Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine
ß The Author 2012; all rights reserved. Advance Access publication 13 December 2012
Health Policy and Planning 2013;28:871–883
doi:10.1093/heapol/czs126
Six concerns about the data in aid debates:
applying an epidemiological perspective to the
analysis of aid effectiveness in health and
development
David Stuckler,1,2* Martin McKee2 and Sanjay Basu2,3
1
Department of Sociology, University of Cambridge, Free School Lane, Cambridge CB3 3RQ, UK, 2London School of Hygiene & Tropical
Medicine, Department of Public Health and Policy, 15-17 Tavistock Place, London WC1H 9SH, UK and 3Department of Preventive Medicine,
Stanford University, Palo Alto, CA, USA
*Corresponding author. Magdalene College, Cambridge CB3 0AG, UK. E-mail: [email protected]
Accepted
6 November 2012
Is aid helping, hindering, or having no effect on development and health? The
answer to this question is highly contested, with proponents on all sides adhering
strongly to their competing interpretations. We ask how it is possible for those who
are often using the same data to hold such divergent views. Here, we employ an
epidemiological perspective and find that, in many cases, the arguments are
characterised by methodological weaknesses. There may be selective citation of
results and failure to account for bias and confounding, such as where an
extraneous factor influencing the outcome is correlated with increased aid or, in
confounding by indication, where increased aid is a consequence of a country being
in an especially adverse situation. Studies may also lack external validity, whereby
lack of data (a widespread problem) or similar considerations mean that analyses
are undertaken on an unrepresentative subset of countries. Multiple outcome
measures can also be problematic, where the main outcome of interest is not
specified in advance. Many studies fail to account for differential time lags between
changes in aid and the outcomes being studied. Some studies may also be
underpowered to detect an association where one exists. Although, ideally, this
debate should be informed by large scale randomised controlled trials, this will
often be unfeasible. Given this limitation, it is essential that those engaged in it are
cognisant of the many methodological issues that face any observational study.
Keywords
Aid, critique, development
KEY MESSAGES
Debates on aid effectiveness largely overlook multiple sources of bias that are well recognized from an epidemiological
perspective.
Often aid analyses rely on inappropriate exposure and outcome variables, without specification of time lags, causal
mechanisms and net effects.
Most aid effectiveness analyses are biased towards the null hypothesis of no effect.
Strong policy conclusions about the effectiveness of aid are not justifiable based on the existing quality of data and
evidence.
871
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HEALTH POLICY AND PLANNING
Introduction
The past decade has seen a vociferous argument about whether
international development assistance for health is a help or a
hindrance to recipient countries. On the one hand, the World
Health Organization’s Commission on Macroeconomics and
Health called for a massive scaling up of assistance to lowincome countries as a means of enhancing health and economic
growth and thus helping them to make progress towards
the Millennium Development Goals (Commission on
Macroeconomics and Health 2002). Its chair, Jeffrey Sachs,
reiterated that call in his book The End of Poverty, although
emphasizing that these resources must be tailored to each
country’s circumstances (Sachs 2005). Others have argued that
the benefits of development assistance are either non-existent
(Raghuram and Subramanian 2005; Chauvet and Guillaumont
2008) or potentially exaggerated (Ravishankar et al. 2009; Lu et al.
2010), with the latter exemplified by a failure of aid to reach
groups it intends to help. One recent analysis finding that
each additional $1 development assistance for health is associated
with only $0.37 health expenditure as recipient countries
divert their own resources to other budgets, such as the military
(Lu et al. 2010), whereas another finds that the figure is even
lower in those countries receiving support from the International
Monetary Fund, with its associated conditionality (Stuckler et al.
2011). Yet, a further group argues that development assistance
is actually harmful.
The two most prominent aid critics are William Easterly
(‘White Man’s Burden’) and Dambisa Moyo (‘Dead Aid’). Their
critiques of aid have a long history in economics, as since the
1970s economists began transposing arguments about dependency theory—of how market integration may cause adverse
economic outcomes—to assess aid-dependency theory
(Bornschier et al. 1978). To quote Easterly and Moyo directly,
they state, e.g. global aid increases risks of war (‘aid increases
the risk of conflict’, Moyo 2009, p. 60), promotes corruption
and weakens democracy [‘By providing funds, aid agencies
(inadvertently?) prop up bad governments’, Moyo 2009, p. 57;
‘Today’s system of foreign aid coddles (and probably worsens)
bad governments’, Easterly 2006, p. 157], undermines social
capital (‘Foreign aid does not strengthen the social capital – it
weakens it’, Moyo 2009, p. 58), reduces savings (Moyo 2009,
p. 46 and 61) and, overall, is bad for economic growth (‘no
evidence that aid raised economic growth’, Easterly 2006,
p. 48). We need to get rid of dependency on Western aid (‘the
more it infiltrates, the more it erodes, the greater the culture of
aid-dependency’, Moyo 2009, p. 37); ‘aid-imperialism’ (Easterly
2008) is how the West holds back the developing countries
(‘What is it about Africa that holds it back, that seems to
render it incapable of joining the rest of the globe in the
twenty-first century? The answer has its root in aid’, Moyo
2009, p. 7). ‘No longer part of the potential solution, it’s part of
the problem – in fact aid is the problem’ (Moyo 2009, p. 47).
How is it possible for such divergent views to (co)exist, with
one camp viewing aid as a panacea and another group seeing it
as a curse? We suggest that there are several methodological
concerns with these divergent arguments. Unfortunately, till
now, these issues have not been sufficiently addressed in the
development or economics literature. In this article, we
approach the debate from a different disciplinary perspective
that of evidence synthesis as employed in epidemiological and
health services research.
Methodological issues
Narrative reviews
Many of the most widely read texts on the effectiveness of aid
draws heavily on case studies from individual countries. Thus, the
critics of aid draw attention to countries such as Botswana, that
have prospered with little or no development assistance and
others that have received large sums of aid but to little effect
(Easterly 2007) or even been extremely damaging, as in Rwanda
where one author has invoked development assistance as a factor
in the genocide (Andersen 2000). In contrast, the proponents of
aid draw attention to what they see as countries that have
benefited from aid, such as Tanzania and Ghana (Sachs et al.
2004). These reviews often lack a systematic approach to
inclusion, raising the possibility of selective citation with consequent misleading results. They also fail to account for confounding factors and bias (to which we return). Studies of similar
narrative reviews in medicine have shown that the results can be
highly misleading (Schmidt and Gotzsche 2005). Such analyses
often draw on personal stories. These have the ability to capture
the human consequences of the phenomena being discussed and
do influence decision making. However, the influence these
stories exert on policy is still poorly understood, leading the
authors of a recent systematic review of their role in decision
making to call for caution in their use (Winterbottom et al. 2008).
Bias and confounding
Aid is only one of many factors involved in development,
whether the outcome is measured as health, wealth or in some
other way. Ideally, an analysis of the effects of aid would
compare what happens when it is given and when it is
withheld, ‘all else being equal’, referred to in social science as a
‘counterfactual’, and ideally tested by a randomized controlled
trial. Clearly it is not possible to develop such a counterfactual,
because of both the ethical constraints on withholding aid and
the challenge of holding all other factors equal. Thus, it is
necessary to infer aid’s effectiveness from observational studies
that exploit differences in levels of aid across recipient groups
and over time. Yet, as is well recognized in epidemiology, such
analyses can be highly misleading because of the scope for bias
and confounding of various forms (Britton et al. 1998). These
can affect both the internal validity of the findings (is the
comparison a fair one?) and the external validity (can the
findings be extrapolated from the sample of countries to all
countries?). All these problems can be identified in the debate
on aid effectiveness.
Internal validity can be compromised where comparisons are
unfair, in this case of countries receiving large amounts of aid
and those not (Raghuram and Subramanian 2005). A highly
cited paper by Burnside and Dollar purportedly showing that
aid is beneficial where good policy environments exist has been
subjected to this critique (Burnside and Dollar 2000; Easterly
et al. 2003) and other cross-national analyses (Collier and Dollar
2002; Raghuram and Subramanian 2005; Roodman 2007). The
main concern is confounding, where an extraneous factor is
correlated with both the putative explanatory factor and the
AID DEBATES AND EPIDEMIOLOGICAL PERSPECTIVES
outcome. An example is the tendency for some types of donor
aid to be subject to conditions, such as those requiring
structural adjustment programmes. In such cases, increased
aid may be diverted to national reserves rather than to
spending that might benefit the populations concerned, as is
the case in many countries in receipt of support from the
International Monetary Fund (Stuckler et al. 2011). More subtle
forms of confounding include confounding by indication. This
bias arises when a factor increases (or decreases) both the
probability that an intervention will be administered and the
outcome of that intervention. Thus, factors that render a
country in need of aid, such as an influx of refugees to
neighbouring countries, may be associated both with an
increase in aid from donors and, because of coincident
challenges of establishing governance systems, a diminished
ability to utilize it effectively. A related issue is confounding by
severity (Salas et al. 1999), where the scale of the problem
facing a country increases the amount of aid that it receives. An
example from medicine is the finding that reducing blood
pressure too far in men with hypertension was associated with
a greater risk of heart attacks (Merlo et al. 1996). This
implausible result was believed to have arisen because those
at greatest risk of heart attack were treated most intensively
(Grobbee and Hoes 1997). Another study of stroke patients
suggested that those receiving sub-optimal care achieved worse
outcomes than those whose care complied with guidelines.
However, this was largely due to those at greatest risk obtaining
better quality care (de Koning et al. 2005). In one study
Raghuram and Subramanian acknowledge this issue and seek
to correct the bias that results from poor countries receiving
greater aid using instrumental variable approaches (Raghuram
and Subramanian 2005).
Protopathic bias is a related phenomenon whereby an
intervention is given in response to the first symptoms that
presage subsequent outcomes unrelated to the intervention. For
example, aid might be increased in response to an apparent
natural disaster that really reflected emerging failures of
governance. The increased aid could then be seen, incorrectly,
as leading to the governance failure. Early research on the
causes of uterine cancer was misleading because many of those
receiving treatment with oestrogen, which was linked with
development of cancer, had been prescribed it because of an
earlier episode of uterine bleeding, itself likely to have been an
early sign of the cancer (Horwitz and Feinstein 1980).
In the absence of a randomized controlled trial, it is possible to
use various methods, such as structural equation modelling, to
obtain insights into the existence of these types of confounding
by showing statistically which variables relate to alternative
pathways (Han et al. 2012) but ultimately its importance is a
matter of judgement. For the present purposes, the main point is
that internal validity should always be considered.
External validity most often arises due to bias in sampling
countries. A few countries, such as the Democratic Republic of
Korea, Iraq, Afghanistan or Somalia, may be excluded because
of absence of data. Widely used databases such as the World
Development Indicators exclude certain small island states,
such as Tuvalu and Kiribati. Many analyses are conducted on
countries from a single continent (typically Africa, and within it
the sub-Saharan countries) with an inference that the results
873
apply worldwide. Yet Africa, while not unique, does have
particular characteristics, such as the timing and magnitude of
the AIDS epidemic, suggesting that such extrapolation should
be undertaken with caution. An analogous situation arises in
medicine when, e.g. clinical trials exclude women, elderly
people or members of ethnic minorities. This can lead either to
the intervention being withheld from those who were not
included in the trials, as with cardiac surgery, with the early
trials excluding women who were subsequently less likely to
receive surgery (Petticrew et al. 1993; Nante et al. 2009) or the
administration of treatment to groups who may not benefit
from it (Matthews 1995). A few studies have attempted to
mitigate such bias by restricting its scope to analysis of small
states (Hansen and Headey 2010) or focusing on islands such
as Fiji (Gounder 2001).
Another limitation to external validity is the inclusion of
states that are irrelevant to the question being asked, such as
when high-income countries are included in studies evaluating
the effects of aid, and weighting of all states equally.
Multiple outcome measures
Aid can impact on countries in different ways, including
economic growth, education, health and growth in infrastructure. Early studies investigated the link between foreign aid and
savings (Papanek 1972). More recent work focuses on effects
on economic growth and foreign investment (Burnside and
Dollar 2000; Lu and Ram 2001; Raghuram and Subramanian
2005). The issue of multiple outcomes is equally common in
medicine, e.g. where psychiatric treatments may seek to
improve scores on specific mental health measures, general
wellbeing, employability or quality of relationships among
others (Tyler et al. 2011). In clinical trials, the appropriate
response is to specify the outcomes in advance by means of
registration of the trial and, ideally, publication of the protocol,
coupled with appropriate statistical techniques to analyse the
data (Yoon et al. 2011). This is not possible in observational
studies of aid effectiveness; therefore, it is essential that the
inclusion (and exclusion) of possible outcome measures are
theoretically justified and their choice is made explicit. One
recent economic paper calls for opening the ‘black box’ of aid
effectiveness to specify the causal chains and mechanisms
involved (Bourguignon and Sundberg 2007).
Time lags
Classic analyses have been cross-sectional, inferring expected
effects over varying periods ranging from the same year to
those of 10–25 years, often with small sample sizes (Bornschier
et al. 1978; Barro 1991; Sachs and Warner 1995). More recent
studies restrict the analysis to 4 years, so determined not by
theory but the validity of statistical models (Clemens et al.
2004), a practice that seems common in recent analyses
(Burnside and Dollar 2000; Collier and Dollar 2002; Clemens
et al. 2004; Raghuram and Subramanian 2005). Other papers
deploy ‘agnostic time series analysis’, using time specifications
that are acknowledged to be ‘largely atheoretical’ (Hansen and
Headey 2010). Yet it is far from clear what the most appropriate
interval is. Furthermore, the relationship may be asymmetrical,
with any benefits of aid taking some time to accrue, e.g.
because of the time taken to build new facilities, create new
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HEALTH POLICY AND PLANNING
institutional structures or train staff, while their withdrawal
may rapidly precipitate a crisis. This is analogous to research on
smoking and health, whereby the adverse effects on heart
disease may accumulate over years, as the components of
tobacco progressively damage the arteries, yet withdrawal of
exposure to smoke, even when it is at relatively low level, e.g.
among those exposed to second-hand smoke in bars, can cause
a rapid fall in heart attacks because of changes to blood clotting
(Sargent et al. 2004). A similar phenomenon is seen with
alcohol and liver disease where, although it may take many
years for cirrhosis to develop, a sudden reduction in supply,
such as that resulting from rationing during the German
occupation of Paris in World War II, may be associated with a
rapid fall in mortality (Ledermann et al. 1964). At present, there
is an insufficient theoretical or empirical basis to determine
what lags are appropriate for studying the effects of aid.
Data limitations
Any analysis is only as good as the data on which it is based.
Unfortunately, the data on which many analyses of the
effectiveness of aid are based are of dubious validity. First,
there is a substantial difference between ‘aid commitments’
(donor promises to give money in the future) and disbursement
(what is actually given). Although development of new databases is under way (Grepin et al. 2012), the majority of
statistical evidence is based on the analysis of aid data from the
OECD Creditor Reporting System (CRS) or Development
Assistance Committee databases, which cover donor aid since
1973 (OECD 2011). Until the mid-2000s, coverage of aid
disbursements was very limited. For example, prior to 2003
the estimated mean of country health aid commitments was
10 times higher than the estimated mean of country health
aid disbursements. Although some discrepancy between disbursements and commitments might occur as a result of
complex politics, the gap never was actually so large. As many
disbursement data are missing or inaccurate, the OECD
recommends using commitment data. Thus, much empirical
research does not actually investigate the effects of aid, but the
effects of ‘aid commitments’. In fact, before 2000, aid disbursements and aid commitments were statistically unrelated
(Figure 1).
Another issue is aid leakage. Aid disbursements do not
correspond to net aid received. It is rarely clear how much of
the aid disbursements actually stay in the country instead of
ending up in the hands of western consultants or being spent
on Western manufactured goods or possibly a different project
than originally intended. A more accurate measure of a
population’s exposure to aid would be the total of aid spent
on specific development interventions minus overhead and
leakage.
One claim often made by aid critics is that aid is volatile, as
governments change their commitments from year to year
(Bulı́ř and Hamann 2008; Hudson and Mosley 2008). A large
literature has arisen trying to estimate the consequences of aid
volatility (Bulı́ř and Hamann 2008; Chauvet and Guillaumont
2008; Hudson and Mosley 2008; Kharas 2008; Arellanoa et al.
2009). Part of the impression that aid is volatile stems from a
misunderstanding of the artificial discrepancy between commitments
and
disbursements,
as
described
earlier.
Unfortunately, few claims about volatility can be substantiated
by the OECD CRS aid data.
Consider a sample spreadsheet of commitment data from the
OECD CRS, as reported by Department for International
Development for the UK (DFID) between 1991 and 1993,
provided in Table A1 (see link). In 1991, the first entry is a
hospital project in Malaysia for US$16 million. In 1992 or 1993,
there is no entry for the project. Is this a sign of whimsical
donors, funding a project then bailing out? This would play into
easy-to-perpetuate stereotypes. Instead, this finding is just an
artefact of entry in the data system. DFID reports commitments
for projects over a multi-year timeline in 1 year only. This is one
of many ‘aid artefacts’, or problems associated with aid that are
not really there, but are simply a product of how the data are
recorded.
This data entry anomaly does not affect the ‘average’ amount
of aid being committed to a country as calculated over long
periods of time, such as decades. But it does mean that
estimates of year-to-year fluctuations are wildly inaccurate. This
limitation invalidates almost every attempt to study the
short-term effects of aid on social or health outcomes using
the OECD CRS data, which include nearly every multi-country
analysis of aid to date.
Statistical power and type-II errors
Measurement errors make it harder to detect an effect of one
variable on another, should a relationship truly exist. While
some critics of aid fail to find a relationship between aid and
outcomes such as improvements in gross domestic product
(Burnside and Dollar 2000; Lu and Ram 2001; Clemens et al.
2004; Raghuram and Subramanian 2005) or foreign direct
investment (Kimura and Todo 2010), they often do not account
for the possibility of large measurement errors in the data. As
Easterly puts it, ‘the data are terrible’ (Easterly and Pfutze
2008). Raghuram and Subramanian (2005) note that ‘If noise
in the data plagues all findings, then strong claims about aid
effectiveness (or equally, on aid ineffectiveness) based on
cross-country evidence are unwarranted’. Such noise in the
data risks a ‘type-II error’, in which there is insufficient
statistical power to identify an effect even if one actually exists.
This lack of statistical power is especially likely if the real effect
size is small, as is likely when looking for macro-effects of aid
on health or development. Nonetheless, numerous studies that
fail to identify a significant effect then conclude that this
means that aid has no effect on growth.
Net effects
Critics of health aid correctly point out that too often top-down
and ‘vertical’ (narrow), development programmes reflect donor
priorities rather than actual health needs. This creates many
disruptions in the system. In the case of health aid it can lead
to some diseases, such as HIV, seeming to be exceptionally
prioritized at the expense of other key health problems, such as
non-communicable diseases (Beaglehole et al. 2011). Yet, one
problem with this argument is the lack of attention to the
nature of aid data. For example, suppose HIV activism has
helped marshal additional aid resources for global health. If
this were the case, it would artificially make resources for some
health conditions appear to drop as a fraction of overall health
875
0
100
Health Aid Commitments
200
300
400
500
AID DEBATES AND EPIDEMIOLOGICAL PERSPECTIVES
0
50
100
Health Aid Disbursements
150
200
Figure 1 Health aid commitments vs disbursements, 1973–2000.
Notes: Source of data, OECD CRS. Aid disbursements and commitments are in USD per capita, adjusted for inflation. Data presented for non-missing
and non-zero disbursement data. Number of country years is 59. Pearson’s R ¼ 0.23, P ¼ 0.07.
aid, even when the real amount of resources going to those
health conditions stayed the same.
Some critics of health aid also mistakenly emphasize prevention and treatment as a zero-sum game. For example, one critic
claims ‘Spending AIDS money on treatment rather than on
prevention makes the AIDS crisis worse, not better’ (Easterly
2006). In fact, in the context of HIV, ‘treatment is prevention’;
under circumstances when anti-retrovirals reduce viral load
among infected persons, the probability of HIV transmission
decreases to the point where it becomes the most potent
preventative intervention in practice, as compared with the
relative observed inefficacy of theoretically conceived preventative measures (Stover et al. 2002; Granich et al. 2009).
Categorizing aid as HIV or not, prevention or treatment,
obscures the complexities of actual implementation.
Policy interpretation
Those who argue that aid has not worked in the past conclude
that aid should be abandoned or significantly curtailed in the
future. We have argued that the first part of this argument is not
justified by the evidence. However, even if it were, the second
part does not necessarily follow. Would outcomes be improved
more by removing aid or by attempting to address its shortcomings? Again, an analogy with medicine is helpful. There have
been many interventions that were at first unsuccessful but, as
experience with their application increased, they became routine
therapy (Woods et al. 1992; Costache et al. 2009).
Some aid critics argue that because redistributive welfare has
limitations and potential negative effects, no redistribution
should occur at all. But if the system that provides food stamps
(vouchers) to the hungry is not ending hunger or is subject to
political manipulation that causes some groups and not others
to receive more stamps, does that mean we should not provide
food stamps at all, and simply cut off all assistance to those
unable to afford food? Would this be a better way to reduce
hunger? Should we not instead seek to determine how to
reduce the dysfunctions in the current system?
The issue is analogous to the classic ‘second-best’ theory
in economics (Lipsey and Lancaster 1956). Getting rid of one
market failure (critics suggest aid is a market distortion) in a
context where there are many market failures could make
outcomes worse. Easterly’s recommendations—experimentation,
evaluation and replication—are needed if the global aid system
is going to be dismantled as much as if it going to be maintained.
Just as ‘shock therapy’ had disastrous consequences (Klein 2007),
so too could a major shock to aid be devastating for aid-dependent
countries.
Counterfactuals
What would happen if aid was removed and a country
abandoned to its own devices. We do have some examples to
draw on, such as Somalia. The potential consequences can
easily be identified, such as mass migration, terrorism and
disease outbreaks. However, the use of such examples is subject
to the same methodological problems as those evaluations of
the effect of increasing aid. On the other hand, it can be argued
that the observable fact that such consequences can occur
justifies invoking the precautionary principle (O’Riordan and
Cameron 1994). One recent example of the lack of a control
group was the Millennium Villages Project. An analysis based
on its effects was withdrawn from the Lancet after a host of
problems resulting from the failure to plan for a counterfactual
rendered the study’s results untenable.
Conclusion
Both aid critics and proponents agree on the need for greater
public scrutiny of aid’s effectiveness, through a process of
experimentation, evaluation and replication. There are now
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HEALTH POLICY AND PLANNING
Table 1 Three views of aid’s role and timeline
View of aid
Description
Aid as permanent
Global social safety net/redistribution (Ooms and Hammond 2009); correct global externalities (e.g. World Bank poverty
strategy reduction papers)
Aid as temporary
‘Big push’ out of poverty traps (e.g. Sachs 2005); cope with short-term effects of crisis and disasters (e.g. international
monetary fund lending; Collier 2009)
Aid as distortion
Distorts markets and causes dependency (e.g. Moyo 2009; Friedman/Hayek)
numerous examples of well-conducted field experiments (Duflo
et al. 2008; Humphreys and Weinstein 2009). How to scale such
approaches to address macro-level issues remains a topic for
future work. In the meantime, many aid critics continue to
commit the same methodological mistakes as those they
attribute to the supporters of aid. They rarely concede that
their evidence is generally based on the wrong variable (aid
commitments) and the use of inappropriate outcome measures
(aggregated macroeconomic variables, such as growth rates) to
make far-reaching claims that cannot be defended with existing
evidence, when measurement errors can be so great as
potentially to prevent the detection of any actual effect, and,
should there be associations, the findings are often biased
towards the null, in the direction of the aid critics’ claims.
Without better evidence it will be extremely difficult to
ascertain where aid is coming from, where it is going and
what effects it has. Rigorous efforts are needed to analyse aid
projects to see whether they redistribute capabilities, such as
money, power and knowledge, equitably and sustainably (see
Table 1 for three main views of aid’s role and timing).
Acknowledgement
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We are grateful to Karen Grepin for contributions to background literature and discussions incorporated into various
drafts of this paper.
Costache V, Chavanon O, St Raymond C et al. 2009.
Dramatic improvement in survival after lung transplantation over
time: a single center experience. Transplantation Proceedings 41:
687–91.
Funding
de Koning JS, Klazinga NS, Koudstaal PJ et al. 2005. The role of
’confounding by indication’ in assessing the effect of quality of
care on disease outcomes in general practice: results of a
case-control study. BMC Health Services Research 5: 10.
None.
Duflo E, Hanna R, Ryan S. 2008. Monitoring Works: Getting Teachers to
Come to Schoool. CEPR Discussion Paper No. DP6682.
Conflict of interest
None declared.
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Rest have Done So Much Ill and So Little Good. Oxford: Oxford
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878
HEALTH POLICY AND PLANNING
Appendix
Table A1 Summary of aid commitments by the UK, reported by DFID to the OECD CRS, 1991–93
Year
USD
commitment
deflated
(millions)
Description
Title
Recipient
1991
16.37
Nucleus Hospitals Grant, AF
Malaysia
1991
0.17
Medical equipment
Turks and Caicos Islands
1991
0.12
Medical clinic
Turks and Caicos Islands
1991
0.92
Health centre complex
Turks and Caicos Islands
1991
0.19
Health, Health services
Tanzania
1991
1.84
Infectious disease control
Bilateral, unspecified
1991
0.04
Health policy and admin. management
Ghana
1991
0.42
Infectious disease control
Bilateral, unspecified
1991
0.62
Nutrition
MALNTRNINFTCHLDMTHR4719
Bilateral, unspecified
1991
0.60
Health/health services
WORLD BANK MISSION
Nigeria
1991
3.78
Rural clinics/dispensaries
PRIMARY HEALTH CARE PROJECT
Namibia
1991
1.71
Doctors training
CLINICAL TRNG NDOLA/KITWE
Zambia
1991
0.74
Nurses/paramedics training
PAEDIATRC CARE KABWE HOSP
Zambia
1991
0.63
Nurses/paramedics training
MNTL HLTH/PSYCH TRG CHNMA
Zambia
1991
6.84
Health/health services
HEALTH MGT STRENGTHENING
Zimbabwe
1991
3.40
Human disease control
AIDS PROGRAMME AIDS ACTION PLAN
Uganda
1991
3.72
Doctors training
MED.TRNG.SCHL.OF.MED-UNZA
Zambia
1991
0.30
Rural clinics/dispensaries
FAMILY HEALTH PROJECT
Tanzania
1991
0.38
Health/health services
MALARIA CONTROL PROGRAMME
Namibia
1992
19.40
Health education
ANDHRA PRADESH SCH HLTH PR
India
1992
0.70
Health policy and admin. management
Tanzania
1992
2.12
Health policy and admin. management
Tanzania
1992
0.63
Health policy and admin. management
Bilateral, unspecified
1992
1.16
Basic health infrastructure
Solomon Islands
1992
24.97
Health policy and admin. management
Pakistan
1992
5.80
Human disease control
AIDS: WEST BENGAL
India
1992
0.69
Health education
INTEGRATED CHILD SURVIVAL URBAN
DHAKA JFS 476
Bangladesh
1992
0.56
Health policy and admin. management
1992
1.24
Health policy and admin. management
1992
1.02
Human disease control
MALARIA CONTROL AND RESEARCH
Zimbabwe
1992
0.44
Nurses/paramedics’ training
OPHTHALMIC TRAINING PROGRAMME
IN ZANZIBAR
Tanzania
1992
1.45
Health policy and admin. management
1992
0.87
Rural clinics/dispensaries
ESSAU HEALTH CEN.UPGD.
Gambia
Congo, Dem. Rep.
America, regional
South of Sahara, regional
1992
0.90
Hospitals
REHAB ROYAL VIC HOSPITAL
Gambia
1992
2.69
Health/health services
MNGT.STRENGTH.PROJ MANAGEMENT
STRENGTHENING PROJ.
Gambia
1992
2.90
Human disease control
WHO MED TERM NAT AIDS PLN
Kenya
1992
0.62
Medical personnel salaries
POPN PROGRAMME OFFICER
Kenya
1992
0.19
Human disease control
ACQ.INMUNE DEFIC. SYNDROM THE
PREVENTION OF AIDS
Lesotho
1992
1.32
Health/health services
SEC POP HEALTH/NUTRITION
Lesotho
1992
0.01
Human disease control
AIDS
Malawi
(continued)
AID DEBATES AND EPIDEMIOLOGICAL PERSPECTIVES
879
Table A1 Continued
Year
USD
commitment
deflated
(millions)
Description
Title
Recipient
1992
0.56
Health/health services
LINK-HSMC-CIESS
Mexico
1992
1.59
Rural hospitals
ISIOLO IMMEDIATE SUPPORT
Kenya
1992
0.67
Hospitals
METHODIST CHURCH O’SEAS
Sierra Leone
1992
2.90
Human disease control
AIDS
Zambia
1992
1.28
Health/health services
HEALTH OF COAL MINERS
India
1992
5.57
Hospitals
EASTERN REGIONAL HOSPITAL DHARAN,
NEPAL
Nepal
1992
21.30
Rural clinics/dispensaries
SAVE THE CHILDREN FUND PHASE II
Sri Lanka
1992
3.03
Human disease control
WP APPROP HLTH TECHNOLOGY
Bilateral, unspecified
1992
4.00
Health/health services
WORK PROG URBAN HEALTH
Bilateral, unspecified
1992
3.59
Human disease control
WP TROP DISEASE CONTROL
Bilateral, unspecified
1992
3.20
Human disease control
WORK PROGRAMME AIDS
Bilateral, unspecified
1992
3.15
Health/health services
WORK PROG ENVIRON HEALTH
Bilateral, unspecified
1992
1.27
Health/health services
WORK PROG AGEING
Bilateral, unspecified
1992
5.31
Health/health services
WP HLTH ECON/FINANCING
Bilateral, unspecified
1992
1.97
Nutrition
EARLY MORT/VIT A SUPPL
Bilateral, unspecified
1992
0.40
Rural clinics/dispensaries
PRIM HLTH CARE FAC AFRICA
Bilateral, unspecified
1992
1.26
Nutrition
INFANT MORBIDITY/VIT A
Bilateral, unspecified
1992
2.06
Doctors training
FIJI SCHOOL OF MED SUPPORT
Fiji
1992
0.36
Rural clinics/dispensaries
COMMUNITY BASED PHC PROGRAMME MEHAL MEDA
Ethiopia
1992
0.84
Rural clinics/dispensaries
KIBWEZI RURAL HEALTH
Kenya
1992
1.46
Human disease control
COMMUNITY BASED HEALTH CARE INC.
HYDATID CONTROL
Kenya
1992
1.45
Health/health services
HEALTH FACILITIES JFS420
Kenya
1992
0.87
Health education
FRENCH EDITION OF DIALOGUE ON
DIARRHOEA
Senegal
1992
1.00
Health/health services
INTEGRATED HEALTH PROJECT
Sierra Leone
1992
11.70
Human disease control
MEDIUM TERM AIDS PLAN
Tanzania
1992
0.97
Health education
CENTRE FOR EDUCATIONAL
DEVELOPMENT IN HEALTH
Tanzania
1992
1.13
Health/health services
MULAGO HOSPITAL ORTHOPAEDIC
PROJECT
Uganda
1992
1.70
Health/health services
OPHTHALMIC CLINICAL OFFICERS
TRAINING PROGRAMME
Uganda
1992
0.58
Rural clinics/dispensaries
PRIMARY HEALTH CARE
Bolivia
1992
2.09
Rural clinics/dispensaries
PRIMARY HEALTH CARE WITH INDIAN
COMMUNITIES
Brazil
NUTRITION PROGRAMME
1992
0.31
Nutrition
1992
0.84
Health policy and admin. management
Peru
Dominica
1992
0.70
Medical services
Bangladesh
1992
0.86
Health policy and admin. management
1992
0.63
Health/health services
HEALTH AND COMMUNITY DEVELOPMENT India
1992
0.53
Health education
TRAINING FOR WOMEN DEVELOPMENT
WORKERS
Pakistan
1992
1.96
Rural clinics/dispensaries
HEALTH RESOURCES AND INFORMATION
NETWORK
Middle East, regional
1992
0.82
Clinics/dispensaries
ALEXANDRA TOWNSHIP CLINIC (JFS515)
South Africa
1992
0.46
Health/health services
HEALTH SERVICES PLANNING
Chile
Cambodia
(continued)
880
HEALTH POLICY AND PLANNING
Table A1 Continued
Year
USD
commitment
deflated
(millions)
Description
Title
Recipient
1992
0.87
Health/health services
SUPPORT IN HEALTH AND POP
Uganda
1992
0.33
Health/health services
TERMINAL CARE CNTR JFS301
Kenya
1992
1.39
Nurses/paramedics training
EXPANDED NURSE-MIDWIFE TRAINING
PROJECT JFS495
Malawi
1992
1.37
Health/health services
COMMUNITY BASED REHABILITATION
PROGRAMME (JFS 522)
Uganda
1992
1.36
Health/health services
LIMB PROJECT JFS 459
Cambodia
1992
0.30
Health/health services
ORTHOPAEDIC WORKSHOP: BANGALORE
India
1992
0.59
Health/health services
DEV AND TRAINING GROUPS OF PEOPLE
WITH DISIBILITY
India
1992
0.48
Human disease control
COMMUNITY HEALTH EDUCATION JFS 555 Nepal
1992
0.59
Human disease control
CRUSH KENYA AIDS PROJECT JFS 533
Kenya
1992
0.40
Health/health services
TO IMPROVE THE HEALTH OF MEN/
PARTNERS NIGERIAN ARMY
Bilateral, unspecified
1992
0.70
Health/health services
DEVELOPING COUNTRIES: RESPONDING
TO ECONOMIC BURDEN
Bilateral, unspecified
1992
0.47
Human disease control
VISCERAL LEISHMANIASIS.
ASYMPTOMATIC CARRIERS
Bilateral, unspecified
1992
0.38
Health/health services
SUPPORT TO FIJI DISABLED PEOPLES
ASSOCIATION
Fiji
1992
0.62
Medical research
PARASITIC NEMATODES
Bilateral, unspecified
1992
0.48
Nurses/paramedics training
MIDWIFERY TRAINING
Bangladesh
1992
2.32
Health/health services
URBAN COMMUN. BASED REHAB
India
1992
1.43
Human disease control
BLINDNESS PROGRAMME
India
1992
1.48
Medical research
HAEMOGLOBINOPATHY CONTROL
India
1992
2.17
Human disease control
VIRAL HEPATITIS
India
1992
1.23
Human disease control
CANCER, MEHDI NAWAZ JUNG
India
1992
1.41
Medical research
CERVICAL CANCER
India
1992
26.10
Rural clinics/dispensaries
AP SCHOOL HEALTH PROG
India
1992
0.39
Medical research
ROTAVIRUS INFECTION
India
1992
0.84
Rural clinics/dispensaries
PRIMARY HEALTH CARE, YEMEN (JFS 574) Yemen
1992
26.55
Health/health services
POPULATION WELFARE PROJECT PHASE III Pakistan
1992
0.85
Human disease control
AIDS INITIATIVE
1992
0.68
Human disease control
STRATEGIES FOR HOPE SECOND PHASE
Bilateral, unspecified
1992
1.16
Health/health services
DEV PROG DISABLED PEOPLE JFS 211
Uganda
1992
2.91
Human disease control
TASO JFS (192)
Uganda
1992
1.21
Rural clinics/dispensaries
PHC, DAICHOPAN, AFGHANISTAN
Afghanistan
South of Sahara, regional
1992
1.45
Health education
OPHTHALMIC PROGRAMME
Mozambique
1992
0.32
Human disease control
PROTOZOAN CYSTS
Bilateral, unspecified
1992
0.37
Rural clinics/dispensaries
NGOS AND PRIM HLTH CARE
Bilateral, unspecified
1992
0.57
Nutrition
LEAF SUPPLEMENT SRI LANKA
Bilateral, unspecified
1992
0.44
Health/health services
FEMALE FACTORY WORKERS, THAILAND
R4859
Bilateral, unspecified
1992
0.51
Health/health services
YANOMAMI HEALTH PROJECT
Brazil
1992
0.43
Health/health services
SECTOR AID MISSION
Ghana
1992
0.29
Health/health services
INDUCED ABORTION R4860
Bilateral, unspecified
1992
4.33
Rural clinics/dispensaries
PRIMARY HEALTH CARE
Bilateral, unspecified
1992
3.07
Health/health services
EPIDEMIOLOGY PROGRAMME
Bilateral, unspecified
(continued)
AID DEBATES AND EPIDEMIOLOGICAL PERSPECTIVES
881
Table A1 Continued
Year
USD
commitment
deflated
(millions)
Description
Title
Recipient
Bilateral, unspecified
1992
2.67
Health/health services
HEALTH IMPACT DEV.
1992
1.64
Medical laboratories
LABORATORY SERVICES
Bilateral, unspecified
1992
2.10
Nurses/paramedics training
AKSON BSC NURSING PROGRAM
Pakistan
1992
0.38
Medical/veterinary services
SCHOOL HEALTH SUPERVISOR
Yemen
1992
0.64
Health/health services
STREET CHILDREN DRUG ABUSE
Peru
1992
0.93
Doctors training
ASS-FAC OF MEDICINE
Ethiopia
1992
2.90
Health/health services
HEALTH AND FAMILY WELFARE
India
1992
3.77
Medical research
MEDICAL RESEARCH PROG.
Bilateral, unspecified
1992
5.74
Rural clinics/dispensaries
PROVISION OF HEALTH CARE SUPPORT
Solomon Islands
1992
7.86
Health/health services
SOUTHERN REG HEALTH PROJ
Tanzania
1992
0.49
Human disease control
CONDOM SOCIAL MARKETING AND
FAMILY PLANNING
Ethiopia
1992
0.86
Health/health services
COMMUNITY HEALTH FOR CAMPESINO’S
Nicaragua
1992
2.62
Health/health services
VOLTA DHMS PROJECT
Ghana
1992
0.87
Health/health services
HEALTH AND POP. FIELD MAN
Nigeria
1992
1.09
Rural clinics/dispensaries
PRIMARY HEALTH
Bolivia
1992
12.78
Nurses/paramedics training
FOURTH POPULATION AND HEALTH:
STRENGTHENING NURSING EDCTION
Bangladesh
1992
7.90
Health/health services
FOURTH POPULATION AND HEALTH:
MEDICAL EDUCATION/COLLEGES
Bangladesh
1992
3.71
Health/health services
FOURTH POPULATION AND HEALTH:
MANAGEMENT DEVELOPMENT UNIT
Bangladesh
1992
0.84
Human disease control
FOURTH POPULATION AND HEALTH:
CONTROL OF IODINE DEFICIENCY
Bangladesh
1992
0.72
Health/health services
FOURTH POPULATION AND HEALTH:
HUMAN RESOURCE DEVELOPMENT
Bangladesh
1992
8.24
Health/health services
HLTH ECON.UNIT-USE OF ECON. AND FIN. Bangladesh
ANALYSIS IN H&P SECT.(PEC)
1992
0.66
Doctors training
MOI UNIV PROF OF MEDICINE
Kenya
1992
2.28
Health/health services
SPASTICS SOCIETY N.INDIA
India
1992
0.76
Rural clinics/dispensaries
AMREF COMMUNITY BASED HLTH CARE
SUPPT UNIT
Kenya
1992
3.28
Medical/veterinary services
CANCER RESEARCH, GUJARAT
India
1992
1.45
Doctors training
MEDICAL EDUCATION TECH
India
1992
0.58
Health/health services
CBR NEWS PUBLISHING (624)
Bilateral, unspecified
1992
0.62
Medical laboratories
BLOOD TRANSFUSION
India
1992
1.45
Clinics/dispensaries
GHANA NATIONAL EYE CARE PROG JFS
609
Ghana
1992
1.75
Health/health services
UNIV WEST INDIES/WALES HEALTH
PROMOTION LINK
West Indies Unallocated
1992
0.43
Health/health services
SUPPURATIVE OTITIS MEDIA
Bilateral, unspecified
1992
3.16
Health/health services
UK HEALTH AUTHORITY LINK
St. Helena
1992
8.82
Health/health services
ADB 3RD HEALTH PROJECT
Pakistan
1992
2.61
Rural clinics/dispensaries
RURAL HEALTH FACILITIES
Solomon Islands
1992
1.67
Health/health services
MEDCL AID FR PALESTINIANS
Bilateral, unspecified
1992
0.43
Health/health services
Y CARE INTERNATIONAL
Bilateral, unspecified
1992
1.10
Health/health services
MANAGEMENT FOR HEALTH
Cambodia
1992
1.67
Nutrition
INCAPTRG.NUTRITION SCIENCE TO
STRENGTHEN INCAP’S CAPACITY
America, regional
(continued)
882
HEALTH POLICY AND PLANNING
Table A1 Continued
Year
USD
commitment
deflated
(millions)
Description
Title
Recipient
1992
1.45
Health/health services
HEALTH SERVICES
Anguilla
1992
0.41
Health/health services
LILONGWE SCH HEALTH SCIEN
Malawi
1992
0.67
Human disease control
ONCHOCERCIASIS RSRCH AND CNT
Malawi
1992
1.88
Doctors training
MED.COLL-INSTT’NL.DEV.PRJ
Malawi
1992
0.87
Human disease control
AIDS PHASE II
Kenya
1992
0.43
Medical personnel salaries
SECONDMENT TO THE INDEPENDENT
COMMISSION -MR.C.ALLISON
Bilateral, unspecified
1992
1.78
Health/health services
CCMRC: HYPERTENSION AND DIABETES IN Bilateral, unspecified
THE COMM. CARIBB
1992
0.57
Health/health services
INDUCED ABORTION
Bilateral, unspecified
1992
1.09
Health/health services
ASSIST. TO MIN. OF HEALTH
Uganda
1992
1.82
Medical laboratories
COMMUNITY OPHTHALMOLOGY NATIONAL India
BLINDNESS PROGRAMME
1992
0.59
Health/health services
A NEW VENTILATOR SYSTEM
Bilateral, unspecified
1992
2.28
Doctors training
POST-GRADUATE MEDICAL
TRAININGPROJECT
Seychelles
1992
5.76
Health/health services
MULAGO HOSPITAL SUPPORT
Uganda
1992
0.52
Medical research
PELVIC INFLAMMATORY (PID) IN SLUM
WOMEN, BOMBAY
Bilateral, unspecified
1992
2.90
Human disease control
MED TRM PLAN: AIDS CONTROL CONTROL Zimbabwe
1992
1.50
Nurses/paramedics training
ASS. WITH NURSE TRAINING HILLINGDON Pakistan
HEALTH AUTHORITY
1992
2.04
Medical/veterinary services
COLL, COMMTY MED, LAHORE SOUTH
BANK POLY LINK
1992
0.86
Medical research
NEW TOOLS TO ASSESS CAUSES OF ADULT Bilateral, unspecified
ILLNESS
1992
58.00
Health/health services
FAMILY WELFARE ORISSA
India
1992
4.20
Health/health services
PRIMARY HEALTH CARE
South Africa
1992
0.43
Health/health services
HEALTH SUPPORT PROGRAMME
Brazil
1993
2.33
Clinics/dispensaries
1993
2.82
Pharmaceutical system, drugs
COMMODITY AID GRANT 1993
Cambodia
1993
14.39
Medical supplies
EQUIPMENT INSTALLATION
Ghana
1993
0.46
Medical services
1993
0.79
Rural clinics/dispensaries
1993
1.26
Infectious disease control
1993
3.50
1993
Pakistan
Ghana
Zimbabwe
PRIMARY HEALTH CARE
Cambodia
Rural clinics/dispensaries
EASTERN REG PRIM HLTH PH2
Nepal
0.56
Health/health services
HEALTH SECTOR REFORM GENERAL
MANAGER ANGUILLA H/A
Anguilla
1993
3.69
Basic nutrition
South Africa
1993
1.09
Health policy and admin. management
Bilateral, unspecified
1993
2.38
Health policy and admin. management
Jamaica
1993
0.32
Basic nutrition
1993
0.34
Health/health services
UNICEF/ODA JOINT PROG.
1993
3.57
Rural clinics/dispensaries
AK PRIMARY HEALTH CARE
Pakistan
1993
3.83
Rural clinics/dispensaries
WORLD BANK FAMILY HEALTH
Pakistan
1993
1.11
Health/health services
MALARIA CONTROL PROJECT
Namibia
1993
0.85
Rural clinics/dispensaries
PHC SUPPORT FACILITY
Solomon Islands
1993
18.45
Rural clinics/dispensaries
FAMILY HEALTH PROJECT
Uganda
Bilateral, unspecified
Bilateral, unspecified
Bilateral, unspecified
(continued)
AID DEBATES AND EPIDEMIOLOGICAL PERSPECTIVES
Table A1 Continued
Year
USD
commitment
deflated
(millions)
Description
Title
Recipient
1993
1.27
Human disease control
INT.CNTRE.DIARRHOEAL DISEASE
RES.DEM.SURV.SYST.COORDINATOR
Bilateral, unspecified
1993
5.07
Medical research
CONCORDAT BETWEEN ODA AND MRC
Bilateral, unspecified
1993
0.93
Rural clinics/dispensaries
RURAL PHC PHASE II
Vanuatu
1993
0.85
Human disease control
CARE NIGER AIDS AND MIGRATION
PILOT PROJECT
Niger
1993
0.42
Medical personnel salaries
CHRIS ALLISON
Bilateral, unspecified
1993
0.52
Health/health services
HEALTH FINANCING
Kyrgyz Republic
1993
0.58
Medical/veterinary services
OPHTHALMIC SERVICES (844)
Cambodia
1993
0.37
Rural clinics/dispensaries
PRIMARY HEALTH CARE PROGRAMME
Cambodia
1993
0.43
Rural clinics/dispensaries
TRAINING IN PRIMARY HEALTH
CARE-JAMKHED
India
1993
0.71
Rural clinics/dispensaries
INTEGRATED HEALTH CARE JFS815
Laos
1993
0.81
Human disease control
AIDS/STDS SERVICE AGREEMENT
Bilateral, unspecified
1993
0.40
Rural clinics/dispensaries
RURAL DEVELOPMENT LAOS JFS 765
Laos
1993
1.14
Human disease control
AIDS EDUCATION JFS819
Kenya
1993
0.78
Medical/veterinary services
ANAESTHETIC TRAINING
Malawi
1993
1.01
Medical personnel salaries
TCO HEALTH AND POPULATION FIELD
MANAGER
Zimbabwe
1993
0.53
Medical/veterinary services
RATTANAK MONDOL RURAL HEALTH
PROJECT 766 CAMBODIA
Cambodia
1993
16.31
Health/health services
HEALTH SECTOR AID
Ghana
1993
0.34
Clinics/dispensaries
RURAL HEALTH FACILITIES RENNELL AND Solomon Islands
BELLONA
1993
0.70
Health/health services
PROSTHETICS CLINIC (830)
Cambodia
1993
1.79
Health/health services
ASSISTANCE TO HEALTH POLICY UNIT
South Africa
1993
2.02
Health/health services
HEALTH SERVICE MANAGEMENT
TRAINING
South Africa
1993
0.70
Medical personnel salaries
TCO HEALTH AND POP OFFICER
India
1993
0.68
Infectious disease control
Bilateral, unspecified
1993
0.42
Health policy and admin. management
Uganda
1993
0.31
Hospitals
NAIROBI HOSPICE
Kenya
1993
0.16
Health/health services
BAMAKO OPERATIONS RESEARCH
Bilateral, unspecified
1993
0.43
Human disease control
IVERMECTIN COMMUNITY TREATMENT:
ONCHOCERCIASIS SIERRA LEONE
Bilateral, unspecified
1993
0.56
Human disease control
COLLABORATIVE STUDY EFFECTIVE OF
HIV/AIDS IN DEV COUNTRIES
Bilateral, unspecified
883