.27). Additionally, nomadic residence, high parity (≥5 children), and early marriage were significantly associated with lower likelihood of facility-based delivery. Conclusion:Facility delivery remains low in Somalia. Wealth status, ANC attendance, and perceived distance to health facilities were key determinants of facility delivery, alongside residence type, parity, and early marriage. Improving ANC coverage, enhancing birth preparedness education, and increasing access to skilled birth attendants are vital steps to reduce home delivery.
Health Information Systems (HIS) are vital for the collection, storage, analysis, and dissemination of health data to support effective decision-making and resource management at all levels of healthcare. However, despite their importance, many healthcare professionals do not effectively use routine health information, leading to missed opportunities for data-driven decisions and weakened health system performance. This study aimed to assess the utilization of routine health information and its determinants among healthcare professionals in public health facilities in the Banadir Region, Somalia. A facility-based cross-sectional study was conducted from March to June 2024 across 32 public health facilities in the Banadir Region, Somalia. A total of 405 healthcare professionals were selected using a two-stage cluster sampling technique. Data were collected using self-administered questionnaires and observational checklists developed based on the PRISM framework. The questionnaire included items assessing factors influencing RHIS use, such as the availability of training, standardization of indicators, level of supervision, and attitudes toward data utilization. Data were entered and cleaned in Excel and analyzed using SPSS version 27. Bivariable and multivariable binary logistic regression analyses were performed, with variables showing p < 0.05 in the multivariate analysis considered statistically significant. In this study, 68.1
BackgroundData quality encompasses completeness, accuracy, integrity, timeliness, and confidentiality. In many low- and middle-income countries, including Somalia, data from RHIS are often poor, limiting their usefulness for public health actions. This study assessed the quality of RHIS data and associated factors among public health facilities in the Banadir region, Somalia.MethodsA facility-based cross-sectional study was conducted from October to December 2024 across 36 public health facilities using a multistage sampling approach. Data were collected through document reviews, interviews, and observations using PRISM-based standardized tools. Data were analyzed in SPSS version 27 after checking logistic regression assumptions. Data quality was assessed by the dimensions of accuracy (≥80%), completeness (≥85%), and timeliness (≥85%). Bivariable and multivariable logistic regression analyses identified associated factors.ResultsA total of 398 healthcare workers (59.5% female) participated, yielding a 98% response rate. Overall, good-quality data were observed in 65.3% of departments. Departments in health centers were 2.7 times more likely to report good-quality data than hospitals. Feedback, refresher training, and user-friendly reporting formats were significantly associated with better data quality.ConclusionData quality across the three dimensions was scored at (65.3%). Strengthening supervision, feedback, and context-specific training can improve data reporting and management.
Coal-dependent power systems must reduce cost volatility and emissions while maintaining reliable supply under rising demand. This study assesses whether a practical transition architecture, high-penetration photovoltaic (PV) generation combined with a dispatchable coal unit and grid support, can improve techno-economic and environmental performance without sacrificing feasibility. A grid-connected PV-coal-grid hybrid system was modelled and optimized in HOMER Pro, and a sensitivity campaign was conducted by varying coal fuel price, global horizontal irradiance (GHI), and load demand to test robustness and dispatch shifts. The least-cost feasible solution within the explored design space comprises 145 MW PV and a 75 MW coal power plant with grid interaction. Under baseline conditions, the optimized system achieves a net present cost (NPC) of $632 million and a levelized cost of electricity (COE) of $0.049/kWh. Sensitivity results show that increased GHI consistently reduces NPC and COE, while coal price increases drive greater PV utilization in dispatch without undermining feasibility. Load growth increases total system cost due to higher capital and operating requirements, yet COE changes remain modest, indicating improved utilization of installed assets at higher demand levels. The optimized configuration's emissions inventory quantifies the residual environmental footprint of the least-cost reliable solution, including 429.2 million kg/yr COQ, 3.30 million kg/yr SOQ, 0.44 million kg/yr NON, 2.30 million kg/yr CO, 19.7 thousand kg/yr particulate matter, and 122 thousand kg/yr unburned hydrocarbons, reflecting reduced coal combustion through PV displacement during high-resource periods. These findings demonstrate that an optimized PV-coal-grid hybrid can deliver cost-competitive electricity, operational robustness to fuel/resource/demand uncertainty, and measurable multi-pollutant emissions mitigation, offering a realistic transition pathway for coal-reliant systems.
Microfilariae are blood parasites transmitted by hematophagous vectors, yet short-term, within-morning dynamics of the infection in wild passerines are poorly understood. This study aimed to (i) assess within-morning fluctuations in microfilariae prevalence and intensity in breeding adult village weavers (Ploceus cucullatus), and (ii) evaluate the influence of infection on host body condition (reflected in their body mass). A total of 124 birds (72 males, 52 females) were trapped in the Amurum Forest Reserve, Nigeria, using mist nets during early, mid-, and late-morning intervals. Microfilariae were detected via the buffy coat method, and body condition was estimated from body mass. Overall, 94.4% of males and 30.8% of females were infected. Contrary to our hypothesis that early-morning captures would predominantly sample filaria-free birds, prevalence and intensity peaked in mid-morning, especially in males (P < 0.05). Infected males were consistently in better condition than uninfected males, indicating trade-offs favoring reproductive investment over immune defense, whereas infected females exhibited a mid-morning reduction in body mass, likely reflecting the energetic costs of infection. These results reveal pronounced sex-biased infection patterns and highlight temporal variation in host activity and condition, with implications for sampling and understanding host-parasite interactions in wild passerines.
