A COST ANALYSIS OF COMMUNITY MANAGEMENT OF …



centercenterDaniel Mwai (PhD)Health Financing specialist Lecturer of Health Economics.University of Nairobi, Kenya.Email :mwaidaniel@Final ReportApril, 2020A COST ANALYSIS OF COMMUNITY MANAGEMENT OF ACUTE MALNUTRITION (CMAM) PROGRAM IN SOUTH SUDAN.8820090900Daniel Mwai (PhD)Health Financing specialist Lecturer of Health Economics.University of Nairobi, Kenya.Email :mwaidaniel@Final ReportApril, 2020A COST ANALYSIS OF COMMUNITY MANAGEMENT OF ACUTE MALNUTRITION (CMAM) PROGRAM IN SOUTH SUDAN.Contents TOC \o "1-3" \h \z \u Acknowledgements PAGEREF _Toc38790508 \h 2Acronyms PAGEREF _Toc38790509 \h 3Executive Summary PAGEREF _Toc38790510 \h 5Introduction PAGEREF _Toc38790511 \h 7Global context PAGEREF _Toc38790512 \h 7South Sudan context PAGEREF _Toc38790513 \h 8Rationale PAGEREF _Toc38790514 \h 9Overall Objective PAGEREF _Toc38790515 \h 10Methodology PAGEREF _Toc38790516 \h 11Results and Discussion. PAGEREF _Toc38790517 \h 15Cost drivers for unit cost for MAM and SAM PAGEREF _Toc38790518 \h 17Spatial variation of the CMAM unit costs across the states PAGEREF _Toc38790519 \h 19Conlcusions and recommendations PAGEREF _Toc38790520 \h 21limitations PAGEREF _Toc38790521 \h 23References PAGEREF _Toc38790522 \h 24Annexes PAGEREF _Toc38790523 \h 27Annex 1 PAGEREF _Toc38790524 \h 27Annex 2 PAGEREF _Toc38790525 \h 28Annex 3 PAGEREF _Toc38790526 \h 28Annex 4 PAGEREF _Toc38790527 \h 32List of Tables TOC \h \z \c "Table" Table 1. Definition of cost drivers used to disaggregate the unit cost PAGEREF _Toc38790425 \h 12Table 2. Unit Cost for delivering SAM and MAM by cost driver (USD) PAGEREF _Toc38790426 \h 16List of Figures TOC \h \z \c "Figure" Figure 1. SAM unit cost disaggregated by cost driver PAGEREF _Toc38790417 \h 17Figure 2. MAM Unit cost for children (<5 years) disaggregated by cost driver PAGEREF _Toc38790418 \h 18Figure 3. MAM Unit cost for children (PLW) disaggregated by cost driver PAGEREF _Toc38790419 \h 18Figure 4. Distribution of unit cost of SAM by State per cost driver (US$) PAGEREF _Toc38790420 \h 19Figure 5. Distribution of unit cost of MAM for children< 5 years by State per cost driver (US$) PAGEREF _Toc38790421 \h 20Figure 6. Distribution of unit cost of MAM for PLW by State per cost driver (US$) PAGEREF _Toc38790422 \h 20AcknowledgementsThe South Sudan Nutrition Cluster Coordination Team spearheaded the development of the CMAM Cost analysis. The exercise adopted a broadly consultative and collaborative approach, drawing on the knowledge, views, and insights of several individuals and organizations. They represented a wide array of nutrition stakeholders in South Sudan. The Authors acknowledge, with sincere gratitude, all those who participated in the development of the CMAM Cost analysis.??The Nutrition Cluster wants to acknowledge the financial and technical support provided by UNICEF and WFP. Special appreciation goes to the Technical Task Force comprising of individuals from the MOH, UN agencies, national and international NGOs. Sincere gratitude also goes to the Implementing Partners that took part in this exercise.?Lastly, we greatly appreciate the technical support of the Consultant, Daniel Mwai, and everyone who contributed to the development of the cost analysis from inception to finalization. Their inputs were critical in strengthening the results of the analysis. Special appreciation goes to James Lual Garang, Khamisa Ayoub (MOH); Koki Kyalo, Regina Mbochi, Qutab Alam, Hermann Ouedraogo (Nutrition Cluster); Jack Achieng (Nile Hope); Ahmed Dugsiye, Deepak Kumar, Muhammad Ali Jatoi (IMC); Mona Shaikh, Dina Aburmishan, Hussein Mahad (WFP); and Biram Ndiaye, Gilbert Dachi, Vandana Joshi (UNICEF).??AcronymsCMAMCommunity Management of Acute Malnutrition CSO Civil Society Organisation.FSNMS Food Security and Nutrition Monitoring SurveyFTS Financial Tracking System GAM Global Acute MalnutritionHNOHumanitarian Needs OverviewHRPHumanitarian Response PlanMAMManagement of Acute Malnutrition NGOsNon-Governmental Organizations OCHA Office for the Coordination of Humanitarian Affairs?OTPOutpatient Treatment Program. PLW Pregnant Lactating Women RUTF Ready to Use Therapeutic FoodsSAMSevere Acute Malnutrition SCStabilization Centres TSFPTargeted Supplementary Feeding Program UNICEF United Nations Children's Fund?UNSSC United Nations System Staff CollegeWFH Weight for Height WFPWorld Food ProgramWHO World Health Organisation Executive SummaryThe National Nutrition Cluster presents an updated unit cost analysis to provide new estimates of the unit cost of providing community management of acute malnutrition in South Sudan. The unit cost captures the actual cost of providing nutrition intervention in a complex humanitarian emergency environment characterized by economic fragility, persistent conflict, and inaccessible areas within the country for a significant proportion of the year.?The unit analysis is based on mixed methods relying heavily on expenditure methods with specific cost ingredients/drivers. These drivers include; Technical support, Capacity Building, Nutrition Supplies, Logistics (clearance, warehouse, handling, and transport), Infrastructure and Equipment, and Programme management. The analysis utilized quasi primary expenditure data collected from UN agencies and implementing partners using a customized data collection tool developed to capture spending on implementing CMAM by all partners that worked in South Sudan in 2018. A total of 871 sites offering MAM interventions and 811site for SAM were targeted with data received from 799 and 764 sites for MAM and SAM, respectively. This represents 92% and 94% response rate, respectively. In terms of the partners who responded, 40 out of 50 key implementing partners provided their data for cost analysis. Output data were extracted from the Nutrition Information System and combined with the expenditure data to estimate the unit cost.The results show the weighted average unit cost of providing SAM treatment in South Sudan was $ 358.19 per child, while that of providing MAM treatment was $ 62.80 per child. The unit cost of delivering a MAM treatment to a PLW is estimated at $ 83.99 per woman. The main cost drivers for the three programs were technical support, program management, nutritional supplies, and logistics. For SAM the key cost driver was technical support at $128.75 accounting for 35.9% of the SAM unit cost, MAM targeting children less than five years and PLW nutrition supplies was the main cost accounting for at 29.6% ($18.59) and 28.6% ($23.99) of the unit cost respectively.For the MAM program, the four main cost drivers (nutrition supplies, technical support, logistics, and program management) account for an aggregate of 91.1% of the unit cost for MAM children aged less than five years, and 91.5% of unit cost for MAM targeting PLW. Substantial economies of scale were apparent in both SAM and MAM program costs, with the unit cost of providing CMAM reducing with the increase in the program output as measured by a number of children / PLWs reached per county. The weight and size of the cost driver vary across the state, and this could be accounted for by state-specific contextual characteristics and heterogeneity in program design.This analysis has shed light on the cost of providing CMAM treatment per child within the South Sudan context. The unit costs will be of great importance toward guiding resources mobilization and allocation for nutrition programs across various players in the South Sudan nutrition space. We provide critical evidence on regional variation in the cost of offering CMAM treatment per child across various States in South Sudan. The spatial difference in cost of providing CMAM is a paramount factor when planning and budgeting for nutrition interventions due to heterogeneity across states, the variation in the cost is driven by varying terrain and topography, accessibility, security, and design of the program across different implementing partners. Failure to take into consideration spatial aspects of the cost may limit the ability of a program to realize the intended outcomes.Introduction Global context Malnutrition is one of the top nutrition-related causes of death in children under five years worldwide. It is estimated that a child with severe acute malnutrition (SAM) or moderate acute malnutrition (MAM) is twelve or three times more likely to die than a well-nourished child, respectively (Khara and Dolan, 2014). Nutrition-related factors contribute to about 45% of deaths in children under-5 years of age (WHO, 2019).?The Sustainable Development Goals were adopted in 2015 by more than 190 world leaders, enshrining the objective of ending all forms of malnutrition and challenging the world to think and act differently on malnutrition (UNSCN, 2015). To do so, the SDGs incorporated the World Health Assembly targets to reduce the proportion of children suffering from wasting to <5% by 2025 (WHO 2014). However, the proportion of wasted children has remained largely unchanged. Today, an estimated 49.5 million (7.3%) children under five worldwide suffer from wasting (UNICEF, WHO, and World Bank 2019). Described as an 'everyday emergency (Generation Nutrition, 2014)' in view of its existence in stable, development contexts as well as in humanitarian emergencies, wasting effects mostly children under five years of age, with the vast majority of cases found in low- and middle-income countries. Of these 49.5 million, 16.6 million are cases of severe acute malnutrition (SAM), and 32.9 million are cases of moderate acute malnutrition (MAM).Despite the scale of the problem, until the early 2000s, wasting appeared to be a neglected issue. Little support went towards large-scale efforts to tackle the condition, and few countries had policies for identifying and treating SAM and MAM-affected children. However, the adoption of the community-based management of acute malnutrition (CMAM) changed the public health nutrition landscape by bringing treatment out of hospitals and into the community (IFPRI, 2016). CMAM was first implemented in 2001, and based on early successes, this method has been adopted by a number of international non-governmental organizations working in emergency contexts. Currently, CMAM is internationally and unequivocally accepted as an effective approach to addressing acute malnutrition and reducing mortality in children under five years of age. The integration of CMAM program into national systems occurred as a growing demand during the series of international conferences for implementation and integration of CMAM in many countries. Now, the Integrated Management of Acute Malnutrition (IMAM) approach is predicated on early case identification and is based on the following four main components embedded in the health system: Community outreach and mobilization, Outpatient therapeutic program (OTP), Inpatient therapeutic program (ITP), and Supplementary feeding program (SFP).??CMAM programs make use of specialized nutritious foods (SNFs) such as Ready‐to‐Use‐Therapeutic Food (RUTF) and Ready‐to‐Use Supplementary Foods (RUSF), and decentralized care models have enabled community‐based treatment for most children. Besides, it is evident that the use of these SNFs has led to high recovery rates globally and in low-income environments (Isanaka et al., 2016; Max 2010). CMAM based approaches are recognized as one of the 13 "high‐impact" nutrition interventions for its potential to save lives (Bhutta et al., 2008) and are included in the package of "key interventions" promoted by the Scaling up Nutrition Movement (Horton. et al., 2010).Despite the potential for CMAM programs to provide safe, effective, and timely care, access to SAM and MAM management services remains low. Currently, less than 20 percent of children are affected by wasting and are receiving the treatment they need, because services are inaccessible or unavailable (No Wasted Lives, 2017). A fundamental obstacle to increasing program coverage is the perceived high cost of treatment. Indeed, funding falls dramatically short of projected needs to scale up the treatment of wasting. In 2015, an estimated $224 million was spent on the treatment of SAM. While estimates for costs to treat MAM are less precise, an estimated $3.6 billion a year is needed (No Wasted Lives 2017). Costs of delivering CMAM programs differ across countries and geographical regions due to heterogeneity of inputs and other structural factors of programs across the world (Isanaka et al., 2018: Save the Children, 2017). The cost variation could be due to varying program designs across regions even within the same jurisdiction, and this explains the need for robust estimation for the country and region-specific cost in order to capture the uniqueness of nutrition program based on existing context and regional characteristics.?South Sudan context In South Sudan, the cumulative effect of years of conflict, violence, and destroyed livelihoods have led to a humanitarian emergency of high proportions. The recently revitalized peace process promises to offer new opportunities in the coming years for South Sudan's women, men, and children (OCHA, 2018). The launch of the National Development Strategy 2018-2021 with the overall objective of consolidating peace and stabilizing the economy echoes the peace optimism.?South Sudan has made substantial progress in the last eight years with respect to the nutrition situation, with a proportion of children under five suffering from acute malnutrition that decreased from 22.7% in 2010 to 16.2% in 2019 (Ministry of Health and National Bureau of Statistics, 2010; and FSNMS, 2019). Hence, despite this improvement, the burden of acute malnutrition remains dire and unacceptably high. Indeed, the prevalence of global acute malnutrition of 16.2% among under-five children is over the WHO threshold for an emergency, and this translates into an expected 1,770,861 People In Need (PIN) of treatment for acute malnutrition in 2020, including 292,373 children suffering from SAM, 1,008,696 children suffering from MAM and 469,792 pregnant and lactating women (PLW) suffering from acute malnutrition.?The CMAM program is the main mechanism for the provision of treatment services for children and women with acute malnutrition. It is run by Implementing Partners, in support of the Government of South Sudan, with technical and financial assistance from UN agencies and Donors, under the coordination of the Nutrition Cluster. The Nutrition Cluster was established in 2010 in South Sudan and currently comprises 64 active partners from Government, UN agencies, donors, and national and international Non-Governmental Organizations (NGOs) supporting the implementation of nutrition interventions.?The supplies are centrally procured by the Pipeline Managers, UNICEF for SAM supplies and WFP for MAM supplies, then dispatched to Implementing Partners (IPs). In some exceptional circumstances, the Logistic Cluster is requested to support with transportation of the supplies to hard-to-reach places, including through airlifting.In South Sudan, CMAM program has progressively been scaled up, from less than 100 operational nutrition sites combined in 2013 to over one thousand sites across the country, embedded or not into health facilities (Dina et al., 2019). In 2020, SAM and MAM management services are provided through 1,133 Targeted Supplementary Feeding Programme (TSFP) sites, 1,102 Outpatient Therapeutic Programme (OTP) sites, and 89 Stabilization Centres (SC). In 95% of cases, TSFP and OTP are integrated. These sites provide a key source of both expenditure and program output data necessary to undertake cost analysis for SAM and MAM program.?RationaleIn South Sudan, the Humanitarian Needs Overview (HNO) and the Humanitarian Response Plan (HRP) are generated annually by Clusters to serve both strategic and operational guidance for programming by partners. The HNO establishes the number of people in need and the targets while the HRP outlines the strategies and activities to be implemented to reach the planned objectives. The core activities of the Nutrition Cluster are the treatment and prevention of acute malnutrition in both children (6-59 months) and pregnant and lactating women (PLW). The Nutrition Cluster HRP budget is estimated by activity-based costing (or unit-based costing). Implementing partners (national and international NGOs) rely on their own funds or grants allocated by donors either directly or through UN agencies for nutrition service delivery. A costed HRP is an excellent tool for advocacy and resource mobilization. In South Sudan, the HRP budget is often questioned, mainly due to a lack of robust and consensual unit costs for SAM and MAM treatment. A case in point was 2016 when the cost of treating a child with SAM was estimated at US$ 207, which included 9% technical assistance, 20% cross-sectoral, and 8% cost recovery. However, the cost did not include many aspects, such as contribution from Civil Society Organizations (CSOs) partners. Therefore, the SAM unit cost was revisited in 2018, more comprehensively, with a new estimate of US$ 315 per SAM child treated. While the revised unit cost was closer to some published literature, there was still no consensus among partners.Furthermore, cost drivers, such as infrastructure, human resources, equipment, supplies, logistics, and other related costs, remain unclear. The lack of clarity on the unit cost of treating acute malnutrition leads to incessant misunderstanding in budget allocations. The complex and uneven operating environment coupled with logistical constraints and operation costs, which differ from one region to another, makes costing of intervention much more challenging in South Sudan.It is therefore critical that standard unit costs for treatment of acute malnutrition are established, with breakdowns by cost driver and region to inform the development of a country-level costed plan, as well as budgetary analysis and funds allocations for the CMAM program. It is against this background that the Nutrition Cluster commissioned a cost analysis of the CMAM program, with the aim of estimating the unit cost for providing SAM and MAM management services in South Sudan.Overall ObjectiveThe purpose of this study was to:To establish the unit costs of delivering treatment services for SAM and MAM in South Sudan;?To Identify the key cost drivers for SAM and MAM treatment programs;?To analyse spatial variations of the costs of delivering treatment services for SAM and MAM.MethodologyThe CMAM cost analysis was based on mixed methods relying heavily on expenditure method with some specific ingredients being captured. The total expenditures on treatment of acute malnutrition, from January 1st to December 31st 2018, were collected from stakeholders. The unit cost was, therefore, derived as the total expenditures divided by the number of beneficiaries treated in 2018.Establishing a study team and study inception.The Nutrition Cluster sought for external expertise on health economics, nutrition programming and costing, and budget analysis. Following public advertisement of the terms of reference, applications were collected and selected, and a consultant contracted to conduct the study through remote and in-country involvement. Furthermore, a Technical Task Force was established to provide oversight on the costing exercise. The TTF include technical staff from the Nutrition Cluster, the National Ministry of Health, two UN agencies (UNICEF and WFP), two NGO, an international and a national one. The TTF was involved in all the staged of the analysis over ring quality control and country context for the analysis.Inception stagePolicy utility of empirical analysis relies heavily not only on results but also on the process used to generate the results and consensus built along the process. The inception phase of this analysis was aimed at building consensus on costing approach, data sources, data collection, and analysis approach. The key activities undertook included:Stakeholder consultation was conducted to lay out the framework that was used to undertake the analysis. The consultation involved various key players within the Nutrition terrain in South Sudan. The consultation which was led by Nutrition Cluster involved, Nutrition Cluster, Technical Task Force, Strategic Advisory Group (SAG), UN agencies, Donor Group, NGO forum, and IPs. This multi-stakeholder consultation enabled adopting consensus on a common approach to the scope of the analysis, data collection, and analysis for the costing exercise. Annex 1 provides a summary of the consultation process.?Review and discussions on programming at the national level, with exhaustive identification of cost drivers. In the inception phase, key stakeholders discussed key cost drivers to be included in the analysis based on the programming experience and need for nutrition in the country.??Preparation of data collection tool to capture necessary information to enable the generation of unit cost for SAM and MAM program, the details of the data collection, and the tool are discussed in the data section below.Orientation for relevant partners on the use of data collection template, and submission to the Nutrition Cluster.?Data collection and quality assurance Data collection toolThe CMAM cost analysis utilized quasi primary data that was collected using a template developed through consultation with the key stakeholders as outline in Annex 1. The model aimed at collecting data from IPs who are delivering nutrition services across South Sudan. The tools captured details on;The period for the analysis, the time boundary, was January to December 2018.Location: Area where services are offered specific State and County.Scope: The data to be collected covered; MAM in children under five years, Acute Malnutrition in PLW; SAM with and without complication in children under five years.Cost Drivers: The template captured expenditure essential cost drivers per each of the partners by county of operation. The cost drivers captured were selected and agreed through intensive stakeholder’s consultations process spearheaded by the Nutrition Cluster. The selected cost drivers and their definitions are presented in table 1.Table SEQ Table \* ARABIC 1. Definition of cost drivers used to disaggregate the unit costCost driverDefinitionTechnical supportSalaries and related costs, this does not include staff cost at regional and head office level.Capacity Building Capacity development, including training and equipment of nutrition staff, and community volunteer services cost. Nutrition Supplies ??Supplementary and Therapeutic food cost (RUSF, RUTF, therapeutic milk), medicines, anthropometric equipment, including freight costLogistics Country Logistics (clearance, warehouse, handling and transport)Infrastructure and EquipmentAny additional capital investment for nutrition in the year.Programme managementCost of running regional office, country office, and HQ for implementing partners and UN agencies.OtherOther costs not classified above.Source: consensus from key stakeholders.Technical support, Capacity Building, Nutrition Supplies, Logistics (clearance, warehouse, handling, and transport), Infrastructure and Equipment, and Programme management.?Data on donor funding to different implementing partners also collect to triangulate the data collected from the implementing partners.?Expenditure DataThe CMAM cost analysis that utilized quasi primary data that was collected UN agencies and IPs using a data collection tool/ template described above. Data collection targeted all IPs spread across 79 counties covering all ten states in the country. The data collection template was shared by Nutrition Cluster to 50 Partners that have been operational in 2018, with instructions on how to populate the model based on their level of activities and geographical coverage. Nutrition Cluster also offered to backstop support to IPs, by virtually and physically guiding the IPs to fill in the needed expenditure pleted data was received from 40 IPs out of 50 who were expected to provide the expenditure data based on partners per site per each of the counties the partner had a presence in. The IPs response rate was 80%; however, some IPs have more comprehensive coverage, both program and geographical, which merit the use of a number of sites as a better estimate for response rate. A total of 871 sites offering MAM interventions and 811site for SAM were targeted, with data received from 799 and 764 sites for MAM and SAM, respectively. This represents 92% and 94% response rate, respectively. Total spending for the year 2018 on nutrition by each partner was recorded retrospectively. This recording was then disaggregated by critical ingredient/cost categories necessary for policy and planning for a nutrition program. The cost categories were essential to evaluate the cost drivers of the unit cost and to observe the spatial distribution of the cost within South Sudan. The cost categories captured were selected and agreed through intensive stakeholders' consultations process spearheaded by the Nutrition Cluster. This enables the selection of cost categories necessary to guide nutrition programming in the country.Program output dataThe denominator that was used to estimate the unit cost was based on partner outputs per county, as reported in the Nutrition Information System (NIS). NIS is used for reporting nutrition program outputs in South Sudan by partners working across the country. Nutrition Cluster assisted in extracting the outputs for various partners across the country, and this data was combined with the expenditure data to estimate the unit cost.Data AnalysisThe expenditure method used for this estimate is merited estimating the actual cost of implementing the program based on the current practice. It is also faster and cheaper than a micro-costing/Activity-based costing method and feasible to implement in a data constrained environment like in South Sudan. The unit costs defined are Incremental unit costs, defined as additional costs of delivering SAM and MAM programs per beneficiary. Unit costs were calculated based on the implementation timeframe covering the year 2018.The data analysis was excel-based; first data received from the IPs were captured in one workbook. The data obtained per each partner included expenditure on nutrition per each of the cost drivers per county. The cost drivers provided in the county by the partners per program was captured, and it includes; SAM, MAM for children less than 5 years, and PLW. Specific program outputs weighted the data on expenditure per partner per county for specific partners per county to provided unit cost for each of the programs per county. The expenditure per the cost drivers is weighted by the output per county to generate a unit cost per county. In case of the presence of outliers in the unit cost by cost categories, the data were smoothed using the Median. The unit cost per county per specific cost driver, per IP, are aggregated to aggregate weighted unit cost for each State for SAM and MAM programs. The logistic cost was estimated based on three aspects, the logistic cost that accrues to the implementing partner directly, to pipeline Managers (UNICEF and WFP), and logistic cost attributable to the nutrition program incurred by the Logistic Cluster.Data and Results Validation Process.Validation of data and results is critical for the acceptability of the results by key stakeholders and policymakers. To validate the findings of the data collected in the inception process, the data and results were presented to the stakeholders. Callbacks were made to the Implementing partners who provided the data where discrepancy or where data were inconsistent, enabling data cleaning pre-analysis. The validation process involved the Nutrition Cluster, the Technical Task Force, the Strategic Advisory Group (SAG), UN agencies, and Donor Group. This multi-stakeholder validation process entailed presenting the preliminary data and the results to each of these platforms of stakeholders, to get their comments, which were further used to strengthen the analysis and enable consensus on the results. The draft report was also shared widely with the stakeholder validation, their review and feedback was key in improving the policy utility of the analysis and acceptability of the results presented in the final report. RESULTS AND DISCUSSION.The weighted average unit cost of providing SAM treatment in South Sudan was $ 358.19 per child, while that of providing MAM treatment was $ 62.80 per child. The unit cost of delivering a MAM treatment to a PLW is estimated at $ 83.99 per woman. The overall costs provided here are within the range of some previously reported estimates despite variation methods applied. The results reported here are in line with past findings, which estimated the cost of delivering SAM treatment in eight CMAM programs in the Sahel (Niger, Mali), East Africa (Kenya), and the Middle East (Yemen). This is to range between $120 and $800, averaging $300 per child treated, including shared costs of country management, and $235, excluding the shared costs of country office management (IRC, 2018).?According to Bachmann, costs of ambulatory community-based treatment of SAM in different programs in Africa ranges between US$46 and $453 per child, depending on the type of care provided and the costing methods used (Bachmann, 2009). However, the result reported here seems lower than the cost reported from Ethiopia, with a low cost per child treated at $284.56 for inpatient phase and $134.88 for outpatient phase, i.e., a total of $419.44 (Tekeste, 2012), and from rural Mali, with an estimate of $442 per SAM child treated as an outpatient (Rogers, 2018). Conversely, it seems higher than costs reported elsewhere, $165 or $170 for Bangladesh (Puett et al., 2013; Kakietek et al., 2018), $ 85 in Afghanistan (Collins, 2016).Variations in unit cost can be driven by various factors, mainly:?The perspective of the cost that can include or not include both institutional cost and opportunity cost incurred by populations, start-up, and recurrent costs, and encompass or not inpatient and outpatient SAM treatment;?Secondly, the cost drivers considered that can limit the cost to the operational ingredient or include costs due to management and technical assistance;?Thirdly, the institutional context, i.e., the level of integration of the nutrition component into the existing health system; and fourthly the implementation period, cost being subjected to cost inflations with time. The current study was conducted in a context of weak integration of nutrition and health, limited to the institutional cost, included all cost drivers up to management and technical assistance cost, and aggregated both in and outpatient treatment for SAM. References to MAM treatment are scarce; the estimate for Bangladesh is at $48 for treating one case of MAM (Katietek et al., 2018). In general, the unit cost for SAM treatment is higher than the unit cost for MAM treatment, 5.7 times higher in South Sudan, 3.5 times higher in Bangladesh. Indeed, this could be accounted for by the number of children reached and heterogeneity in the program design and country-specific characteristics.The unit cost of delivering SAM and MAM disaggregated by cost drivers is presented in table 2.Table SEQ Table \* ARABIC 2. Unit Cost for delivering SAM and MAM by cost driver (USD)Cost driver SAM MAM <5YrsMAM- PLWTechnical support $ 128.31 $ 11.34 $ 19.82 Capacity Building $ 18.46 $ 2.83 $ 3.65 Nutrition Supplies $ 68.43 $ 18.59 $ 23.99 Logistics $ 37.03 $ 11.29 $ 14.57 Infrastructure and Equipment $ 11.55 $ 2.09 $ 2.69 Programme management $ 93.19 $ 16.01 $ 18.44Other $ 0.84 $ 0.65 $ 0.84 Total $ 358.19 $ 62.80 $ 83.99 Source: Authors estimation.Cost drivers for unit cost for MAM and SAMThe weight of each of the cost drivers in the overall unit cost for the three programs is further estimated to give insights into various cost drivers. The results show that the main cost drivers for the unit cost across the three programs are technical support, nutrition supplies, and program management, which total 81%, 73%, and 75% of the cost of SAM treatment, MAM treatment, and PLW treatment, respectively.??Figure1 shows the weight of various cost drivers for the SAM program.Figure SEQ Figure \* ARABIC 1. SAM unit cost disaggregated by cost driverSource: Authors estimationA look into cost drivers of SAM treatment shows technical support is the highest contributing cost driver accounting for 36% of the unit cost. While program management accounts for 26%, nutrition supplies are 19%, logistics is 11%, capacity building is 5%, and infrastructure and equipment is 3%. These results are, to a more considerable extent, consistent with Isanaka et al., 2016, who found the primary cost driver of providing SAM program per child to be nutrition supplies, technical support, infrastructure, and logistic. This shows the existence of heterogeneous nutrition programs across countries that count be attributed to variation in the program design and country-specific social, economic, and political characteristics.?Since nutrition program in South Sudan is financed mainly by donors and their implementing partners, with low integration into the government health system. The need for technical assistance to manage the program is a key driver across all the programs, especially since these programs are not integrated but quasi parallel to the health system.Figure 2, below, shows the MAM unit cost for children (<5 years) disaggregated by cost drivers. It highlights the contribution of various cost drivers to an overall unit cost of delivering the MAM program to children less than 5 years old. While Figure 3 shows the weight of cost drivers in the overall unit cost of delivering the MAM program targeting pregnant and lactating mothers in South Sudan.?For MAM (<5years) program, the cost drivers and their contribution to the overall unit cost are as follows: Nutrition supplies 30%, program management 25%, technical support 18%, and logistics 18%. Infrastructure and Equipment, Capacity Building, and another cost not elsewhere classified accounted for approximately 9% of the unit cost.?Figure SEQ Figure \* ARABIC 2. MAM Unit cost for children (<5 years) disaggregated by cost driverSource: Authors estimationIn relation to the MAM program for PLW, the cost driver's contribution to the overall unit cost follow the same structure as in MAM under 5, with nutrition supplies accounting for 29, program management 22%, technical support 24%, and logistics 17%. Capacity building, Infrastructure, and Equipment account for less than 8% of the unit cost.Figure SEQ Figure \* ARABIC 3. MAM Unit cost for children (PLW) disaggregated by cost driverSource: Authors estimationSpatial variation of the CMAM unit costs across the statesTo assess the geospatial variability of the unit costs, the study further disaggregated the estimated costs by each of the ten former states in South Sudan. The analysis shows there is variation in the unit cost by State. The unit cost for SAM treatment ranges from $227.3 in Lakes state to $449.2 in Jonglei state (see Figure 4).Figure SEQ Figure \* ARABIC 4. Distribution of unit cost of SAM by State per cost driver (US$)Source: Authors estimationThe unit cost of MAM treatment for children less than five years range from $ 44.8 in Northern Bahr el Ghazal state to $77.9 in Central Equatorial state with a weighted average of $ 62.80. The contribution of the each of the cost driver to the total unit cost is shown in Figure 5. Figure SEQ Figure \* ARABIC 5. Distribution of unit cost of MAM for children< 5 years by State per cost driver (US$)Source: Authors estimationThe unit cost for providing MAM programs for pregnant and lactating women ranges from $ 65.2 in Northern Bahr el Ghazal state to $107.8 in Central Equatorial state with a weighted average of $ 83.99. The cost driver for each of the state are presented in Figure 6. Figure SEQ Figure \* ARABIC 6. Distribution of unit cost of MAM for PLW by State per cost driver (US$)Source: Authors estimationIn contrast to IRC, 2018 analyses, relatively large variation exists in the unit cost for MAM and SAM programs across states. This supports the idea that, at least for SAM and MAM programs, contextual factors—such as population density, burden of acute malnutrition, program design, program reach based on the number of children treated, transport, and logistic considerations have a massive effect on the unit cost of the program states in the same country.?Substantial economies of scale were exhibited and reflect within the unit costs analysis, with per child costs decreasing with a number of children reaches per State. Besides, there is an association between the cost of delivering the three programs per State where a state with a high unit cost of SAM has a high unit cost of MAM both for under five years and PLW. This could be explained by variation in logistic cost and other contextual factors unique to each of the states.?Summary and ConlcusionThis study provides empirical estimates of unit cost for SAM and MAM management in South Sudan, focusing on SAM for children under five years and MAM for children under five years and PLW with acute malnutrition. The CMAM cost estimated presents the actual cost of providing nutrition intervention in a complex humanitarian emergency environment characterized by economic fragility, persistent conflict and inaccessible areas within the country for a significant proportion of the year, and a fragile health system. The terrain of nutrition programming in South Sudan also presents a case of high burden, low‐income setting with donor funding accounting for the largest share of nutrition financing.We found the overall cost per child treated for SAM to be $358.19, while that of providing MAM treatment was $ 62.80 per child. The unit cost of delivering a MAM treatment to a PLW is estimated at $ 83.99 per woman. For the MAM program, there are four main cost drivers, and these are nutrition supplies, technical support, logistics, and program management that dominated unit costs. Substantial economies of scale were apparent in both SAM and MAM program costs, with the unit cost of providing CMAM reducing with an increase in the program output as measured by the number of children reached per county.The available cost analyses are inconsistent from a cross country perspective; this could be attributed to unique country characteristics. Despite varying costing methods and study designs among available studies, the overall cost provided here falls under upper middle bound of previously reported estimates ($120 to $800, (Isanaka et al., 2016, IRC, 2018, Bachmann, 2009, Concern Worldwide, 2007, Gabo laud, 2004, Puett et al., 2013, Tekeste et al., 2012, Wilford, Golden, and Walker, 2012)). Our estimate reflects current costs within the context of a nutrition program implemented mostly under humanitarian response. It may reflect lesser efficiency attributable to operational experience, program scale, and more precise the costing method targeting both direct and indirect costs required for SAM and MAM treatment in South Sudan. Essential differences in costs between contexts may arise from differences in the services offered, local transport infrastructure, and patient mix.While CMAM has been merited as a safe and cost‐effective approach in the management of malnutrition, efforts to scale up treatment within a humanitarian response and resource-constrained settings are perceived to be hampered by the high cost of providing nutrition interventions (Isanaka et al., 2016). This underpins the importance of establishing the actual cost of implementing the CMAM program not only to guide resources mobilization from both domestic and external sources to scale nutrition programming in the country. Within the South Sudan nutrition environment, there is limited empirical evidence on the cost of CMAM program that captures the actual country context in specific and the same is lacking for countries that are implementing nutrition programs under humanitarian conditions in the region. The few available studies are limited in the scare and have not looked at the whole CMAM program, but have mainly targeted the SAM program.?In conclusion, we present updated empirical estimates of SAM and MAM treatment costs for children less than five years and PLW that substantially represent the current actual cost in the South Sudan context. This analysis has shed light on the cost of providing CMAM program per child within the South Sudan context, will be of great importance toward guiding resources mobilization and allocation for nutrition programs across various players in the South Sudan nutrition space, including the Nutrition cluster. The evidence contained in this analysis will provide critical evidence on regional variation in the cost of providing CMAM treatment per child across various States in South Sudan. The spatial difference in cost when providing CMAM is a paramount factor when planning and budgeting for nutrition interventions. This difference is due to the heterogeneity in regions in terms of terrain and topography, accessibility, security amount other factors the affect implementation of the program, and failure to take into consideration spatial aspects of the cost may limit the ability of a plan to realize the intended outcomes.limitationsThis analysis has several limitations. First, the cost analysis is based on expenditure methods that rely on assessment and scope of activities or interventions implemented. This makes this method to be independent of operational factors. Second, the cost estimates do not include health system costs despite there being a continuous investment in the health system over time and capture incremental unit cost based on periodical investment in the SAM and MAM programs in S. Sudan. Third, the analysis used a provider's perspective, which not incorporate the economic impact on households. Household costs are relevant for sustainability and equity, but could not be quantified in this analysis. A societal perspective would have allowed for the most inclusive perspective possible, incorporating the potential benefits, harms, and costs for all parties involved, that is, household, health system, and provider services. Fourth, scale and outputs of the programs have an effect on the unit cost with programs with lower outputs reporting high unit costs despite having low expenditure in absolute terms. Five, the analysis has used cross-section data set collected for one year; this limits the analysis for comparing the trend in the unit cost over time.References Bachmann, M. O. (2009). Cost-effectiveness of community‐based therapeutic care for children with severe acute malnutrition in Zambia: Decision tree model. Cost-Effectiveness and Resource Allocation 7, 2.Bhutta, Z. A., Ahmed, T., Black, R. E., Cousens, S., Dewey, K., Giugliani, E., Shekar, M. (2008). What works? Interventions for maternal and child undernutrition and survival. Lancet, 371, 417–440.Black, R. E., Victoria, C. G., Walker, S. P., Bhutta, Z. A., Christian, P., de Onis, M., … Uauy, R. (2013). Maternal and child undernutrition and overweight in low‐income and middle‐income countries. Lancet, 382, 427–451.Briend A and Prinzo Z.W. 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World Health Organization, the World Food Program, the United Nations System Standing Committee on Nutrition, and the United Nations Children's Fund, Geneva.AnnexesAnnex 1Consultation process. Nutrition cluster:?Conducted initial meetings with the nutrition cluster to discuss feasible costing approaches and costing models for the assignment. The criteria considered were the Bottom-up approach and top-down approach, while the costing models discussed where ingredient, expenditures method, and mixed-method (combining ingredient and expenditure method). The consensus was made to focus on an approach that is feasible based on the availability of data and time constraints without losing sight of the utility of the end product in S. Sudan nutrition Landscape. A discussion of the draft data collection tools was held with the production of 3 data collection tools, as follows (i) Implementing partners tool; (ii), Donor tool; and (iii) U.N. agencies tool.?Nutrition cluster and technical task force:?Further consultation was done with Nutrition Cluster, and Cost Analysis Technical Task Force on draft tools to build consensus on the data collecting tools and possible sources of data. Inputs from consultation with the task force were used to improve data collection tools in readiness to further discussion and sharing with the other key stakeholders. Besides, the consultation leads to the identification of six cost drivers that would form the basis for disaggregating the costing data.??Strategic Advisory Group (SAG):?A meeting was held to with the SAG to bring the members to speed on progress made towards and the critical steps on cost analysis. The members were taken through the costing approach to be used, the draft tools, and the expectation in terms of the cost drivers. The members were also briefed on potential data sources and data collection process. They reviewed the tools and gave views to necessary to make it feasible to capture necessary data for costing.??United Nations Agencies:?After consultation and technical inputs from the Nutrition cluster and Cost Analysis Technical Task Force, a meeting was held with the U.N. agencies to brief them and update on the approach proposed for data collection, analysis, and potential sources of the data. Specific meetings were held with UNICEF and WFP, who play a crucial role in the implementation of the nutrition program in South Sudan. The meeting also entailed taking agencies through the approach to be used for data collection, analysis, and disaggregation of unit cost data. Support from the agencies also needed to populate the U.N. agency tools and evaluation of the feasibility of being able to capture data per the required format and detail. The views and feedback were used to improve and fine-tune the tools.?Donor Group:?Meeting was held with the donor group to brief them and get buy-in for the whole exercise. The donor groups were taken through the approach, the data needs, and the policy utility of the results of the cost analysis.??NGO forum:?The last meeting was held with the NGO forum, to introduce the costing exercise the approach and data needs. The NGOs present in the meeting were taken through the implementing partner tool for data collection, which they were expected to populate. The main ideas were to assess the feasibility of completing the data and the ability to capture data per each of the identified cost drivers. Their view and sentiments were captures to develop a final costing tool in readiness for data collection.Annex 2List of participating organizations.ACEMCordaidMalaria ConsortiumACFCRSMedairACROSSCUAMMNHDFAFOD SSDAIPIAFSSGOALPUIAMREFGREDORIARCHCORMFARTHelpSACAVSIHLSSCICAREIHOSPCASS-NNGOIMCSSUHACCMIRCTearfundCHDIslamic ReliefUNIDOCMAJAMUNKEACMDJDFWRCMMBJohanniterWVIConcernMaCDAAnnex 3Description of cost input per each of the cost driverSalaries and related cost at county levelCapacity building and Volunteer servicesSupplements and Therapeutic foodMedical and non-medical supplies?Technical staffStaff attendance at CMAM trainingRUTFMedical treatment of inpatent SAMNutrition Manager/Specialist/Coordinator/OfficerStaff attednace at ITP trainingRUSFCooking and feeding utensils/kitsCMAM Manager/Specialist/Coordinator/OfficerStaff attendance at MIYCN trainingCSB++WASH kitsMIYCN Manager/Specialist/Coordinator/OfficerCMAM training conducted for organization staffF100/F75Long lasting insecticide treated net Nurse/Nurse AssistantITP training conducted for organization staffOral Rehydration solutionsDrugs and supplements used to manage SAM and MAM without complications eg Antibiotics, Dewormers, Micro-nutrient supplements Nutrition AssistantsMIYCN training conducted for organization staffOtherRoutine medicationM and E and related costs- may include M and E manager/ coordinator/ officer, assistant etc / surveillance manager/ coordinator/ officer/ NIS reporting personnel/ Programme support officers etcCMAM training conducted for organization CNVAssessment, Monitoring & Evaluation Costs- we highlight that this covers SMART surveys, KAP surveys and other kinds of assessments, including consultancy services related to the assessmentsMIYCN training conducted for organization CNVOtherVisibility material that includes T-shirts, Caps, JacketsJob Aids and HandoutsMonitoring and reporting toolsIncentives for CNVTransport and LogisticsInfrastructure and equipmentCounty-level Management costTransport CostInfrastructureStaff salaries and related costMotor Vehicles (Purchase)Shelter/waiting bayNon-technical staffBicycles for CNVsStore for suppliesHuman resource/ administration and related staff- Human resource manager/ coordinator/ manager/ office/ assistant etcTruck rentalScreening and triage/consultation areaFinance and related staff-Finance manager/ coordinator/ office/ assistant/ Grants manager/ office/ Audit manager / officer etcTruck running costsMinor renovation of nutrition sitesICT/Communication and related staff-ICT manager/office etcLight vehicles rentalAnthropometric and medical equipment Supply chain/ procurement/ logistics and related staff- supply chain/ procurement / logistics managers/ officers/ storekeeper/ warehouse staff etcLight vehicle running costsARI Timer Security and related staff-could be managers, officer, coordinators etcOther vehicle rentalHeight boardOperations and related staff- eg areas manager/ area/ office coordinator/ Head of field office etcOther vehicle running costHeight sticks (87.0cm for U2 and 110.0cm for U5)Communication and advocacy staffBoat transportationMUAC tapes under fiveOffice Rent and Running costsLocal and international travelAdult MUAC tapesRental of facilityLocal transportation of project materialsSalter scaleUtilitiesLoading/offloading of project materialsBaby scalesCommunications feesFlight ChartersDigital scaleAdministrative suppliesLocal transport, In country Flights Weighing pantsOutsourced servicesContracted transportDigital thermometerOutsourced servicesStorageBP apparatusStationariesHandling, casual labour (double handling)StethoscopeRuler, Eraser, Pencils, Marker pens, Ball point pensWarehouse rental / CostsHygiene and Sanitation requirementNote books, printing papers and Box filesPalletsLatrine and Hand washing stationsScissors, Paper punch, Calculator, Stapler & staplesCleaningPlastics cups, Teaspoon, medicine cupsFumigationCleaning Buckets and Container for drinking waterCasual labourer / storage sectionIncinerator, Trash bin and Plastic bootsFood Mgmt & Transformation ServicesMop, Brooms, Plastic gloves, Scrubbing and Cob web brushRebaggingFurnitureReconditioningChairs, Benches, TablesProvision of empty bags/tins/jerry cans, etc.Plastic sheets and matsOther Delivery CostsComputer and communications equipmentConsumablesMedical equipmentCommercial service feesCamp SuppliesDistribution costsOthersVehicles maintenance Filing SystemOtherCMAM databaseWeighing scaleCalibrated container to measure rationAnnex 4Program output per state. Name of the StateSAM with complicationSAM without complicationMAM<5yrsMAM PLW Central Equatorial1,184 9,005 24,618 14,390 Eastern equatorial371 17,480 39,795 34,725 Jonglei1,208 36,301 71,234 76,191 Lakes1,297 24,658 42,025 41,247 Northern Bahr el Ghazal913 29,251 61,693 55,647 Unity824 26,267 51,853 39,294 Upper Nile468 11,121 19,149 10,486 Warrap1,352 24,039 66,286 55,143 Western Bahr el Ghazal282 9,608 21,072 15,125 Western equatorial607 10,901 18,148 13,089 Grand Total8,506 198,631 415,873 355,337 ................
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