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Background paper for the Africa Heads of State and Government Summit on HIV/AIDS, TB and Malaria, Abuja, Nigeria, May 2006 Financial Factors Affecting Slow Progress in Reaching Agreed Targets on HIV/AIDS, TB and Malaria in Africa Chris Atim May 2006 DFID Health Resource Centre 5-23 Old Street London EC1V 9HL Tel: +44 (0) 207 251 9555 Fax: +44 (0) 207 251 9552

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The DFID Health Resource Centre (HRC) provides technical assistance and information to the British Government’s Department for International Development (DFID) and its partners in support of pro-poor health policies, financing and services. The HRC is based at HLSP's London office and managed by an international consortium of five organisations: HLSP Ltd, UK; Ifakara Health Research and Development Centre, Tanzania (IHRDC); ICDDR,B - Centre for Health and Population Research, Bangladesh; Sharan, India; Swiss Centre for International Health (SCIH) of the Swiss Tropical Institute, Switzerland. This report was produced by the Health Resource Centre on behalf of the Department for International Development, and does not necessarily represent the views or the policy of DFID. Financial Factors Affecting Slow Progress In Reaching Agreed Targets On HIV/AIDS, TB And Malaria In Africa Prepared by: Chris Atim, HLSP Institute With research assistance from: Mark Pearson, HLSP Ellie Bard, HLSP Consultancy funded by DFID Health Resource Centre DFID Health Resource Centre 5-23 Old Street London EC1V 9HL Tel: +44 (0) 207 251 9555 Fax: +44 (0) 207 251 9552

ACKNOWLEGEMENTS My sincere thanks go to Mark Pearson and Ellie Bard of HLSP who helped a lot in the preparation of this paper by turning out tables and charts in record time. Valuable assistance (especially in data access and some charting) was also received in the preparation of the paper from World Bank Health Financing Staff, Alex Preker, Gift Manase and Kofi Amponsah. I am particularly grateful to Alex Preker for making available some relevant documents including unpublished or forthcoming ones from the international agencies, as well as for maintaining close contact throughout the preparation of the paper. Many thanks also go to ‘miracle maker’ Claudia Sambo of HLSP Institute – she has been very responsive and helpful with obtaining information quickly and in appropriate format!

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ACRONYMS AND ABBREVIATIONS ARVs Antiretrovirals AU African Union AUC (annex) African Union Commission BS Budget Support CBHI Community Based Health Insurance CCT Conditional Cash Transfer CMH Commission on Macroeconomics and Health DAC Development Assistance Committee DFID Department for International Development (UK) DRC Democratic Republic of Congo ECOWAS Economic Community of Western African States ESA Eastern and Southern Africa FBO (annex) Faith Based Organisation GAVI Global Alliance for Vaccines Initiative GDP Gross Domestic Product GFATM Global Fund to fight AIDS, Tuberculosis and Malaria GHP Global Health Partnership GLC Green Light Committee GNI Gross National Income HIPC Highly Indebted Poor Country HIV/AIDS Human Immunodeficiency Virus /

Acquired Immunodeficiency Syndrome HLSP Health and Life Sciences Partnership IDA International Development Association IFF International Finance Facility IMF International Monetary Fund M&E Monitoring and Evaluation MAP (annex) World Bank Multicountry AIDS Program MDG Millennium Development Goal MDR TB Multi-drug Resistant Tuberculosis MTEF Medium Term Expenditure Framework NAC National AIDS Commission NEPAD (annex) New Economic Partnership for African Development NGO Non Governmental Organisation NHA National Health Account NSP Non State Provider ODA Official Development Assistance OECD Organisation for Economic Co-operation and Development OOP Out of Pocket (spending) PBA (annex) Programme Based Approach PEPFAR The President’s Emergency Plan for AIDS Relief PPP (1) Public Private Partnership PPP (2) Purchasing Power Parity PRS (annex) Poverty Reduction Strategy PRSP (annex) Poverty Reduction Strategic Plan SADC (annex) South African Development Community SDR Special Drawing Rights SSA Sub Saharan Africa SWAp Sector Wide Approach SWOT Strengths, Weaknesses, Opportunities and Threats TA (annex) Technical Assistance

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TB Tuberculosis TOR Terms of Reference UNAIDS The Joint United Nations Programme on HIV/AIDS US The United States of America WB (annex) The World Bank WHO The World Health Organisation

Financial factors affecting slow progress in reaching agreed targets on HIV/AIDS, TB and Malaria in Africa

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CONTENTS

ACKNOWLEGEMENTS ...............................................................................................i

ACRONYMS AND ABBREVIATIONS..........................................................................I

EXECUTIVE SUMMARY ............................................................................................iv

1.0 INTRODUCTION....................................................................................................1 1.1 Methodology and limitations...............................................................................1

2.0 NATIONAL HEALTH SECTOR FUNDING AND RESOURCE ALLOCATION IN AFRICA........................................................................................................................2

2.1 Selected health financing indicators...................................................................2 Source: WHO, 2002 .................................................................................................8 2.2 Analysis of sources and use of funds based on NHA data ................................9

3.0 FUNDING PROJECTIONS ..................................................................................14 3.1 What is the approximate shortfall in currently available financing if the MDGs and Abuja Targets are to be met?..........................................................................14 3.2 What would it cost to implement the health MDGs?.........................................16

4.0 THE INTERNATIONAL CONTEXT FOR MEETING THE TARGETS .................18 4.1 Trends in ODA and international aid flows for health.......................................18 4.2 Impact of GHPs on commodity pricing and security.........................................21 4.3 The Impact of Increased Debt Relief on Health Spending ...............................21 4.4 Analysis of Aid Modalities ................................................................................22

5.0 SUSTAINABILITY AND EFFECTIVENESS OF AID AND FISCAL SPACE ISSUES......................................................................................................................24

5.1 Aid sustainability ..............................................................................................24 5.2 Fiscal Space and Efficiency of Resource use in Health ...................................27

6.0 CONCLUSIONS...................................................................................................31

ANNEX 1: TERMS OF REFERENCE (FINANCING PAPER)...................................32

ANNEX 2: League Tables - Selected Indicators in PPP (international) Dollars..34

ANNEX 3: Role of Sub-Regional Economic Groupings........................................35


DFID Health Resource Centre April 2006

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EXECUTIVE SUMMARY It is now well-known that Africa, with 10 percent of the world’s population, accounts for 25 percent of the global disease burden and 60 percent of the people living with HIV/AIDS, as well as the highest disease burden for TB and malaria in the world. Yet Africa accounts for less than 1 percent of global health spending and contains only 2 percent of the global health workforce. With low levels of per capita income, mixed or limited growth prospects, and low domestic revenue mobilization potential in many countries, the continent faces very tough health financing challenges. It has been rightly observed that, “in this region, increasing the level of health expenditures and improving their efficiency is literally a life and death situation.” The evidence reviewed in this paper shows, however, that by almost any measure, most low income African countries are spending very small amounts on health, whether this is in terms of overall per capita spending, share of GDP devoted to health, percentage of public spending allocated to health or Government spending on health per capita. On the other hand, private spending, and especially out of pocket (OOP) spending, is extremely high in many of these countries (OOP spending constitutes up to 80% of all private spending and 50% of overall spending), a major factor further impoverishing vulnerable households. Increasing public spending on health is essential in those countries in order to reduce high levels of impoverishing OOP expenditure, but also and above all, to achieve the international targets for achieving various health sector goals. The Abuja Declaration of 2001 set a target for all African countries of 15% of public spending for health. However, the analysis shows that many countries are still far short of this goal (two-thirds of countries are spending below 10%). The analysis also shows that while it is important to encourage AU member states to devote more to the health sector through targets such as the Abuja one, it may be even more important to focus in the medium to longer term on attaining the levels of spending that would enable the countries to meet other international targets such as the Commission on Macroeconomics and Health (CMH) and Millennium Development Goals (MDGs), which are more linked to obtaining reasonable health outcomes than the Abuja target. The CMH target of $34 per capita spending is based on what is needed to buy an essential package of health services, while the health MDG targets directly seek some desirable health outcomes. Indeed, estimates of what difference the Abuja targets would make to achieve such priority goals, based on 2002 data, show that, even if they met the Abuja target, more than half of all AU members would not have made much progress towards attaining the CMH and MDG targets. All estimates of what is required to attain the CMH and MDG targets show however that the financing gap between currently available funds from all sources and what is needed is huge and well beyond what many of the countries can mobilize under any realistic scenario. The estimates of what is needed range from US$20 to US$70 billion per annum until 2015 (against $10 billion total health aid in 2003). Thus the levels of spending required to attain the CMH and MDG targets would require even higher levels of external assistance for many of the low income countries involved While the international health financing context for responding to the challenges posed by these targets, and especially for HIV/AIDS, TB and malaria, has considerably improved in recent years, the efforts still fall well short of the needs. Official development assistance increased by nearly fourfold between 1990 and



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2003, and is the main source of external finance in Sub-Saharan Africa, accounting for more than 55 percent of total external flows in 2003. Much of this increase is due to the entry of Global Health Partnerships (GHPs) and new private foundations onto the international funding scene. These new global institutions have also helped greatly to raise awareness of the issues around HIV/AIDS, TB and malaria. But the advent of new GHPs and increased bi- and other multilateral assistance for specific health interventions has also met with some criticism for accentuating certain problems associated with the international aid architecture: unpredictability and volatility of donor funding; proliferation of disease- and intervention-specific programs, which are often not integrated into any particular country’s ongoing programs; large numbers of new actors and donors; other macro-economic distortions, and lack of accountability of donors for the absence of results and progress. These problems reduce the impact of donor funding in achieving economic growth and health improvements. Indeed, it is also relevant to ask whether the GHP model of funding new interventions for a specific period of time and then moving onto new areas, while leaving behind each time the recurrent costs of the new programmes for states, is a viable one for many countries. The evidence seems to be that the recurrent costs of GHP investments (human resources required to deliver new programmes, new treatment centres, costs of vaccines and life-saving drugs, etc) are not sustainable for many low income countries. Proposals for mitigating the impact of the above problems include: making future aid flows more certain and less subject to annual donor budget allocations; harmonization and alignment; and leadership of the development process and coordination of all funding including donor aid by country authorities in line with country-led priority-setting. Governments of recipient countries may also be able to act to mitigate volatility by prudent public expenditure management. Providing fiscal space will also allow countries to allocate resources to their top priorities in a sustainable manner. Perhaps the most realistic instruments/methods for increasing the fiscal space available to African countries to increase spending on health priorities include: increasing tax levels, reallocating from lower to higher priority areas (and making other efficiency improvements), attracting more donor funding (but with regard to sustainable levels), borrowing (for countries where debt levels are not too high already), even more debt relief directed towards the health sector, policies and institutions to attract and make optimal use of workers’ remittances and foreign direct investment, and introducing innovative health financing mechanisms such as well designed and publicly supported community health insurance schemes and social health insurance if the conditions are right. It is of some concern that there is no reliable information on the resource requirements for other important health priorities for achieving the MDG targets such as child mortality and maternal health, as well as water and sanitation. It seems that the increased international attention on and funding for the diseases that are the main focus of the GFATM and some other GHPs has not led to similar specific interest in other vital health goals such as these. Finally, to return to the main theme, the next Abuja Summit should be urged to work with their partners to secure a commitment to the CMH target of at least $34 per capita spending by all countries (and from all sources) if real progress is to be made towards achieving the MDG targets by 2015. This should go with a real commitment to utilise increased resources more efficiently while providing more effective country leadership of the development process.



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1.0 INTRODUCTION In 2001, African heads of State meeting in Abuja, Nigeria, pledged to increase the proportion of public expenditure going to health to 15% in their countries, among other commitments. African states have also signed onto other international targets such as those of the Millennium Development Goals (MDGs). The Commission on Macroeconomics and Health (CMH) has calculated that a country needs to spend at least $34 per capita in order to provide an essential WHO-defined package of health services to their population. This paper was commissioned by the UK Department for International Development’s (DFID) Health Resource Centre in order to assess the financial factors affecting the slow progress in attaining these agreed targets in Africa. Briefly, the terms of reference (see Annex 1 for the specific issues relating to this paper) called for an assessment of:

• Key health financing indicators; • Sources and use of funds based on NHA data; • The flow of resources to sub-national levels and the balance between

promotive, preventive and curative health care; • What it would cost to implement the health MDGs and the approximate

shortfall in currently available financing if the MDGs and Abuja targets are to be met;

• Fiscal space; • The impact of debt relief on health spending; • Commodity pricing and security; • Aid modalities; • The international context for meeting the targets, including the roles of

international bilateral and multi-lateral donors, the GHPs and private foundations.

The above items sum up the principal issues discussed in this paper.

1.1 Methodology and limitations The TORs clearly stated that the paper was to be based on a review of existing data and documentation; no original research was to be undertaken. We have followed that recommended approach. However, we also found that there were several problems of data quality and reliability, including gaps where no data were available to adequately analyse some issues, or data that have not been updated for some years. For instance, it seems that data are not available on spending in countries per disease categories (these are not being tracked) or the resource requirements for other important health priorities within the MDG context such as child mortality and maternal health. More data are readily available for the diseases that are the main focus of the GFATM and some other GHPs. Similarly, no extensive analyses or data were found on the flow of resources to sub-national levels and the balance between promotive, preventive and curative health care. Even the available data is not always reliable, and it is important to bear this in mind in reading the report.



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2.0 NATIONAL HEALTH SECTOR FUNDING AND RESOURCE ALLOCATION IN AFRICA This section presents snapshots of, as well as overall trends in, the health funding situation in Africa. It presents and discusses statistics from various sources on selected health sector funding and expenditure indicators.

2.1 Selected health financing indicators Analysis of WHO data on the evolution of spending per capita in US dollars in 52 African countries between 1998 and 2002 show that the majority of countries are spending less than $34 on health1. 19 of the 52 countries are spending at least $34 per capita, while 33 countries are spending below. When the Sub-Saharan countries alone are considered, only 12 are spending above this recommended threshold.2

Table 2.1.1: Total health spend per capita in US$ 1998 – 2002 (Average exchange rates) 1998 1999 2000 2001 2002 Algeria 62 61 65 70 77 Angola 17 16 25 37 38 Benin 18 17 17 18 20 Botswana 137 141 144 151 171 Burkina Faso 12 12 10 9 11 Burundi 5 4 3 3 3 Cameroon 28 31 28 28 31 Cape Verde 64 63 57 64 69 Central African Republic 10 10 10 10 11 Chad 12 12 11 12 14 Comoros 11 10 8 7 10 Congo 20 19 19 17 18 Côte d'Ivoire 54 49 42 41 44 Democratic Republic of Congo 5 9 11 5 4 Djibouti 52 52 52 51 54 Egypt 64 67 67 59 59 Equatorial Guinea 42 44 52 65 83 Eritrea 10 8 8 9 8 Ethiopia 5 5 5 5 5 Gabon 162 130 138 151 159 Gambia 23 23 23 21 18 Ghana 22 23 14 15 17 Guinea 24 24 20 20 22 Guinea-Bissau 8 8 9 9 9 Kenya 19 16 18 18 19 Lesotho 28 27 27 23 25 Liberia 7 8 7 5 4

1 This threshold has been chosen because of the $34 per capita health spending recommended by CMH for a country to be able to buy an essential package of health services. Clearly, there will be questions about the appropriateness of such a globally set target in the context of different country circumstances, but we do not enter this debate in this paper. 2 See Annex 2 for a league table based on a broader range of health spending indicators for African countries, in Purchasing Power Parity (PPP) or international dollars. The average exchange rates are used for the analysis here because we have been advised that the CMH target is in average exchange rates, not PPP dollars.



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Libyan Arab Jamahiriya 210 207 175 158 121 Madagascar 6 5 5 5 5 Malawi 15 14 12 14 14 Mali 11 10 10 11 12 Mauritania 11 10 9 10 14 Mauritius 102 109 109 107 113 Morocco 56 54 54 53 55 Mozambique 9 10 10 10 11 Namibia 129 128 126 114 99 Niger 8 9 7 7 7 Nigeria 17 17 18 20 19 Rwanda 15 14 13 11 11 Sao Tome and Principe 25 32 29 33 36 Senegal 22 23 22 25 27 Seychelles 448 441 395 388 425 Sierra Leone 5 6 6 7 6 Somalia 6 7 6 6 6 South Africa 261 266 244 224 206 Sudan 20 18 17 18 19 Swaziland 96 85 81 73 66 Togo 35 35 26 26 36 Tunisia 126 124 115 120 126 Uganda 15 17 16 18 18 United Republic of Tanzania 12 12 13 14 13 Zambia 21 17 17 20 20 Zimbabwe 59 35 46 55 118 Source: World Health Report 2005: Making Every Mother and Child Count When these spending patterns are projected (by sub-region), it is found that even by the MDG target date of 2015, well above 80% of West and East African, and over 50% of Central African countries will still be spending less than $34, the current MCH threshold. By 2030, still over 50% of East African, and about a quarter of West African countries would still be spending below the current threshold. Figure 2.1.1: Proportion of countries spending less than $34 per head.

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NB The true situation would actually be worse than this analysis shows because the CMH recommended threshold in fact rises to $38 per capita by 2015.



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Regional data on total Government spending per capita in dollars (weighted) show that East and West African country Governments are spending between $8 and $9 per head, Central African Governments are spending about $20 per head; while the corresponding amount for North African Governments is over $40 and Southern African ones over $140. Table 2.1.2: Total Government spending per capita in dollars (weighted) SUB-REGION 2002 2003 2004 2005 East Africa 5.79 6.44 7.71 8.35 West Africa 4.85 6.23 7.92 8.84 Central Africa 10.78 13.12 17.93 19.83 Southern Africa 86.73 100.62 135.51 145.67 North Africa 28.97 33.05 39.07 43.30 Source: WHO On the basis of some assumptions stated at the bottom of Figure 2.1.2 below, public expenditure per capita on health has been projected for the above regions till 2030. With those assumptions, which on past evidence some might consider optimistic, all regions show an increasing amount devoted to health by Governments, but even so, the rate of growth appears very slow for West and East African regions. Figure 2.1.2: Projected Per Capita Public Expenditure on Health by Region (weighted average)

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Assumptions: 4-6% annual increase in per capita income, modest increases in share of public spending/GDP and share of public spending to health, no increase in aid dependency. Analysis of NHA data by WHO shows the percentages of GDP spent on health in Africa in 2002 (see Figure 2.1.3). The WHO analysis presents health spending data as percentage of GDP but disaggregated according to public and private sources.3 In terms of share of their GDP devoted to health, 25 or nearly half of the 52 countries

3 Note that private spending here will include out of pocket spending as well as spending on health insurance which is not organised and/or provided directly by Government.



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spent less than 5%, 22 spent between 5% and up to 8 %, 3 spent between 8% and 10% and 2 spent above 10%. Private spending clearly predominates over public sources in at least 24 of the countries. Figure 2.1.3: Health Spending by Source as % of GDP

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Source: Figures computed by WHO to assure comparability; they are not necessarily the official statistics of Member States, which may use alternative rigorous methods. Recent data collected and analysed by the African Union on Government health spending among SSA countries and presented in its “Progress Report on the Implementation of the Plans of Action of the Abuja Declarations for Malaria, HIV/AIDS and Tuberculosis” paint an interesting picture (see Figure 2.1.4 below). According to this data, about a third of SSA countries are allocating 10% or more of their national budgets to the health sector, 38% of countries allocate 5-10% while 29% of them allocate below 5%. The Report also shows that West and Central Africa contain most of the countries that allocate less than 5%. Botswana, according to this data, is the only country that has achieved the Abuja target of 15%, while countries nearing this target include The Gambia (13%), Ghana (13%), Namibia (12%), Sao Tome and Principe (14%), Tanzania (13%), Uganda and Zimbabwe (all at 14.5%). The picture coming out of the AU analysis above differs markedly from that which emerged from other trend data relating to an earlier period 1998 – 2002, (see Figure 2.1.5). The earlier data shows a different set of countries with a percentage of Government budgets for health close to or exceeding the Abuja target of 15%, including Mozambique, Congo DR, Tanzania (all achieving 15% or more), with a further dozen or so countries achieving the regional average of about 9% or above.



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Figure 2.1.4.: Percentage of national budgets allocated to health sector.

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Source: African Union. Progress Report on the Implementation of the Plans of Action of the Abuja Declarations for Malaria, HIV/AIDS and Tuberculosis; Revised Final Draft, 22 December 2005.



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Figure 2.1.5: Government Expenditure on Health as % of Total Government Expenditure 2002

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Regional Average Abuja Target Source: World Bank staff It is also significant that the data discussed above include North African countries with higher per capita health spending and (generally acknowledged) better performing health systems than many of the SSA countries that scored so highly in Government spending as a percentage of the total Government spending.4 Yet the North African countries, as a group, have Government spending levels below the SSA countries. Examining comparative data from across the world about how much of their public spending different regions are devoting to health (Figure 2.1.6), several observations stand out. We have already observed the pattern between SSA and North African countries. Next, apart from South Africa, all regions in Africa are spending less than corresponding regions from other parts of the world except for West, South East and South Central Asia. Furthermore, while the percentage of public spending devoted to health by more advanced regions is generally higher than in Africa, there is no obvious correlation between the level of public expenditure and what is known about the performance of health systems in these regions (similar to our first observation). In fact, only North America, Oceania and Central America are devoting at least the equivalent of the African Abuja Declaration target of 15% to health. These observations hint at an important underlying message: that the focus on a percentage of public spending by itself does not tell us much about how resources are actually used, and the returns from such allocation of resources.5 Nor does it tell 4 Government spending is of course only a part of the picture. Total health spending includes private sources which are generally high in Africa, as NHA analysis below will show. But high private sending in Africa, with the exception of the high private health insurance based systems of South Africa and Namibia, are not usually associated with good performing heath systems. 5 This is a timely reminder that efficiency of resource use is arguably just as important as how much is spent on health. We leave aside for now the differences in share of total health spending represented by public spending for many of the regions involved.



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us how large is the denominator over which the percentage of health spending is calculated; in other words, is it a percentage of a very small budget or of a large one; and indeed is it of a budget that is growing or declining over time?6

Figure 2.1.6: Health Spending as % of Public Spending p g

Source: WHO, 2002

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Source: WHO, 2002 It is also useful to examine how country military spending stacks up against social spending. Comparative data from 2004 on percentage of GDP devoted to military, health and education spending in African countries show at least 21 countries (or 43% of all those for which data was available), in which military spending is at least equal to or exceeding spending on health (see Figure 2.1.7). In 14 cases (29% of countries), military spending exceeds or is equal to education spending. In three countries facing post-conflict situations, military spending exceeds both education and health spending together.7 These data partly reflect the fragile state systems in many countries, but even some states enjoying relative peace appear also to have military expenditures that well exceed their education and/or health spending. To the extent that high levels of military spending reflect internal or external tensions and conflicts, this means that in principle, efforts to resolve those conflict situations would improve the room to spend more on health and education (see later discussion on fiscal space).

6 If an economy as a whole is contracting, and if social sectors such as health are contracting at a slower pace than the rest of the economy (a reasonable supposition as declining public sector finances may be devoted mainly to slowing down or arresting the deterioration of essential services), then an increase in the share of public spending going to health in this situation will not necessarily signify great progress! 7 Note that some countries in conflict situations or emerging from such situations, such as Congo DR, Somalia and Liberia, are not included, presumably because of the difficulty of obtaining reliable statistics in such situations.



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Figure 2.1.7: Comparison of Public Spending on Health, Education and Military as % of Total Public Spending

Figure 2.1.5.1: Comparison of public spending on Health, Education and Military as % of total public spending

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Sao

Tom

e an

d Pr

inci

pe

Nig

eria

Libe

ria

Som

alia

% o

f tot

al p

ublic

spe

ndin

g

Public spending on military as % of total public spending

Source: various Government and international agency sources, 2004 data. NB Health spending missing for Somalia; Education missing for DRC, Liberia, Sao Tome and Somalia

2.2 Analysis of sources and use of funds based on NHA data Analysis of the NHA data used in the WHO’s World Health Report 2005 reveal the following characteristics of health care financing in Africa: Government expenditure forms over 50% of the total expenditure on health in 24 countries. Out of 39 countries for which data were available, social security did not contribute to health expenditure in 19 of the countries. Social security contributed less than 10.1% of the general government expenditure on health in 14 countries; and social security contributed over 10.1% to the general government expenditure on health in the remaining six countries. The same data source indicates that private spending for health – which includes out-of-pocket (OOP) payments made directly to various providers, private prepaid plans, including payments to community financing schemes and other private insurance plans, indirect payments for health services by employers (firms) and local charitable groups - constituted over 40% of the total expenditure on health in 31 countries.8 The very high levels of personal out-of-pocket expenditures are revealed by the findings that such spending constituted 51% to 90% of the private health expenditure in 14 countries and 91% to 100% in 24 countries. Such high levels of personal out of pocket spending at the point of use constitute a heavy burden capable of impoverishing vulnerable households and individuals.9

8 The data represented in Figure 2.1.3 further bear out a frequent observation from NHA data that public spending is not necessarily the dominant form of health spending in most African countries. In fact, in 27, or just over half, of the 52 countries where this data was available, private spending exceeds public spending on health. 9 NHA Data, World Health Report 2005, WHO.



10

BOX 2.2.1 NHA SUB-ANALYSIS: HIV/AIDS SPENDING IN RWANDA In Rwanda, the first NHA HIV/AIDS sub analysis in 1998 showed that only 10 percent of all health expenditures in the country went toward prevention and treatment of the disease. Moreover, while donors financed more than half the health sector, only 1 percent of their funds went toward HIV/AIDS services and programs. Households were the primary financiers of HIV/AIDS services, providing 93.5 percent of total HIV/AIDS funding; donors provided 6 percent while the government contributed less than 1 percent. Revelation of the financial burden on households and the paucity of donor funds led the donor community to increase its contribution to the fight against HIV/AIDS in Rwanda by tripling its assistance from $0.5 million in 1998 to $1.5 million in 2000.

Excerpt from: Mark Pearson, Economic and Financial Aspects of the Global Health Partnerships, Oct 2004

Despite so much private health spending, the private health insurance industry is little developed outside of Namibia and South Africa where private health insurance plans (provided principally by Medical Aid Societies) accounted for more than 72% of the private health expenditure. Data on availability of health insurance plans were collected for 37 countries. Fifteen of these countries reported having no private health insurance plans; 16 countries reported that health insurance plans contributed less than 11% to private expenditure on health; and the remaining 6 countries reported that health insurance plans accounted for 11% and above of the private health expenditure.10

While there has been an increasing number of national health accounts exercises at the sector level, specific programme expenditure data is less available. One such exercise, for HIV/AIDS spending, was carried out in Rwanda in 1998 (see Box 2.2.1 to the right). A synthesis of findings from NHA studies in 26 Countries around the world carried out by Abt Associates in 2004 included 9 ESA countries where such studies had been undertaken. 11 This synthesis report gives more detailed information about funding sources in those study countries than the aggregate data cited above for all Africa countries. That synthesis shows the share of funds channelled through financing agents for the ESA countries. The share of public financing agents (Ministries, state-run social insurance, sub-national levels of Government and parastatals) ranged from 38 percent in Kenya to 67 percent in Zambia. The findings also indicate that households were the main private financing agent in all the countries, except in South Africa, where private insurance accounted for 41 percent of all funds that flowed through financing agents, significantly higher than the 11 percent accounted for by households. Private financing agents accounted for 50% or more of health spending in four of the ESA countries involved (see Table 2.2.1). The data from the NHA studies do not permit an analysis of the balance of spending between promotive, preventive and curative care. However, data available from WHO sources allow us to examine expenditures by type of health provider, or level of health care (i.e. primary, secondary and tertiary facilities) for some 10 SSA countries. The data show that in 7 out of the 10 countries, secondary and tertiary facilities together account for more spending than primary facilities, and in Burkina and Eritrea, tertiary facilities alone account for a greater share of spending than primary and secondary facilities combined. Primary facilities consume at least the same as the other two levels together in 3 countries - Madagascar, Zambia and Mauritania.

10 World Health Report 2005, op. cit. 11 Synthesis of Findings from NHA Studies in Twenty-Six Countries, Abt Associates Inc, July 2004

cial factors affecting slow progress in reaching agreed targets on HIV/AIDS, TB and Malaria in Africa


11

Table 2.2.1: Share of Funds Channelled through Financing Agents: ESA Countries

Public Financing Agents Private Financing Agents Rest of World

Ministry of Health

Other Minis- tries

Social Insurance

Regional or Local Govt

Para- statals

Public Total

Households Employ- ers

Private Insurance

Private Total

NGOs Donor

ESA Average

26% 3% 1% 15% 2% 47% 32% 4% 5% 41% 11%

Ethiopia 5% 6% 0% 28% 1% 40% 53% 0% 0% 53% 7% Kenya 24% 1% 4% 1% 8% 38% 49% 8% 3% 60% 2% Malawi 42% 4% 0% 2% 0% 48% 17% 15% 1% 33% 18% Mozambique 54% 3% 0% 0% 0% 57% 18% 7% 0% 25% 19% Rwanda 19% 2% 0% 16% 1% 38% 33% 7% 0% 40% 23% South Africa 1% 3% 1% 42% 0% 47% 11% 1% 41% 53% 0% Tanzania 19% 1% 0% 24% 0% 44% 47% 0% 3% 50% 7% Uganda 27% 1% 0% 10% 1% 39% 33% 2% 0% 35% 25% Zambia 46% 2% 0% 9% 10% 67% 32% 0% 0% 32% 2% Source: NHA reports. A.K. Nandakumar, Ph.D. Consultant Abt Associates Inc. et al. Synthesis of Findings from NHA Studies in Twenty-Six Countries; July 2004. Some totals (Public + Private + Rest of the World) may not add up to 100% due to rounding off errors.

Finan



12

Figure 2.2.1: Percentage of Health Expenditure among Primary, Secondary and Tertiary Facilities among Selected SAA Countries

0%

20%

40%

60%

80%

100%

Chad Eritrea Kenya Madagascar Malawi Zambia Burkina Faso Cote d'Ivoire Mauritania Togo

Tertiary % Secondary % Primary %

Source: Adapted from: WHO, Regional Office for Africa and Eastern Mediterranean, "Mid-term progress report on Abuja Declaration for Malaria control", Dec 2004. Note: In the original source, the percentages for the 3 levels of care for 5 of the countries are below 100; the differences from 100% has been assumed to represent spending areas outside those care levels (eg administration and central level, research and teaching, etc). For better visual inspection, we projected all figures to add up to100%. There is limited hard data to make an analysis of the share of resources flowing to sub-national levels within the health system. Nevertheless, the WHO cites data showing for instance that in Senegal, “only 20% of total health expenditure is utilised at the operational level”12. Similarly, a WHO study found that in Malawi, funds for primary level health care are channelled through district hospitals, “where they are often diverted from their original allocation”.13 Another study for the World Bank found that of the sums officially allocated for health services at the operational (sub-national) levels, there was leakage on the way from the centre of about 40% of the non-salary budgets in Tanzania and up to 80% in Ghana. Furthermore, 70% of the drugs and supplies budget suffered a similar fate in Uganda.14. This implies that whatever the official level of funding for sub-national levels, it is perhaps even more important that most or all of it gets to where it is needed. There is also fairly reliable anecdotal (and direct observational) evidence that in some countries such as Togo and Guinea, the only national level funding that ever arrives at local levels is that for personnel salaries, while non-salary operational costs have to be funded from sources such as user fees, or revolving drug funds sometimes set up with the aid of international NGOs. An indirect confirmation of this picture can also be gleaned from Figure 2.1.3, where the proportion of public expenditure compared to private sources is extremely low for the 2 countries.

12 Toonen J. Towards Pro-poor health Planning in the Context of Macroeconomics and Health: Country Case Study Senegal. WHO, Oct 2004. 13 Conticini, A. Macroeconomics and Health in Malawi: What Way Forward. WHO, Oct 2004. 14 Lindelow et al, 2005. Cited in Lewis M. Addressing the Challenge of HIV/AIDS: Macroeconomic, Fiscal and Institutional Issues. Working Paper 58. Centre for Global Development, Washington DC, 2005.



13

nalysis of available data on the share of external resources in total health

igure 2.2.3: Dependence of Health Spending on External Resources

Aexpenditures for 52 African countries shows donor dependence is very high for some of them. The evidence from this data shows that 17 countries, or a third of them, have donor dependence in the health sector exceeding 25%, and of these, two countries (Benin and Eritrea), depend for at least 60% of health sector funding on donors. Twenty-three countries however, have a health sector dependence on external resources of less than 10%.15 (see Figure 2.2.3). F

Figure 2.2.3 Dependence of Health Spending on External Resources

0

10

20

30

40

50

60

70

Benin

Eritrea

Liberi

a

Mozam

bique

Malawi

Rwanda

Ethiop

iaCha

d

United

Rep

ublic

of Tan

zania

Djibou

ti

Zambia Mali

Seneg

al

Kenya

Guinea

Seych

elles

Nigeria

Namibi

aTog

o

Swazila

nd

Gabon

Zimba

bwe

Congo

Mauriti

us

Tunisi

a

Algeria

Libya

n Arab

Jamah

iriya

Exte

rnal

Res

ourc

es a

s %

of T

otal

Exp

endi

ture

on

Hea

lth

Source: WHO, from NHA data.

wn due to limited space.

Note: Not all country names sho

15 World Health Report 2005, op. cit.



14

3.0 FUNDING PROJECTIONS This section discusses projections of resources required to meet the Abuja and CMH targets, on the basis of currently available financing and what additional funding would be required from domestic and external sources. The data available for the detailed analysis required here are from 1998-2002, and therefore not as recent as the 2005 snapshot data presented in the AU’s progress report.

3.1 What is the approximate shortfall in currently available financing if the MDGs and Abuja Targets are to be met? Previous data and analysis in the preceding Section 2 above have already shown that the majority of African countries are still far from the Abuja target of devoting 15% of national budgets to health. Two-thirds of SSA countries were found to be spending below or no more than 10% of budgets on health. The actual levels of the shortfalls in achieving the Abuja target for some 40 African countries are shown further below. An interesting preliminary question in this regard, already implied by some of the earlier analysis above, is what difference would achieving the Abuja targets make, in terms of achieving other international targets such as the CMH one of $34 per capita? The data presented in Figure 3.1.1 below attempts to provide an answer to that question for some 40 AU countries where current spending per capita is less than $100, based on current 2002 spending data. Even if all these countries achieved the Abuja target of 15% of all public spending going to health (and assuming private spending remains the same), only 12 countries would then attain or exceed the CMH target of $34 per capita. Twenty-eight countries will not be able to attain this target even under those conditions. Of these, 12 will not even achieve half of what the CMH calculates as the level of per capita spending needed to ensure an essential package of health services for the population. It is also remarkable to note from Figure 3.1.1 that for some of these countries the extra effort required to reach the Abuja target is not very high, relatively speaking, compared to current spending levels, although as we have seen, achieving the target might make little difference to capacity to deliver the WHO’s essential package.16

Based on 2002 data, we have also calculated how much of their national budgets must be allocated to health in order to achieve the $34 CMH target, for about 50 AU countries (see Figure 3.1.2). Not less than 27 of these countries would need to spend more than 30% of their budgets on health in order to achieve the CMH target, which would constitute clearly unrealistic spending allocations. Three countries would never be able to achieve the target even in principle, because it would require them to spend more than 100% of their national budgets on health!

16 In the light of the previous discussion in this section about the Abuja targets, note here that the DRC, which we found to be achieving the Abuja target by 2002, is actually spending an extremely low amount on health from public sources, around $2 per capita (adding private spending still leaves the DRC at no more than $5 per capita). Thus meeting the Abuja target in this case would not even appear to make a huge difference to actual health expenditures in per capita terms. One of the weaknesses of the focus on a target that is a percentage of public spending is that it ignores, or at best makes some incorrect assumptions about, existing sizes/levels as well as trends in growth of GDP/ GNI.



15

Figure 3.1.1: Expenditure on Health Compared to CMH Target: Would Meeting the Abuja Targets Make Much Difference?

Fig. 3.1.2: Expenditure on Health Compared to CMH Target Would Meeting the Abuja Targets Make Much Difference?

excludes all countries with total spend > $100 per capita

0

10

20

30

40

50

60

70

80

90

100

Buru

ndi

Com

oros

Djib

outi

Eritr

eaEt

hiop

iaKe

nya

Mad

agas

car

Mal

awi

Moz

ambi

que

Rw

anda

Uga

nda

Tanz

ania

Beni

nBu

rkin

aC

ape

Verd

eC

ôte

d'Iv

oire

Gam

bia

Gha

naG

uine

aG

uine

a-Li

beria

Mal

iM

aurit

ania

Nig

erN

iger

iaSe

nega

lSi

erra

Leo

neTo

goAn

gola

Cam

eroo

nC

ARC

had

Con

goD

R C

ongo

S To

me

Leso

tho

Swaz

iland

Egyp

tM

oroc

coSu

dan

E Africa W Africa Central Africa SAfrica

N Africa

Private SpendingAbuja Shortall in Public SpendingCurrent Public Spend

CMH Target

Source: HLSP Figure 3.1.2: Share of Public Spending Required to achieve Per Capita Public Health Expenditure of $34

Figure 3.1.3 Share of Public Spending Required to achieve per capita public health expenditure of $34

Source: WHO 2002 excludes DRC, Niger and Ethiopia where share would need to exceed 100%

-20

0

20

40

60

80

100

Burund

i

Djibou

ti

Kenya

Malawi

Mozam

bique

Seych

elles

Tanza

nia

Zimba

bwe

Burkina

Faso

Côte d'

Ivoire

Ghana

Guinea

-Biss

au Mali

Nigeria

Sierra

Leon

e

Angola

Centra

l Afric

an R

epub

lic

Congo

Gabon

Botswan

a

Namibi

a

Swazila

ndEgy

pt

Morocc

o

Tunisi

a

% o

f bud

get

Source: WHO



16

3.2 What would it cost to implement the health MDGs? Various sources differ in their estimates of what it would require to implement the MDGs, but these differences do not necessarily imply inconsistency because they arise mainly from the approach taken and what is included or excluded, whether the costs involved are incremental or total, etc. But perhaps more significant is that there is evidence that income growth and other complementary investments play a much greater role in improving health outcomes than investment in health itself.17 This raises the issue of whether it is additional resources or the better use of existing resources which is more important, and furthermore whether access to finance is the binding constraint or whether implementation capacity is more important. Income growth would not only improve health outcomes, it would also strengthen Government finances and their ability to fund health programmes.18 With these points in mind, this section examines some estimates of the costs of achieving the health-related MDGs. Cost of achieving targets for SSA countries The World Bank has estimated the cost of achieving the health MDGs at $20-25bn per annum as part of the US$35-76 billion required to achieve all of the non income MDGs, or almost three times the ODA aid for 2003.19 The CMH estimates of achieving MDG targets for HIV/AIDS, TB and Malaria are considerably higher, about $40-$52 billion annually until 2015. Table 3.1.1 below presents the incremental costs of achieving the targets, according to the CMH. In addition, investments in education (the additional costs of achieving universal primary education are estimated to be $9-$15bn) and water and sanitation ($5-21bn p.a) will also contribute to improved health outcomes. The figures show the scale of resources required to be spent annually in order to reach the target coverage levels.20 Preker et al estimated that $25 billion to $70 billion of additional spending would be required to bring poorly performing countries up the level of high performers.21 Box 3.1 below also presents estimates from different international sources /institutions concerning funding gaps for HIV/AIDS, TB and malaria. Table 3.1.1: Costs of Achieving MDG Targets for HIV/AIDS, TB and Malaria Incremental Costs 2007

($bn 2002)

Incremental Costs 2015 ($bn 2002)

TB Treatment 0.08 0.44 Malaria Prevention 1.03 2.33 Treatment 0.85 1.95 HIV/AIDS Prevention 4.25 8.7 Care 9.45 26.45 HAART 3.95 5.7 Total 19.3 45.8 Source: CMH 2001; Devarajan, Miller and Swanson, 2002. midpoint of ranges taken.

17 Filmer and Pritchett 1999. Cited in Pearson M. Economic and Financial Aspects of the Global Health Partnerships. Oct 2004 18 Pearson M. op. cit. 19 World Bank, Health Financing Revisited, forthcoming. 20 Note that the costs for 2007 and 2015 include costs of implementation for higher coverage levels as well as required investments and management and administration expenses. CMH Working Paper Series No: WG5: 26. 21 Preker A. et al. Financing the Millennium Development Goals. Expenditure Gaps and Development Traps. World Bank, 2005.



17

Commenting on these various estimates, a recent World Bank publication stated that “whatever estimation method is used, the conclusion of all the Millennium Development Goal cost estimate studies is the same: the financing gap is large between the costs of achieving the Millennium Development Goals and the potential for low-income countries to mobilize domestic resources. … Hence, all Millennium Development Goal cost estimate studies conclude public expenditures on health must be increased and this additional spending must be financed largely by donor support, especially in the least developed countries (emphasis added).”22

BOX 3.1 ESTIMATES OF FINANCING GAPS FOR HIV/AIDS, TB AND MALARIA Annual financial needs for HIV/AIDS epidemic (UNAIDS, 2005; OECD, 2005): UNAIDS has estimated that a comprehensive response to HV/AIDS requires between US$9.6 billion and 11.3 billion in 2005 and rising to between US$14.1 billion and US$18.8 billion by 2007 from all sources to address the epidemic in low and middle-income countries. Actual spending however was US$6 billion in 2004, including US$3.7 billion from external sources. [Total annual ODA for health is about US$7 billion.] Annual financing gap for CMH malaria target (CMH 2001): According to the report of the Commission on Macroeconomics and Health, up to US$2 billion will be needed each year to achieving the goal of halving the burden of malaria by 2010. Currently, only US$600 million is being spent. … Annual financing gap for TB epidemic (GFATM web site): It has been estimated that the gap is U$300 million a year to address the TB epidemic in low and middle-income countries. …

22 World Bank, Health Financing Revisited, forthcoming.



18

4.0 THE INTERNATIONAL CONTEXT FOR MEETING THE TARGETS In the face of the huge financing gap for achieving the targets noted in the previous section, there are essentially two sources from which the extra resources required can be raised: domestic revenues and external assistance. This section will focus specifically on the international context for the achievement of the targets. It will examine questions such as the funding levels for these disease areas, and trends in contributions from major donor categories (bi- and multilateral, private foundations, etc.) The discussion will further assess the impact of debt relief in improving health spending in beneficiary countries. It should be noted however, that the available data do not permit us to analyse spending by disease category, including resources going into achieving the child mortality and maternal health MDGs.

4.1 Trends in ODA and international aid flows for health Official development assistance (ODA) is of particular significance for Sub-Saharan Africa (SSA), compared to other regions of the world (see Figure 4.1.1). Although SSA accounts historically for around 20 percent of total official assistance, this region received 54 percent of the total increase in such assistance between 2001 and 2003. ODA is the main source of external finance in Sub-Saharan Africa, accounting for more than 55 percent of total external flows of about $41 billion received by these countries in 2003.23 Figure 4.1.1 also shows that foreign direct investment represented 25 percent of the total long-term flows, remittances 15 percent, and other private flows 5 percent. By comparison, in other regions, foreign direct investment and remittances account for the bulk of external financial flows, while official development assistance accounts for only 9 percent of such flows. Figure 4.1.1 Long-term capital flows to Sub-Saharan Africa and the rest of the developing countries, 2003

Development assistance specifically for health has been rising rapidly in recent years in nominal terms.24 From US$2.6 billion in 1990, development assistance for health rose to more than US$10 billion in 2003, and much of this increase is directly traceable to the entry of the new global health partnerships (GHPs) onto the international aid scene and a significant increase in funding by private philanthropic

23 World Bank, Health Financing Revisited, forthcoming. 24 In real terms, however, ODA has hardly risen from its level in the early 1990s (World Bank, forthcoming).



19

foundations, especially the Bill and Melinda Gates Foundation.25 The principal focus of these partnerships and philanthropies has been on funding programmes for major diseases especially HIV/AIDS, TB and Malaria. Increased funding has gone into areas such as vaccine development, technical assistance, commodity procurement, as well as prevention, care and support interventions related to these diseases. The GHPs – principally the GFATM, GAVI, Roll Back Malaria and others – plus the US President’s PEPFAR initiative together accounted for about 15 percent of total donor aid for health in 2002 (from practically zero in 1990) and 20 percent in 2003.26 Figure 4.1.2 below presents graphical evidence of the rising significance of GHPs and private foundations in development assistance for health.27

Figure 4.1.2: Development Assistance for Health by Source, 1997-2003

-

2,000

4,000

6,000

8,000

10,000

12,000

Average 1997 - 99 2003

US$ (in millions) Private nonprofitOther multilateral Development BanksUN System Bilateral

Source: Michaud, 2005 cited Chapter 4, World Bank, Health Financing Revisited, forthcoming Note: The category of other multilateral includes the European Union and the Global Fund to Fight AIDS, Tuberculosis and Malaria (GFATM). In terms of resources going specifically into disease programmes, the next figure below shows what is available for HIV/AIDS. This funding is mainly concentrated in 25 countries of the world (which receive about 72% of the donor funding shown in the figure), the majority in high prevalence countries of Africa and the Caribbean.28 Members of the OECD’s Development Assistance Committee (DAC) have also steadily increased their bilateral financing for HIV/AIDS, although this is chiefly dominated by the US Government’s PEPFAR programme. The dramatic rise in multilateral funding for HIV/ADS shown in the figure is the result mainly of the setting up of the GFATM. In fact, it is reported that in 2004, GFATM funding for HIV/AIDS was about the same as all DAC members’ bilateral (excluding PEPFAR) funding for this disease.29 The potential impact of the increased

25 Michaud CM. Trends in development assistance to the health sector 2000-2004. In: Tough choices: investing in health for development. Global report on the Commission on Macroeconomics and Health follow-up work in countries. Geneva:WHO, 2005. Cited in Chapter 4, World Bank, Health Financing Revisited, forthcoming. 26 World Bank, Health Financing Revisited, forthcoming. 27 For further data about the per capita donor assistance for health by African country in 2004 and the donor assistance for health by type of health activity/service since 1973, see Figures 4.1.3 and 4.1.1 in Annex 1. 28 Lewis M. 2005, op. cit. 29 World Bank, Health Financing Revisited, forthcoming.



20

prominence of the GFATM on other multilateral assistance and on African health systems is further analysed in section 5 below. Figure 4.1.3: Trends in HIV/AIDS Financing by Source: Developing Countries

Source: M Lewis, 2005. Addressing the Challenge of HIV/AIDS: Macroeconomic, Fiscal and Institutional Issues. Note: External private includes only international NGOs; domestic funding includes public and private sources but NOT household expenses. A questionnaire survey of donor funding for malaria activities from 1999 to 2003, was undertaken by HLSP in 2004.30 The trend, which may be more important than the absolute figures, shows donor funding increasing over the period 1999-2002, followed by a small (10%) decrease in 2003, little change in 2004 and then a marked drop in 2005. However the data needs to be interpreted with care, especially for 1999 and 2005 where there were very few responses (see Figure 4.1.4). Figure 4.1.4: Donor financial contributions for Malaria Control

Overall Financial Contributions to Malaria Control Activities 1999 to 2005 (in US$)

020,000,00040,000,00060,000,00080,000,000

100,000,000120,000,000140,000,000160,000,000180,000,000

1999

2000

2001

2002

2003

2004

(pro

jected

)

2005

(pro

jected

)

Source: HLSP. December 2004. Survey of International Funding for Malaria Control; Prepared for the Roll Back Malaria Partnership (draft report).

30 The figures therefore most probably under-state the true picture because of the incomplete responses. For instance, the development banks were unable to provide detailed financial data and 8 out of 17 respondents expressed their difficulty in separating funding for malaria from their broader support to countries (through General Budget Support, SWAps and primary health care projects). See HLSP, 2004.



21

4.2 Impact of GHPs on commodity pricing and security Another area where GHPs may have made a significant difference has been on commodity pricing and security. The Green Light Committee (GLC) for multi-drug resistant tuberculosis (MDR TB) has leveraged its position as a major purchaser to increase supply security and decrease the price of quality-assured MDR TB drugs, achieving reductions of 85 - 99% on US prices of the 14 products procured for GLC-endorsed projects. Recently the Clinton Foundation managed to negotiate lower prices for ARVs. On the other hand, GAVI’s initial expectations of lower some vaccine prices over time have yet to be realised, and the WHO/Novartis partnership to provide the malaria drug Coartem (artemether-lumefantrine) at ‘cost’ pricing has had arguably mixed success.31

4.3 The Impact of Increased Debt Relief on Health Spending It is too early to assess the impact of recent debt relief initiatives such as the Gleneagles commitment to cancel the debts of some low income countries, mainly in Africa. However, the earlier HIPC initiative has been around for a while and some impact evaluations are available. Launched in 1996, forty-two countries are now eligible for HIPC relief, and another 38 are expected to qualify for such relief. As of 2005, 27 countries, including 23 in Africa, had reached the decision point and were receiving some interim debt relief. Nine African countries had reached the completion point (Benin, Burkina Faso, Ethiopia, Mali, Mauritania, Mozambique, Niger, Tanzania, and Uganda) as of May 2005.32

The initiative provides eligible countries with substantial savings in debt service payments. The relief committed to the 27 countries that have reached their completion points or are in their interim period, together with other debt relief, represents a two-thirds reduction in their overall debt stock. But what is relevant for this analysis is whether the beneficiary countries had access to resources for additional expenditures as a result of debt relief. Debt service payments relative to fiscal revenue in these 27 countries have declined from an average of 24 percent in 1998–99 to 15 percent in 2003 and are expected to decline to less than half the 1998–99 average by 2006.33 An important question is whether the resources made available through debt relief were used to increase expenditures in the social sectors. Progress on this front is measured by IDA and the IMF as the share of poverty-reducing spending to GDP and to total spending. The definition of poverty-reducing spending is country specific and includes, for example, outlays on basic health, primary education, agriculture, infrastructure, housing, basic sanitation, and HIV/AIDS. According to the IMF and IDA 2004 Status of Implementation Report, poverty-reducing expenditures in the 27 highly indebted poor countries have increased on average from 6.4 percent of GDP in 1999 to 7.9 percent of GDP in 2003.34

31 Grace C. Global Health Partnership Impact on Commodity Pricing and Security. DFID Health Resource Centre, 2004. 32 Hinchliffe K. The Impact of the HIPC Initiative on Public Expenditures in Education and Health in African Countries. World Bank, Human Development Department, Africa Region, 2004. 33 Hinchliffe K, 2004. op. cit. 34 Hinchliffe K, 2004. op. cit.



22

According to Hinchliffe (2004), while poverty-reducing expenditures increased on average from 39 percent in 1999 to 48 percent in 2003 as a share of total revenues in the 23 African countries, it increased by as much as 76 percent in Mozambique and declined by 27 percent in Chad. Of 20 countries for which there was full information, 13 showed significant increases in the share of total revenues directed toward poverty-reducing expenditures. Exceptions were Benin, Madagascar, and Niger, where the share remained roughly constant, and Chad, Ghana, São Tomé and Principe, and Zambia, where it fell. Comparisons across countries are not really valid, however, as the definition of poverty-reducing expenditures varies substantially from one country to another. The tendency for countries has been to widen the definition of “priority sectors.” In Ghana, the number of poverty-reducing areas has increased from 13 to 31. This wider definition can easily mask what is happening to expenditures in education and health, in particular. An analysis by Hinchliffe (2004) of the trend in health expenditures as a share of total government expenditures in 20 highly indebted poor countries between 1998 and 2002 shows that the share increased on average from 6.2 percent to 8.1 percent. Of the 20 countries, 13 showed increases, with exceptions being Guinea-Bissau, where data is not available for enough years to discern a trend; Malawi and Zambia, where the share remained essentially constant; and Burkina Faso, Ethiopia, Madagascar, and Mali, where the share declined.

4.4 Analysis of Aid Modalities Table A4.4.1 in Annex 1 presents a matrix of key aid modalities (e.g. development credits and debt relief under ‘fiscal space’ below). In this section, we present a summary analysis of some of the key aid modalities35. General budget support (not sector BS): Recent aid trends, and the received wisdom or current best practice, favour this approach as it gives maximum flexibility to countries to spend according to their own priorities, and integrates aid into national planning processes, utilising existing or beefed-up national M&E processes for reporting, thus cutting down on transaction costs of doing so separately for different programmes or projects etc. This approach can also address key cross-cutting and systemic issues, such as human resource constraints. Also, countries are in principle less likely to undertake investments with unaffordable long term recurrent cost implications if spending decisions are under their own control. Constraints include: this form of delivering aid is also the easiest for donors to cut (e.g. if the conditionality for one area is not met, or even for political reasons not related to macro-economic performance); and donors may have enhanced control over strategic direction of country policies. It also involves accepting that health may also not be the government’s top priority. Programme support including SWAPs: This involves more predictable donor and Government funding, with Government leading the sector. Priorities can be set jointly across the whole sector, instead of each donor (and Government) setting their own. It can also help build up national (sector) systems, resources can be allocated more equitably across districts, greater transparency and accountability of donors and Government can be achieved, and transaction costs are less than for project funding

35 The reader interested in a fuller analysis of aid instruments may contact HLSP in the UK ([email protected]) and ask either for the report “Aid Instruments: Distinctive Features, SWOT and Evidence on Impact” or the CD-Rom “Effective Development Assistance: A Guide to Aid Instruments”.

mailto:[email protected]



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but more than for general budget support. The sector approach may however undermine country-led policy coordination and macro-economic management. Project support: This offers donors maximum control over spending decisions, donors can set up monitoring and reporting systems in accordance with their own requirements and procedures (perhaps imposed by country legislation). Donors also have direct control over financial and administrative management of their projects. They can therefore report directly on outcomes. This approach can also bring resources to bear on under-funded health problems and in order to achieve clear targets e.g. in immunization. The constraints are: project support is not integrated into national planning processes and country priorities, it does not address systemic issues e.g. low salaries, most of the benefits usually go to only the areas of country where the donor has chosen to work in, thus possibly accentuating regional disparities (unless projects benefit mainly the poorest districts); there are high transaction costs associated with many separate donor projects, and such projects compete for scarce skills in country. They can also lead to duplication of efforts as well as problems of sustainability when project funding ends. Aid in kind: The advantages of this form of aid in avoiding macro-economic distortions are discussed under section 5.1. The constraints include: lack of flexibility for country in resource allocation (e.g. such aid may be tied to particular suppliers and/or branded goods in donor countries, and the quality of such goods may not be the best possible; thus the opportunity costs could be high for the recipient country). Hence aid in kind shares some of the problems of tied or project aid, though fungibility can mitigate them for the recipient country Government.



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5.0 SUSTAINABILITY AND EFFECTIVENESS OF AID AND FISCAL SPACE ISSUES

5.1 Aid sustainability Official development assistance in general and health aid in particular have been criticized for unpredictability and volatility of such funding; proliferation of disease- and intervention-specific programs, which are often not integrated into any particular country’s on-going programs; large numbers of new actors and donors; inflexibility of aid for dealing with sudden problems and crises; and lack of accountability of donors for the absence of results and progress. These problems reduce the impact of donor funding in achieving economic growth and health improvements.36

Unpredictability of future aid flows is a major problem related to the present international aid architecture, which has arguably been compounded by the GHPs. Poor countries are asked in effect to finance long term recurrent spending obligations on the basis of vague future donor aid commitments. The situation is worsened by the fact that data show quite clearly that substantial donor aid commitments consistently exceed actual disbursements.37 Yet aid recipients have to make budgetary projections (such as within the MTEF framework) using aid commitments which may not be realised to the degree planned for. Despite such aid fluctuations however, GHPs and some bilaterals have invested in programmes in African countries which generate long term recurrent costs (such as salaries, the running costs of new treatment centres, costs of vaccines and drugs etc) even though there is no guarantee that donor aid will be available over the long term. The case of Zambia’s 5-year HIV/AIDS strategic plan, presented below in Table 5.1.1, is instructive in this regard. The programme, very largely funded by donors, is more or less assured of adequate funding over the next three years. However, there is uncertainty about funding after 2008 from the two major sources of funding for the programme (PEPFAR and the GFATM), resulting in very large projected deficits thereafter, even with a 50% scale up scenario. Volatility and unpredictability of donor aid may be the result of:

Donor country conditions: for instance, political, legislative or budgetary processes.

Conditionality: disbursements may be suspended or stopped by donors due to non-compliance with conditions in a programme or the macroeconomic framework

Absorptive capacity off recipient country: Problems such as lack of administrative capacity or inefficiencies in public expenditure management (which inhibit resources already disbursed from reaching the projects or program executing units) may originate in the recipient country.38 However, problems may also emanate from donors, which may have burdensome procurement and reporting requirements.39

36 Chapter 4 of World Bank, Health Financing Revisited, forthcoming. 37 Foster, M. MDG-Oriented Sector and Poverty Reduction Strategies: Lessons from Experience. Health, Nutrition, and Population Discussion Paper, World Bank, Washington D.C, 2005 38 In the Zambian case depicted in Table 5.1.1, annual levels of funding from the GFATM has in fact been discounted to take account of past experience of delayed disbursements and inability to optimally access the funds committed from the Global Fund’s Rounds 1 and 4. This is also why there appears to be some (reduced) funding available for 2009-10. 39 World Bank, Health Financing Revisited, forthcoming.



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Exchange rate fluctuations: Commitments are often stated or reflected in U.S. dollars, therefore exchange rate fluctuations between the currency in which donors make their commitments and the U.S. dollar and between the U.S. dollar and the local currency affect volatility.

Table 5.1.1: Projected expenditure and funding of Zambia’s 2006 – 2010 National HIV/AIDS Strategic Framework

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Data Table- 50% scale upITEM 2006 2007 2008 2009 2010

ESTIMATED EXPENDITURE 268,225,861 275,486,769 242,620,193 255,795,080 257,778,401 1,299,906,303 124,853,452 116,702,712 88,556,876 89,761,768 90,304,000 510,178,808 ALL DISTRICTS & PROVINCES 84,038,459 86,058,507 87,324,942 96,008,093 94,000,449 447,430,451 LINE MINISTRIES 11,862,009 12,609,316 13,227,172 13,875,304 14,555,194 66,128,995 NAC 14,427,831 24,990,345 16,664,145 17,497,352 18,372,220 91,951,894 CIVIL SOCIETY ORGANISATIONS 24,120,517 25,640,110 26,896,475 28,214,403 29,596,908 134,468,414 PRIVATE SECTOR 8,923,592 9,485,778 9,950,581 10,438,160 10,949,630 49,747,741

ESTIMATED FUNDING 271,849,321 271,849,321 271,849,321 82,449,321 82,449,321 980,446,603 UN Family (Includes WB) 20,000,000 20,000,000 20,000,000 11,600,000 11,600,000 83,200,000 JICA 3,205,785 3,205,785 3,205,785 3,205,785 3,205,785 16,028,925 USG 148,000,000 148,000,000 148,000,000 444,000,000 NORAD 2,850,000 2,850,000 2,850,000 2,850,000 2,850,000 14,250,000 Netherlands 1,210,090 1,210,090 1,210,090 1,210,090 1,210,090 6,050,450 DCI (Ireland) 3,751,279 3,751,279 3,751,279 3,751,279 3,751,279 18,756,395 SIDA 3,933,333 3,933,333 3,933,333 3,933,333 3,933,333 19,666,667 Global Fund 52,800,000 52,800,000 52,800,000 19,800,000 19,800,000 198,000,000 ADBDFID (UK) 7,065,200 7,065,200 7,065,200 7,065,200 7,065,200 35,326,000 EU 4,033,633 4,033,633 4,033,633 4,033,633 4,033,633 20,168,167 Private Charities and Foundations 10,000,000 10,000,000 10,000,000 10,000,000 10,000,000 50,000,000 GRZ 15,000,000 15,000,000 15,000,000 15,000,000 15,000,000 75,000,000 GAP (ESTIMATED FUNDING - ESTIM 3,623,460 3,637,448- 173,345,759- 175,329,080- 319,459,700- 29,229,128

GRAND 5-YEAR TOTALS

ANNUAL TOTALS

Source: C Atim. Jan 2006. Costs and Financing of the 2006 – 2010 Strategic Framework: Report to NAC / Joint Financing Technical Working Group, Lusaka, Zambia. The proliferation of disease- and intervention-specific international aid programmes have arguably raised global awareness and focused attention on global health issues such as HIV/AIDS and vaccinations, as well as bringing significantly increased resources to bear in responding to these challenges. However, such programmes also have the potential to disrupt a country’s health system. The expenditures they generate may not be sustainable within the recipient country’s budget constraints. In addition, the global programs are not accountable to the recipient country. Thus, focusing solely on disease-specific initiatives can miss the opportunity to integrate with the country’s overall health program, fragment outreach, raise the demand for management skills that are already in short supply, and bleed the health system of financial and human resources in order to set up a parallel delivery operation, possibly delaying much needed institution building in the health sector.40

Data examined earlier in this paper show that some African countries are heavily aid dependent, and some of them receive annual inflows of donor resources that dwarf their health budgets. Apart from the sustainability and absorptive capacity concerns just discussed, there are other potential macro-economic risks associated with such relatively large aid inflows. The main ones are currency appreciation and inflation.

40 Lewis M. 2005, op. cit.



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Large aid increases have the potential to lead to currency appreciation and a drop in a country’s export competitiveness (the so-called ‘Dutch Disease’) and hence to slower economic growth. It is usually contended that if increased aid is spent on imported drugs or other such commodities, then this should not result in any macro-economic distortions, since there is no effect on domestic demand and on the current account. On the other hand, if aid is spent on domestic services, the resulting increased demand for domestic factors such as labour will create an upward pressure not only on wages and hence on inflation, but also on the exchange rate, since the inflow of foreign aid has not been matched by increased demand for imports.41,42

A number of suggestions have been put forward to try and mitigate the impact of the above problems that can arise from aid inflows. Among these suggestions, are the following:

Various proposals to make future aid flows more certain, and less subject to annual donor budget allocations. Specific measures suggested include: the IFF (and the ‘mini IFF’ recently established to support GAVI), the proposed tax on aviation fuel or airfares, global carbon taxes, tax on currency speculation (the ‘Tobin tax’) or the use of IMF gold sales or SDR issues to fund development finance. These proposals have the merit that, once agreed, they provide a secure stream of additional global development finance.43

Better harmonization and alignment among donors plus a single overall national policy and planning framework for public expenditure, including all donor aid, and coordinated by national authorities in accordance with their own national priorities. This does not preclude diversity of funding sources, decentralisation and types of service providers.

Best practice approaches to budget support try to address the problems by medium term indications of support, earlier commitment in time for budget preparation, disbursement early in the budget year, and reduced conditionality applied to the following year’s commitment to avoid interrupting the current budget, with only a portion of funding at risk from policy failure in any one area of performance.44

Some experts suggest that these measures may not be sufficient to persuade Governments to take the risk of relying on aid to significantly increase their public expenditure obligations, in the light of the long history of volatile aid that falls short of promised levels. In order to provide the required assurances, a DFID-funded study proposes the establishment of an Aid Guarantee Facility that poor and highly aid dependent countries could draw on if donors do not fulfil promises of increased aid. It would also be drawn on to slow any decline in aid, to give more time for managing the consequences. The guarantee would be limited to budget and programme support, ensuring that aid shortfalls do not create financing gaps in the Government budget.45

41 Lewis M. 2005, op. cit. 42 However it is important to point out that this does NOT lead to an automatic policy recommendation in favour of using aid money for imported goods, because a country’s development and economic priorities will mainly determine the optimal policy mix regarding how much to spend on imported goods and on domestic services with available aid inflows. 43 Foster M. 2005, op. cit. 44 Foster M. 2005, op. cit. 45 Foster M. 2005, op. cit.



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Governments of recipient countries can also act to mitigate volatility by prudent public expenditure management. For instance, Ghana avoided a currency appreciation by saving some of its increased aid through accumulation of reserves. Even where aid is earmarked and tracked, it has been suggested that the same effect can be achieved through using resource allocations under Government’s control to substitute for donor funds going to particular programmes (fungibility!).46

5.2 Fiscal Space and Efficiency of Resource use in Health Having discussed the scale of the health financing challenge facing African countries if the Abuja and MDG targets are to be met (even with the additional projected aid resources coming on stream), and relevant aspects of the international aid architecture, what options are available to countries to increase resources available for spending on health? Providing fiscal space allows countries to allocate resources to their top priorities in a sustainable manner. This section briefly analyses alternative financing mechanisms available to AU countries and the main factors constraining their expansion. The possible Instruments/methods for increasing the fiscal space available to countries include the following. Taxation: International experience shows that most African countries fall within the low taxation category, with overall tax rates well below 20% of GDP. It has been suggested that many low income countries could make it a target to raise their tax levels to at least 15% of GDP, although this is easier said than done.47 Developed countries typically have tax shares of around 40% of GDP and above. However, there are significant obstacles to raising more taxes in low income countries. These include technical capacity and administrative bottlenecks (including inability to collect taxes from large sections of the population whose level and sources of income are difficult to estimate or ‘invisible’ to state agencies), inefficient tax collection systems, unacceptability of tax increases as the tax burden may already considered as too high by formal sector populations. Low ratios of tax to GDP imply that developing countries have room to increase revenues from taxation to accommodate some increase in expenditures, including those for health. Developing countries may want to replace narrow, distorting tax bases that have widely differentiated rates and numerous loopholes with broader tax bases that generate higher revenues at lower rates and do not discriminate against the various sources and uses of income. Doing so would result in efficiency gains and greater administrative simplicity and horizontal equity. However, the practical difficulties of implementing tax reforms must not be underestimated. Increasing revenues through tax reforms affects many interests and cannot be done effortlessly, especially when institutional changes in the tax authorities are required, rural and informal sectors are important, borders are large, and wealthy elites are politically powerful. Countries are unlikely to attempt tax reforms only to accommodate additional health expenditures within their budget constraints. Earmarked taxes (including ‘sin’ taxes on alcohol, tobacco etc) may be easier to sell to the populace but entail the disadvantage that they pre-empt a possibly more efficient allocation of such revenues by preventing their being put to potentially more cost-effective uses.

46 Lewis M. 2005, op. cit. 47 Heller, P. Understanding Fiscal Space. International Monetary Fund, Washington, D.C. 2005



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Greater efficiency, or reallocating from lower to higher priority areas, and other efficiency improvements: Although using resources more efficiently will not increase the total envelope, it could enable achievement of goals at less cost, or permit more/better outcomes with the same envelope. Even within the same total envelope, it may be possible to improve outcomes significantly by re-allocating resources from lower to higher priority areas. e.g. military to health, tertiary to primary care. We saw earlier that some countries spend a significant amount of their resources on the military, and others focus health sector resources on tertiary facilities as opposed to more cost-effective primary level ones (interventions having highest marginal impact on health outcomes). Other areas of unproductive or lower priority expenditure that could be curtailed to the benefit of priority programmes include foreign travel by top officials, foreign embassies, and ‘ghost’ civil servants. Also, reducing corruption and improving governance can increase fiscal space. In some situations, efficiency gains may be made if Government policies encouraged more public-private partnerships (PPP) in service delivery as well as in other areas of spending. Public financing need not always imply public provisioning. Aid: An increased level of aid resources would increase fiscal space, ceteris paribus. But such resources must be sustained and predictable, to enable countries to scale up expenditure in the knowledge that such investments would be sustained in future, instead of creating uncertainty about future flows. According to the IMF, “greater predictability and reduced volatility is enormously important in creating fiscal space”.48 Another caveat about increased aid is to do with absorptive capacity of the country concerned, as well as issues of existing levels of aid dependency and related questions of sustainability (see next major section below on international context). Borrowing: Borrowing (both internal and external) constitutes another option for the financing of additional expenditure, including on health. However, as such loans have to be repaid (usually with interest, even if it is concessional lending), care needs to be taken to ensure first that the expected return on the loan spending is worth the cost of the loan, and second that such loans are spent in a way as to increase government revenues to enable repayment of the loan, unless the overall strength of the economy and debt repayment and service obligations are such that the loan can be justified on other socio-economic grounds. Factors that might influence the decision to take a loan include the expected economic growth rate, projections of exports growth and remittances, the interest rate regime, the composition of existing debt (in terms of interest rates, maturity, currency of borrowing), and the terms of new debt being considered.49

Debt relief: While in principle, countries can increase their fiscal space through additional borrowing as suggested above, a good number of SSA countries already have a high debt burden and so have limited room for additional borrowing. Furthermore, the scaling up of key health services as required by the MDGs and financed for instance by the Global Health Partnerships (GHPs) entails increased spending on recurrent items (such as human resources). It would not be sustainable or wise policy to finance such recurrent expenditure with loans. Debt relief would release domestic resources that could be used for additional investment and recurrent spending in the country. The HIPC Debt Initiative aims to increase the

48 Heller P, 2005. op. cit. 49 International Monetary Fund. Debt Sustainability in Low-Income Countries—Proposal for an Operational Framework and Policy Implication. 2004a.



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financing available for the social sectors in the target countries. It is also intended to help address constraints to improved health, nutrition, and population outcomes.50 Remittances and foreign direct investment: These sources account for around $250 billion of annual capital flows into developing countries, and governments could offer appropriate policies and institutions to attract such foreign investments and to use workers’ remittances from abroad to help increase fiscal space for health spending. (See also figure 4.1.1 above.) Printing money: One way to create fiscal space is to print more money, or borrow money from the central bank! However, although Governments have a perpetual licence to print money, this licence or power must be used with extreme caution. To avoid creating inflationary pressures in the economy as a whole, the printing of more money must be aimed primarily at the creation of sufficient liquidity to support an economy’s real growth and not principally to enable the government to increase its expenditure levels. The IMF estimates that the scope for additional expenditure that can be financed in most developing countries by money creation is rarely above 1 percent of GDP, unless a clear and relatively quick supply-side impact can be obtained from the higher level of expenditure. Reorganisation of health financing system: Fiscal space can be increased by implementing or supporting innovative new health financing mechanisms that have been emerging in African countries in recent times, although some of these new mechanisms have so far mainly been in experimental stage. Such mechanisms include community based health insurance (CBHI) and social health insurance (SHI). There is some evidence that CBHI schemes reduce out-of-pocket spending, improve health service utilisation rates by members and enable communities in some countries (e.g. Senegal, Ghana) to begin a welcome process of (initially limited) negotiation and dialogue with health providers. They also have a potential to raise additional resources for health; however, the evidence so far suggests that this potential remains unrealised for many existing schemes. They also have other limitations too. Frequently, their small size, limited resources and limited management skills leave them vulnerable to shocks and financial stability risks. Government may therefore have an important role to play to help such schemes achieve their potential.51 Some African countries, including Tanzania, Kenya, Cote d’Ivoire, Gabon, Rwanda, Ghana, Nigeria etc. are considering introducing or implementing social health insurance for their population. If well implemented and managed, such schemes have the potential to:

Increase resource mobilization for health— equivalent to introducing a new “tax.” Improve health care access to poor and vulnerable populations by eliminating

financial barriers to such access and improving the quality of existing services. Improve equity—redistributing income and ensuring equitable access to medical

services. Improve health care quality by introducing greater transparency and powerful new

demand-side organisations (the national health insurance fund or agency) which

50 World Bank, Health Financing Revisited, forthcoming. 51 Although it is important to stress that one of the key factors often cited for the limited relative success of such schemes in West Africa for instance, has been the community ownership and control of them, their greater accountability to communities (engendering enhanced confidence in them) plus their low administrative costs and autonomy from state control etc. Nearly all these aspects risk being undermined by inappropriate forms of state intervention.



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can negotiate on behalf of consumers and use innovative mechanisms such as capitation payments to encourage desirable provider behaviour. However, the challenges to successful implementation and achievement of the above goals are many and complex in the most African countries (with the exception of high income and highly urbanised ones like South Africa). They include low per capita incomes, large rural and informal sector population compared to formal ones, lack of administrative and technical skills, poor quality of public health infrastructure and inadequate governance systems.



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6.0 CONCLUSIONS The main conclusions from the analysis in this paper are:

Most African countries are spending very low amounts on health, by almost any measure.

Out of pocket spending is especially high in many of these countries (up to 80% of all private spending and 50% of overall spending), reflecting low levels of Government spending.

Increasing public spending on health is therefore essential in those countries to: o Reduce high levels of impoverishing out of pocket expenditure o Achieve the international targets for achieving various health sector goals.

The Abuja Declaration target, the CMH and health MDG ones Estimates of what difference the Abuja targets would make to achieve the CMH

and MDG targets show that more than half of all AU members would not have made great progress towards attaining them, based on 2002 data, even if they met the Abuja target.

While achieving the Abuja target is important to show commitment towards increasing the share of public spending going to health, in many African countries, this would not be enough to assure a decent package of health services to the population. For this, it is necessary for states to commit themselves (together with their partners) also to attaining the CMH target of at least $34 per capita spending on health.

All estimates of what is required to attain those targets show that the financing gap between currently available funds from all sources and what is needed is huge and well beyond what many of the countries can mobilize under any realistic scenario. Those estimates range from US$20 to US$70 billion per annum until 2015.

Official development assistance increased by nearly fourfold between 1990 and 2003, and is the main source of external finance in Sub-Saharan Africa, accounting for more than 55 percent of total external flows in 2003. A lot of the increase is due to the entry of the GHPs and new private foundations onto the international funding scene.

The advent of the new global health partnerships and increased bi- and other multilateral assistance for specific health interventions has also met with some criticism for accentuating certain problems associated with the international aid architecture: unpredictability and volatility of donor funding; proliferation of disease- and intervention-specific programs, which are often not integrated into any particular country’s on-going programs; large numbers of new actors and donors; other macro-economic distortions, and lack of accountability of donors for the absence of results and progress.

The evidence seems to be that the recurrent costs of GHP investments (human resources required to deliver the new programmes, new treatment centres, costs of vaccines and life-saving drugs, etc) are not sustainable for many low income countries.

The paper also reviewed some proposals for mitigating the impact of the above problems as well as how to provide fiscal space so that countries can allocate resources to their top priorities in a sustainable manner.



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ANNEX 1: TERMS OF REFERENCE (FINANCING PAPER) Development of Technical Papers for the Africa Heads of State Summit on HIV/AIDS, TB and Malaria (revised 07/02/06) February 2005 1. This paper will provide an outline of the principal financing factors affecting the

slow progress in reaching agreed targets in Africa regarding the control and eventual elimination of HIV/AIDS, TB and Malaria. The paper shall also suggest the necessary actions that need to be taken to overcome financial constraints.

2. A critical issue is scaling up financing to the health system up to the levels

recommended by the Macroeconomic Commission on Health. This requires creating predictable aid flows that will increase spending in health and allow for the expansion of health services to achieve the MDGs. It is critical to overcome the fiscal constraints imposed by uncoordinated and unpredictable aid flows.

3. The analysis of financial factors should take a broad approach to health sector

financing, considering factors both within and external to the sector, both domestic and international such as available finance both from domestic and from international sources, absorptive capacity, efficiencies, shortfalls, potential new sources, etc.. An indicative, but not exclusive, list of factors to be taken into consideration includes:

• A description of all funding in the health sector including state funding, but

also private spending. It would be useful to prepare league tables including:

a. total spending per capita in the health sector using PPP b. total government spending per capita c. percentage of health per GDP d. percentage of health for all government spending e. percentage of education of all government spending f. percentage of military of all government spending

• Fiscal space data: Mid-term growth and expenditure plans and fiscal space

for expansion in public health spending. The efficiency with which available resources are utilized, including the absorptive capacity of health systems to spend money effectively;

• Overseas Development Assistance (ODA) financing:

a. health as percentage of total ODA b. composition of health spend

1. HIV/AIDS: delineate major projects (e.g. GFATM, WB, etc) 2. TB (map of projects) 3. malaria (map of projects) 4. child survival 5. reproductive health 6. general health



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• The appropriateness, or otherwise, of national health budgets, within the overall constraints of relatively poor economies;

• Where possible the flow of resources within the health system, including the

proportion that reaches sub-national and local levels;

• The balance between promotive, preventive and curative spending;

• An analysis of source and use of funds based on NHA principles including all fiscal intermediaries like social and private health insurance, including the mix of various financing instruments and their relative advantages and disadvantages.

• The roles of international bilateral and multilateral donors, charitable

foundations, international NGOs and global funds;

• Description of broader aid modalities: General budget support, sector-wide swaps, PRSP credits etc. The appropriateness and effectiveness (or otherwise) of different aid modalities in various situations: general budget support, sectoral budget support, development credits versus grants, global funds, aid in kind, technical assistance, direct funding of NGOs and FBOs, etc. What role do various conditionalities play, and what are the transaction costs associated with the various modalities?

• The impact of increased debt relief on combating these key diseases

• The role of international and domestic health commodity markets (drugs,

nets, vaccines, test-kits, condoms, etc.) in making vital commodities affordable

• What is the approximate shortfall in currently available financing if the MDGs

and Abuja Targets are to be met? How much of this could potentially be met from increasing domestic resources and improving efficiencies? Part of fiscal space. Use estimates from macro-economic commission estimates.



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ANNEX 2: League Tables - Selected Indicators in PPP (international) Dollars

Per capita total expenditure on health at international dollar rate

Per capita government expenditure on health at international dollar rate

Total expenditure on health as % of gross domestic product

General government expenditure on health as % of total expenditure on health b

General government expenditure on health as % of total government expenditure

Member State

2001 2002 2001 2002 2001

2002 2001 2002 2001 2002

Angola 87 92 45 39 5.3 5 51.8 41.9 5.4 4.1 Benin 44 44 20 19 4.9 4.7 46.2 44.4 11.9 11.1 Botswana 331 387 188 240 5.4 6 56.7 61.9 6.3 7.5 Burkina Faso 35 38 14 17 4.1 4.3 39.7 45.9 8.7 10.6 Burundi 16 16 3 3 3.2 3 20.8 21.5 2.2 2 Cameroon 64 68 17 18 4.5 4.6 26.2 26.2 7.4 7.9 Cape Verde 188 193 142 145 5 5 75.8 75.1 12.4 11.1 Central African Republic 48 50 19 21 3.7 3.9 39.4 41.6 9.6 7.4 Chad 45 47 19 20 6.6 6.5 41.5 41.9 13.6 12.2 Comoros 22 27 10 16 2.3 2.9 46.9 58 6 8.2 Congo 24 25 17 18 2.1 2.2 69 70.3 5.7 6 Côte d'Ivoire 110 107 22 24 6.2 6.2 20.1 22.4 7.5 7.2 Dem Republic of Congo 12 15 2 4 3.5 4.1 18.2 30.2 13.5 16.4 Equatorial Guinea 117 139 82 100 1.7 1.8 70.1 72.2 9.8 9.8 Eritrea 34 36 21 23 5.1 5.1 61.5 63.7 5.3 5.6 Ethiopia 20 21 8 9 5.4 5.7 41.4 44.9 7.6 7.6 Gabon 240 248 105 102 4.2 4.3 43.5 41.3 5.9 6.3 Gambia 85 83 37 37 7.2 7.3 43.7 44.6 9.4 12 Ghana 71 73 29 30 5.6 5.6 40.9 41 8.5 8.4 Guinea 93 105 16 16 5.3 5.8 16.8 15.5 4.8 4.8 Guinea-Bissau 40 38 19 18 6.1 6.3 46.6 48.2 6.6 8.5 Kenya 70 70 30 31 4.9 4.9 42.8 44 7.7 8.4 Lesotho 102 119 86 101 5.6 6.2 83.7 84.9 10.3 10.9 Liberia 15 11 11 7 2.9 2.1 71 68 5.9 5.5 Madagascar 19 18 12 10 1.9 2.1 64.1 55 7.1 8 Malawi 46 48 20 20 9.4 9.8 43.6 41.1 9.9 9.7 Mali 29 33 15 17 4.4 4.5 50.1 50.8 8.2 9 Mauritania 39 54 26 40 2.9 3.9 67.9 74.2 8 10.1 Mauritius 305 317 229 244 2.8 2.9 75 76.9 7.6 8.3 Mozambique 44 50 31 36 5.5 5.8 69.8 71 18.2 19.9 Namibia 347 331 247 232 6.9 6.7 71.1 70.1 13 12.9 Niger 28 27 14 14 4.3 4 49 50.8 10.8 10 Nigeria 42 43 13 11 4.5 4.7 31.4 25.6 3.4 3.3 Rwanda 44 48 25 27 5.5 5.5 55.4 57.2 14 13.4 Sao Tome and Principe 100 108 88 95 10.5 11.1 87.6 87.7 11.4 14.5 Senegal 62 62 28 28 5.2 5.1 45.1 45.2 10.8 11.2 Seychelles 568 557 430 414 5.3 5.2 75.7 74.3 8.1 6.6 Sierra Leone 29 27 18 16 3.7 2.9 61 60.3 8.8 6.8 Somalia 13 n/a 6 n/a 2.6 n/a 44.6 n/a 4.2 n/a South Africa 673 689 277 280 8.7 8.7 41.2 40.6 11 10.7 Sudan 51 58 10 12 4.5 4.9 19.7 20.7 5.4 6.3 Swaziland 300 309 174 184 6 6 57.9 59.5 11.3 10.9 Togo 128 163 18 18 10.1 10.5 14.3 10.8 8.6 7.8 Uganda 72 77 20 22 7.3 7.4 27.3 27.9 9.6 9.1 United Republic of Tanzania 31 31 17 17 5.2 4.9 55.3 54.8 16.9 14.9 Zambia 50 51 26 27 5.7 5.8 52.8 52.9 9.4 11.3 Zimbabwe 157 152 74 78 7.7 8.5 47.4 51.6 9.6 12.2 Source: Prepared by World Bank Staff. d Health data for year 2002 have been largely developed by WHO, as they were not yet available through the OECD Health Data 2004. e Official exchange rates have been used. 'n/a' Used when the information accessed indicates that a cell should have an entry but no figures were available.



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ANNEX 3: Role of Sub-Regional Economic Groupings Sub-regional groupings such as ECOWAS and SADC bring significant added value to national and international efforts in responding to the challenges posed by HIV/AIDS, TB and malaria, although as their activities are generally funded through the same ODA sources discussed above, their contribution in terms of additional financial resources is probably negligible. Their added value lies generally in organising cross-country programmes and inter-country coordination in the responses to these challenges and to tackle health issues that are outside the domain of national boundaries. Since SADC is operating in the highest burden sub-region for HIV/ADS, it has perhaps not surprisingly the most developed programmes in this regard. SADC has developed the SADC Business Plan on HIV and AIDS which seeks among other things to produce harmonized guidelines for the region on strengthening national coordination, developing best practices for the region, and strengthening collaboration and networking in the region. These activities are being undertaken within the context of the Maseru Declaration, the SADC HIV and AIDS Strategic Framework and Programme of Action 2003-2007 adopted by Heads of State and Governments, and are mostly funded by DFID and the EU.

FINANCIAL FACTORS AFFECTING FACTORS SLOW ... - …siteresources.worldbank.org/.../21032808/Financialfactors.pdf · Summit on HIV/AIDS, TB and Malaria, ... Financial Factors Affecting

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