Development assistance for health in Africa: are we telling the right story?

OBJECTIVE: To describe the different types of data sets on aid flows, what they capture and the types of questions they answer, and to explore the extent of variation in levels and trends between these data sets at the regional and country levels. METHODS: Data included in the database of the World Health Organization are derived from official country documents and are published annually after review by each country. In addition to such data, the authors extracted data from publicly available web sites. The data extracted covered all aid flows from all donors specified for sub-Saharan African countries (including aid for the African region as a whole or for groups of countries in the region) as being for health. FINDINGS: The variation in levels and trends in development assistance for health across the six data sets compared in this paper was substantial. Variation was greater at the country than at the regional level, partly because the different aggregates of development assistance for health have different meanings and partly because of incomplete reporting. CONCLUSION: It is important to know what the different aggregates of development assistance for health reported in the different databases mean before deciding which ones to use to answer a particular policy question. Using the wrong source can lead to erroneous conclusions.

Proposing standardised geographical indicators of physical access to emergency obstetric and newborn care in low-income and middle-income countries.

Emergency obstetric and newborn care (EmONC) can be life-saving in managing well-known complications during childbirth. However, suboptimal availability, accessibility, quality and utilisation of EmONC services hampered meeting Millennium Development Goal target 5A. Evaluation and modelling tools of health system performance and future potential can help countries to optimise their strategies towards reaching Sustainable Development Goal (SDG) 3: ensure healthy lives and promote well-being for all at all ages. The standard set of indicators for monitoring EmONC has been found useful for assessing quality and utilisation but does not account for travel time required to physically access health services. The increased use of geographical information systems, availability of free geographical modelling tools such as AccessMod and the quality of geographical data provide opportunities to complement the existing EmONC indicators by adding geographically explicit measurements. This paper proposes three additional EmONC indicators to the standard set for monitoring EmONC; two consider physical accessibility and a third addresses referral time from basic to comprehensive EmONC services. We provide examples to illustrate how the AccessMod tool can be used to measure these indicators, analyse service utilisation and propose options for the scaling-up of EmONC services. The additional indicators and analysis methods can supplement traditional EmONC assessments by informing approaches to improve timely access to achieve Universal Health Coverage and reach SDG 3.

Estimated global resources needed to attain international malaria control goals.

OBJECTIVE: To provide the international community with an estimate of the amount of financial resources needed to scale up malaria control to reach international goals, including allocations by country, year and intervention as well as an indication of the current funding gap. METHODS: A costing model was used to estimate the total costs of scaling up a set of widely recommended interventions, supporting services and programme strengthening activities in each of the 81 most heavily affected malaria-endemic countries. Two scenarios were evaluated, using different assumptions about the effect of interventions on the needs for diagnosis and treatment. Current health expenditures and funding for malaria control were compared to estimated needs. FINDINGS: A total of US$ 38 to 45 billion will be required from 2006 to 2015. The average cost during this period is US$ 3.8 to 4.5 billion per year. The average costs for Africa are US$ 1.7 billion and US$ 2.2 billion per year in the optimistic and pessimistic scenarios, respectively; outside Africa, the corresponding costs are US$ 2.1 billion and US$ 2.4 billion. CONCLUSION: While these estimates should not be used as a template for country-level planning, they provide an indication of the scale and scope of resources required and can help donors to collaborate towards meeting a global benchmark and targeting funding to countries in greatest need. The analysis highlights the need for much greater resources to achieve the goals and targets for malaria control set by the international community.