Assessing development assistance for child survival between 2000 and 2014: A multi-sectoral perspective

Background: The majority of Countdown countries did not reach the fourth Millennium Development Goal (MDG 4) on reducing child mortality, despite the fact that donor funding to the health sector has drastically increased. When tracking aid invested in child survival, previous studies have exclusively focused on aid targeting reproductive, maternal, newborn, and child health (RMNCH). We take a multi-sectoral approach and extend the estimation to the four sectors that determine child survival: health (RMNCH and non-RMNCH), education, water and sanitation, and food and humanitarian assistance (Food/HA). Methods and findings: Using donor reported data, obtained mainly from the OECD Creditor Reporting System and Development Assistance Committee, we tracked the level and trends of aid (in grants or loans) disbursed to each of the four sectors at the global, regional, and country levels. We performed detailed analyses on missing data and conducted imputation with various methods. To identify aid projects for RMNCH, we developed an identification strategy that combined keyword searches and manual coding. To quantify aid for RMNCH in projects with multiple purposes, we adopted an integrated approach and produced the lower and upper bounds of estimates for RMNCH, so as to avoid making assumptions or using weak evidence for allocation. We checked the sensitivity of trends to the estimation methods and compared our estimates to that produced by other studies. Our study yielded time-series and recipient-specific annual estimates of aid disbursed to each sector, as well as their lower- and upper-bounds in 134 countries between 2000 and 2014, with a specific focus on Countdown countries. We found that the upper-bound estimates of total aid disbursed to the four sectors in 134 countries rose from US$ 22.62 billion in 2000 to US$ 59.29 billion in 2014, with the increase occurring in all income groups and regions with sub-Saharan Africa receiving the largest sum. Aid to RMNCH has experienced the fastest growth (12.4%), followed by aid to Food/HA (9.4%), education (5.1%), and water and sanitation (5.0%). With the exception of RMNCH, the average per capita aid disbursed to each sector in the 74 Countdown countries was smaller than in non-Countdown countries. While countries with a large number of child deaths tend to receive the largest amount of disbursements, non- Countdown countries with small populations usually received the highest level of per capita aid for child survival among all 134 countries. Compared to other Countdown countries, those that met MDG 4 with a high reliance on health aid received much higher per capita aid across all sectors. These findings are robust to estimation methods. Conclusions: The study suggests that to improve child survival, better targeted investments should be made in the four sectors, and aid to non-health sectors could be a possible contributor to child mortality reduction. We recommend that future studies on tracking aid for child survival go beyond the health sector and include other sectors that directly affect child survival. Investigation should also be made about the link between aid to each of the four sectors and child mortality reduction.

The definition of development assistance for child survival was built upon an influential and widely cited conceptual framework, proposed by Mosley and Chen [18], for the study of child survival in developing countries. The basic idea of the Mosley-Chen framework was that all background (social, economic, cultural, and health system) variables impacted child survival through a set of proximate determinants. Though the proximate determinants in different studies varied, the main categories included maternal health and education, environmental contamination (e.g., food security, water and sanitation), nutrient deficiency (calories, protein, micronutrients), and medical services (especially the RMNCH) [18–23]. Existing evidence from developing countries provided solid ground for the model and demonstrated that addressing the complexity of child mortality required joint and integrated efforts to improve these categories. Studies in developing countries showed that expanding access to primary and secondary schools greatly improved parental or maternal education and therefore improved child health outcomes [24]. In Zimbabwe, for example, an additional year of maternal secondary education was associated with 21% reduction in child mortality [25]. Unsafe drinking water and lack of sanitation accounted for 88% of global death from diarrhea [26]—a leading cause of death for under-five children [27]. Increasing access to clean water and sanitation effectively reduced child mortality and led to, for example, a 26% drop in child mortality in the poorest areas in Argentina [28]. WHO identified that about 45% of all child deaths were linked to malnutrition [27] and better nutrition for both mothers and children significantly reduced child mortality [29]. Based on the conceptual model and supporting evidence, our study defined development assistance for child survival as aid disbursed to proximate determinants: medical care (especially RMNCH); food, food security, and humanitarian assistance; water and sanitation; and primary and secondary education (Fig 1). According to this framework, aid to other sectors, such as agriculture or industry, operated through the proximate determinants to affect child survival, and therefore, was not included in our estimation. Measuring proximate determinants with the four areas was not exclusive, which is a limitation of this strategy. It is worth noting that the impact of aid to education on child survival through improving parental or maternal education may have a significant time lag. There is no commonly-accepted approach on how to measure development assistance for RMNCH. Previous studies divided RMNCH into various categories and used different methods to classify the services in these categories. For example, the Institute for Health Metrics and Evaluation (IHME) provided mutually exclusive estimates on child care and maternal care, with little justifications offered [16]. Estimates on child and maternal care, produced by The Countdown Initiative, excluded projects on reproductive health and included a portion of expenditure on infectious disease control and health system strengthening [8–13], but their allocation of funds to child and maternal care relied on either assumptions or scanty evidence, which raised concern over their estimation [12, 17]. In contrast to the differential approach adopted by previous studies, our study proposed an integral approach and defined development assistance for RMNCH as the aid for medical activities that have the purpose of preventing diseases, and restoring and improving RMNCH. Instead of dividing aid to RMNCH into different categories, we grouped all projects with activities on improving RMNCH into one category. Our approach was built upon the evidence that RMNCH are interdependent, and that interventions for maternal or reproductive health played a critical role for reducing still-births, and neonatal and infant death [30, 31]. The advantage of this approach is that we could avoid making assumptions on how funds were allocated across different categories for a multi-purpose project. The underlying message of the integral approach is that funds for interventions targeting different population groups are not competitive, but complementary or mutually supportive. Health interventions for RMNCH cover from pre-conception to pregnancy, to labor and delivery, to neonatal (birth to first month), to infancy (1–23 months), and early childhood (24–59 months), and include activities on RMNCH (Fig 2). To track the development assistance for child survival between 2000 and 2014, we used the aid datasets from the following sources: (1) The OECD Creditor Reporting System (CRS) aid activity database [32]. Data were downloaded in February 2016 with projects reported by 68 donors and implemented in 147 low and middle-income economies. We excluded 13 states or territories without complete time series data on total/child populations, or on child mortality rates, including South Sudan (a Countdown country). The final sample has 134 low- and middle-income countries (S1 Text). The CRS aid activity database documents aid activities reported by bilateral Official Development Assistance (ODA) to developing countries from OECD’s 26 member countries and European institutions, on a mandatory basis. It also provides information reported by multilateral organizations (such as the United Nations and World Bank), non-DAC countries (such as the Russian Federation, United Arab Emirates), and private donors (such as The Bill & Melinda Gates Foundation) on a voluntary basis (S3 Table). (2) The OECD Development Assistance Committee (DAC) Annual Aggregate Database (DAC data). In addition to reporting to CRS aid activity database, DAC country members are required to report to DAC Annual Aggregates Database on their annual disbursements and commitments to recipients. The DAC2a database provides disbursements by a specific donor to a specific recipient in a specific year, yet has no breakdowns across sectors [33]. The DAC5 reported the level of disbursements (or commitments if disbursements were not available) for each sector by a donor in a specific year [34], but not by recipient countries. The reporting to CRS and DAC is conducted independently. (3) Gavi, the Vaccine Alliance [35] and The Global Fund to Fight AIDS, Tuberculosis and Malaria (GFATM) [36]. The data from the GFATM and Gavi are not complete in CRS. We downloaded disbursements data between 2003 and 2006 from Gavi and 2002 from GFATM and added them to the CRS data. We used disbursements (grants and loans) data to measure the development assistance for child survival between 2000 and 2014. Return of unspent balances and repayments of loans were excluded. Our focus is on the level of aid disbursed to developing countries rather than on comparing donors’ contribution patterns; therefore, donors without complete time series were included. Based on the conceptual framework, we tracked the aid disbursed to projects with activities on improving RMNCH, water and sanitation, food and humanitarian assistance, and primary and secondary education in developing countries. Table 1 presents the corresponding sector names and codes in the CRS data [37]. Aid that focused on assisting education/training, government and civil society, or other commodities could also include activities related to child survival. We used a list of key words to identify these activities and included them in the corresponding areas (S3 Text). Aid flows are measured on a calendar year basis. The CRS database has variables regarding project purpose, its title, donor(s), recipient(s), annual disbursements, and short and long descriptions of the project, which enabled us to derive the amount of aid disbursed by a donor in a year to a recipient country for activities directly related to RMNCH. We followed previous studies [14, 38] and used a combination of keyword search and manual coding, with keyword search as the first step and manual coding as the second step. Details on developing and implementing the identification strategies are presented in the S3 Text. For projects with multiple purposes, two sets of estimates were generated: one including the full disbursements of multi-purpose projects (the upper-bound of estimated aid for RMNCH), and the other excluding multi-purpose projects (the lower bound of RMNCH). One challenge of using the CRS data is the incompleteness of the reported disbursements, especially before 2003: donors reported aggregated disbursements to DAC, but did not report the related aid activities to the CRS. We analyzed and imputed the missing data and validated the imputation methods (S4 Text). The trends of missing rates suggested similar patterns across the four sectors: the missing rates are below 10% since 2008, except for food and humanitarian assistance between 2012 and 2014 (S7 Fig). Some donors reported disbursements only at the regional level or labeled it as “Developing countries, unspecified”. These unspecified funding could take a substantial proportion of total disbursements (33% in 2014, S8 Fig). We followed previous studies [12, 38] and allocated the annual regional or unspecified fund to each recipient based on its proportion in total aid disbursed to the region or to the developing countries in the year using available CRS data (S4 Text). All disbursements are deflated into 2013 US dollars. We produced six sets of annual recipient-level estimates for aid disbursed to RMNCH (upper/lower bound), health, food and humanitarian, water and sanitation, and education (Table 2). For each sector, “CRSrys” represents the lowest value and “ESTrys + Est(Allorys_reg_unsp)” represents the highest value (Table 2). We tracked the levels and trends of aid for each child survival sector (in total and per capita) at the global and regional levels between 2000 and 2014, tested the robustness of trends, and examined their growth rates during the period. To investigate whether resources were differentially allocated to the countries in high need (high child mortality rate), we estimated the aid per capita to each sector for countries with various characteristics: (1) 134 low- and middle-income countries; (2) 74 Countdown priority countries that accounted for more than 90% of child and maternal deaths worldwide [1]; (3) 67 Countdown countries with higher child mortality rate (greater than 40 per 1,000 live births) in 2000; (4) 25 fragile Countdown countries [39]; and (5) 15 Countdown countries that were on track to meet the MDG 4 and had a high-level of reliance on health aid (S7 Table). At the country level, we examined the total and per capita aid received during the period and compared the top 10 countries that received the largest amount of aid for each sector of child survival to the top 10 countries that received the highest per capita aid for each sector. We also estimated trends for four types of interventions that targeted the leading causes of death for children under-five: (1) child vaccines and immunizations, (2) prevention and treatment of diarrhea and pneumonia, (3) prevention and treatment of malaria, and (4) services for neonatal health such as breastfeeding, antenatal care, neonatal care, postnatal care, prevention of mother-to-child transmission of HIV, and skilled birth attendance. Knowing how much aid is invested in these interventions could help both donors and recipients to identify underfunded services. We compared our estimates of RMNCH in the Countdown countries with the ones produced by the Countdown group between 2003 and 2012 –the period with available estimates in the Countdown studies. STATA 14 was used in analysis.

• lu, chunling
• chu, annie
• li, zhihui
• shen, jian
• subramanian, s. v.
• hill, kenneth