SummaryBackground3 years before the 2015 deadline, Ethiopia achieved Millennium Development Goal 4. The under-5 mortality decreased 69%, from 205 deaths per 1000 livebirths in 1990 to 64 deaths per 1000 livebirths in 2013. To understand the underlying factors that contributed to the success in achieving MDG4, Ethiopia was selected as a Countdown to 2015 case study.MethodsWe used a set of complementary methods to analyse progress in child health in Ethiopia between 1990 and 2014. We used Demographic Health Surveys to analyse trends in coverage and equity of key reproductive, maternal health, and child health indicators. Standardised tools developed by the Countdown Health Systems and Policies working group were used to understand the timing and content of health and non-health policies. We assessed longitudinal trends in health-system investment through a financial analysis of National Health Accounts, and we used the Lives Saved Tool (LiST) to assess the contribution of interventions towards reducing under-5 mortality.FindingsThe annual rate of reduction in under-5 mortality increased from 3·3% in 1990–2005 to 7·8% in 2005–13. The prevalence of stunting decreased from 60% in 2000 to 40% in 2014. Overall levels of coverage of reproductive, maternal health, and child health indicators remained low, with disparities between the lowest and highest wealth quintiles despite improvement in coverage for essential health interventions. Coverage of child immunisation increased the most (21% of children in 2000 vs 80% of children in 2014), followed by coverage of satisfied demand for family planning by women of reproductive age (19% vs 63%). Provision of antenatal care increased from 10% of women in 2000 to 32% of women in 2014, but only 15% of women delivered with a skilled birth attendant by 2014. A large upturn occurred after 2005, bolstered by a rapid increase in health funding that facilitated the accelerated expansion of health infrastructure and workforce through an innovative community-based delivery system. The LiST model could explain almost 50% of the observed reduction in child mortality between 2000 and 2011; and changes in nutritional status were responsible for about 50% of the 469 000 lives saved between 2000 and 2011. These developments occurred within a multisectoral policy platform, integrating child survival and stunting goals within macro-level policies and programmes for reducing poverty and improving agricultural productivity, food security, water supply, and sanitation.InterpretationThe reduction of under-5 mortality in Ethiopia was the result of combined activities in health, nutrition, and non-health sectors. However, Ethiopia still has high neonatal and maternal morbidity and mortality from preventable causes and an unfinished agenda in reducing inequalities, improving coverage of effective interventions, and strengthening multisectoral partnerships for further progress.FundingBill & Melinda Gates Foundation and Government of Canada.

BackgroundDisparity in resource allocation is an issue among various health delivery units in Ethiopia. To sufficiently address this problem decision-makers require evidence on efficient allocation of resources. Therefore, the purpose of this study was to assess the technical efficiency of primary health care units providing neonatal health services in Southwest Ethiopia.MethodsTwo-stage data envelopment analysis was conducted based on one-year (2016/17) data from 68 health posts and 23 health centers in Southwest Ethiopia. Primary data were collected from each of the facility, respective district health offices and finance and economic cooperation offices. Technical efficiency scores were calculated using data envelopment analysis software version 2.1. Tobit regression was then applied to identify determinants of technical efficiency. STATA version 14 was used in the regression model and for descriptive statistics.ResultsBy utilizing the best combination of inputs, eight health posts (11.76%) and eight health centers (34.78%) were found to be technically efficient in delivering neonatal health services. Compared with others included in the analysis, inefficient health delivery units were using more human and non-salary recurrent resources. The regression model indicated that there was a positive association between efficiency and the health center head’s years of experience and the facility’s catchment population. Waiting time at the health posts was found to negatively affect efficiency.ConclusionsMost of health posts and the majority of health centers were found to be technically inefficient in delivering neonatal health services. This indicates issues with the performance of these facilities with regards to the utilization of inputs to produce the current outputs. The existing resources could be used to serve additional neonates in the facilities.

Ethiopia's recent improvements in health outcomes benefited from the large increase in development assistance for health received in recent years, most of which supported its primary care system. Increased domestic resource mobilization for health will be needed to sustain progress given recent and likely future declines in external support. We estimate a projection model of Ethiopian government domestic resource mobilization potential compared with future health care delivery costs in order to assess Ethiopia's ability to finance its planned primary health care system. For the period of Ethiopia's current five-year health sector plan (2016-2020), the projection model indicates that if real external resources remain at the levels of 2011, domestic resource mobilization may only provide half of the estimated funds needed. Including out-of-pocket spending currently captured as retained user fees, Ethiopia is more likely to successfully finance continued delivery of primary care. Over 20 years, 2016-2035, the future sustainability of primary care services without increasing contributions from households will depend largely on significant economic growth and more government funding for primary care. Our modeling suggests that Ethiopia can substantially support further development of primary care services, even in the face of declining external support. However, it is unlikely to achieve its goals solely through "business as usual." Ethiopia is already moving forward with timely adoption of sound strategies to maintain progress. External partners should support these trends to enable transition plans to greater domestic funding with minimal disruption to positive progress that has been and is being made.

Multisectoral approaches are central to the global Scaling Up Nutrition (SUN) movement and the Sustainable Development Goals. Nepal joined SUN in 2011 and approved the first 5-year Multisectoral Nutrition Plan (MSNP) in 2012, covering 2013-2017. This mixed methods study draws on organizational network analysis (ONA) and qualitative interviews with a sample of 22 organizations to examine (1) levels of engagement and network dynamics among government sectors and development organizations and (2) milestones and processes in the development and implementation of Nepal's MSNP. Findings suggest that the development of the MSNP was related to the high density of organizational connections; the leadership role of the Nepal's National Planning Commission and the National Nutrition and Food Security Secretariat; and the bridging roles played by a few government ministries and UN agencies that linked organizations that did not have direct relationships with each other. Specialized roles were observed for the three types of working relationships: policy dialogue, strategic planning and implementation. Partners were less connected on MSNP implementation than for policy dialogue and strategic planning, which may have constrained collaborative scale-up efforts. The Ministry of Agricultural Development, in particular, was the conduit for connecting non-health sectors into the broader network. Our study offers insights into the structure and dynamics of multisectoral planning in Nepal. It also contributes to a small but growing literature that illustrates how ONA can be applied to measure and use network results to elucidate the processes for strengthening multisectoral planning and implementation of nutrition-specific and nutrition-sensitive interventions.