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The financial cost of doctors emigrating from
sub-Saharan Africa: human capital analysis
OPEN ACCESS
Edward J Mills chair of global health 1 2, Steve Kanters statistician 1 2, Amy Hagopian assistant
professor of global health3, Nick Bansback health economist4, Jean Nachega professor of medicine,
and director 5, Mark Alberton research associate 1, Christopher G Au-Yeung research assistant 6,
Andy Mtambo research scientist 6, Ivy L Bourgeault professor 1, Samuel Luboga deputy dean,
education 7, Robert S Hogg professor of health sciences 6 8, Nathan Ford research associate 9
1Faculty of Health Sciences, University of Ottawa, Ottawa, Canada K1N6X1; 2Centre for Evaluation and Clinical Epidemiology, Vancouver, Canada;
3Department of Global Health, School of Public Health, University of Washington, Seattle, USA; 4School of Population and Public Health, University
of British Columbia, Vancouver, Canada; 5Centre for Infectious Diseases, Faculty of Health Sciences, University of Stellenbosch, Cape Town, South
Africa; 6British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada; 7Office of the Dean, School of Medicine, Makerere University,
Kampala, Uganda; 8Faculty of Health Sciences, Simon Fraser University, Burnaby, Canada; 9Centre for Infectious Disease Epidemiology and
Research, University of Cape Town, South Africa
Abstract
Objective To estimate the lost investment of domestically educated
doctors migrating from sub-Saharan African countries to Australia,
Canada, the United Kingdom, and the United States.
Design Human capital cost analysis using publicly accessible data.
Settings Sub-Saharan African countries.
Participants Nine sub-Saharan African countries with an HIV prevalence
of 5% or greater or with more than one million people with HIV/AIDS
and with at least one medical school (Ethiopia, Kenya, Malawi, Nigeria,
South Africa, Tanzania, Uganda, Zambia, and Zimbabwe), and data
available on the number of doctors practising in destination countries.
Main outcome measures The financial cost of educating a doctor
(through primary, secondary, and medical school), assuming that
migration occurred after graduation, using current country specific interest
rates for savings converted to US dollars; cost according to the number
of source country doctors currently working in the destination countries;
and savings to destination countries of receiving trained doctors.
Results In the nine source countries the estimated government
subsidised cost of a doctor’s education ranged from $21 000 (£13 000;
€15 000) in Uganda to $58 700 in South Africa. The overall estimated
loss of returns from investment for all doctors currently working in the
destination countries was $2.17bn (95% confidence interval 2.13bn to
2.21bn), with costs for each country ranging from $2.16m (1.55m to
2.78m) for Malawi to $1.41bn (1.38bn to 1.44bn) for South Africa. The
ratio of the estimated compounded lost investment over gross domestic
product showed that Zimbabwe and South Africa had the largest losses.
The benefit to destination countries of recruiting trained doctors was
largest for the United Kingdom ($2.7bn) and United States ($846m).
Conclusions Among sub-Saharan African countries most affected by
HIV/AIDS, lost investment from the emigration of doctors is considerable.
Destination countries should consider investing in measurable training
for source countries and strengthening of their health systems.
Introduction
The migration of health workers from developing countries to
developed ones is a well recognised contributor to weak health
systems in low income countries and is considered a primary
threat to achieving the health related millennium development
goals.1In 2010 the World Health Assembly unanimously
adopted the first code of practice on the international recruitment
of health personnel, which recognises problems related to the
global shortage of health staff and calls for all countries to
mitigate the negative effects from the migration of health
workers. The code also calls on wealthy countries to provide
financial assistance to source countries affected by the losses
of health workers.2
The code is particularly important for sub-Saharan Africa where,
according to the World Health Organization, the majority of
countries are experiencing a critical shortage of doctors, nurses,
and midwives.3Many doctors from these countries have left to
pursue better career opportunities in developed countries.4-12
The problem is exacerbated by the continent bearing the greatest
burden of diseases such as HIV/AIDS.13 While Africa
experiences 24% of the global burden of disease, it has only 2%
Correspondence to: E J Mills Edward.mills@uottawa.ca
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Research
RESEARCH
of the global supply of doctors, and less than 1% of expenditures
are on global health.1 14 Countries with a high prevalence of HIV
are particularly affected by shortages of health workers for
several reasons. Firstly, HIV has been documented as a leading
cause of death among health workers—in the first five years of
the AIDS epidemic, for example, an estimated 1 in 10 health
workers in Malawi died of AIDS.15 Secondly, HIV leads to
health workers’ absenteeism owing to illness among staff or
their relatives.16 Finally, the increased workload resulting from
HIV/AIDS illness has not been met by a commensurate increase
in staff, leading to increased burnout and fatigue.17
The shortage of doctors in most African countries is attributed
to institutes lacking the capacity to train sufficient numbers of
doctors, coupled with an inability to retain doctors, who choose
to emigrate for what they consider better career
opportunities.18 19 20 Many wealthy destination countries, which
also train fewer doctors than are required,21 depend on immigrant
doctors to make up the shortfall. In this way developing
countries are effectively paying to train staff who then support
the health services of developed countries. Although developed
countries often provide development assistance to resource
limited countries, the amount that goes into the training of health
workers is variable and limited.22
Although the code of practice is voluntary, specific
recommendations are to report data on the migration of health
staff and to establish research programmes on migration.2The
ability of wealthy countries to produce such data is mixed as
non-licensed health workers are often not counted. We estimated
the monetary losses incurred by sub-Saharan African countries
secondary to the migration of doctors licensed to practise in
Australia, Canada, the United Kingdom, and the United States.
These four destination countries were chosen because for more
than 50 years they have benefited from the mass immigration
of doctors.4In the setting of HIV epidemics and related health
problems, the loss of these vital members of society undermines
both health and social stability in African communities.
Quantifying economic losses may help motivate and encourage
policy makers to improve working conditions and incentive
programmes to retain doctors in the countries where they were
trained, and to support improvements in the infrastructure of
medical training in sub-Saharan Africa.
Methods
We included data on doctors practising in Australia, Canada,
the United Kingdom, and the United States who had received
their medical education in a selected African country. As the
concern about loss of doctors is related to the burden of disease
in the countries left, we selected African states according to
HIV rates, as determined by WHO, and included those that had
an HIV prevalence of 5% or greater or more than one million
residents with HIV/AIDS. We excluded countries with no
medical schools or those with medical schools too new to have
generated doctors.
Data sources
We accessed publicly available data.23 To estimate data on
primary and secondary school spending we used Unesco data
from two published reports on public expenditure for students
in primary and secondary schools as a percentage of gross
domestic product per capita.24 Data on gross domestic product
were obtained from the United Nations and included the gross
domestic product and gross domestic product per capita in
current US dollars.24
The number of medical schools and contact information were
identified through the Institute for International Medical
Education website (a comprehensive database of international
medical schools) and the sub-Saharan Africa Medical Schools
Study.19 25 For each country we obtained the costs of medical
schools up to July 2011 through information posted on the
medical school or university website. In the absence of available
data for the largest medical university in a given country, we
chose the largest with available data. University costs were
gathered from the Addis Ababa University (Ethiopia), University
of Nairobi (Kenya), University of Malawi (Malawi), Igbinedion
University Okada (Nigeria), University of Stellenbosch (South
Africa), Makerere University (Uganda), Hubert Kairuli
Memorial University (Tanzania), University of Zambia
(Zambia), and the University of Zimbabwe (Zimbabwe). When
medical school costs subsidised by government were not
available from our contacts for public universities, we used the
costs from large not for profit private medical schools.
We obtained statistics on HIV prevalence (percentage in those
aged 15-49) from the UNAIDS 2008 report on the global AIDS
epidemic and the 2009 AIDS epidemic update.13 Data on the
density of doctors was obtained from the WHO Global Health
Observatory.26 Currency conversion was done through the XE
universal converter website in July 2011.27 We derived data on
the number of African trained doctors currently practising in
the destination countries through communication with
respondents at the Australian Medical Association (Masterfile),
the Canadian Medical Association (Masterfile), the American
Medical Association (Masterfile), and the UK General Medical
Council (through an access to information request). All data
were accurate up to September 2010.
We took the average age of retirement for doctors in the
destination countries from various sources, including direct
contact with the medical councils of the destination countries.28-31
The age distribution of active doctors for Australia, Canada, the
United Kingdom, and the United States was taken from,
respectively, the Australian Institute of Health and Welfare, the
Canadian Medical Association, the British Medical Association
and General Medical Council, and the American Medical
Association, respectively.27 32-34
We obtained the most recent interest rates on savings for each
African country from the websites of their respective major
national banks. Given the economic instability of Zimbabwe,
we derived a conservative inflation rate from neighbouring
countries. The average cost of medical education was obtained
from the medical association of each destination country.
Statistical analysis
Education costs
Medical schools in sub-Saharan African countries tend to admit
students directly from secondary (high) school into university
programmes that last for five or six years. Typically, the first
two years focus on the basic sciences and the remaining three
on clinical medicine. Recently, some schools have begun to
adapt their curriculums around health problems of national
priority.19 Postgraduate specialty training varies widely from
location to location, sometimes in the form of programmes at
masters level.35 36
We estimated the total costs of government subsidised education
through primary, secondary, and tertiary school. Because of
inconsistencies in estimating these across countries and because
several countries lack enough capacity for most doctors to obtain
advanced training, we took the conservative course of not
including costs for postgraduate education and training.
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RESEARCH
To calculate the government cost of primary and secondary
schooling within each country, we first calculated the cost for
each year within each country. The costs for each school year,
for primary and secondary school, were obtained by multiplying
the gross domestic product per capita by the public expenditure
for each pupil as a percentage of gross domestic product per
capita:
public expenditure per student (primary or secondary)=gross
domestic product (current $ per capita)×(public expenditure per
student, as % of gross domestic product per capita)/100)
Finally, we calculated the total cost of primary and secondary
school by multiplying the respective cost per year by the number
of years spent at each school level. The number of years spent
at each school level differs between countries. For example,
Kenyan children spend eight years at primary school and four
at high school, whereas Ugandan children spend seven and eight
years, respectively. We accounted for this in the estimation
process.
Medical school costs
Medical school costs were obtained in local currency and then
converted to US dollars. We calculated the cost per year of
medical education and accommodation, incorporating the
differing years of programmes between states. We identified
the costs for private tuition and calculated the state subsidised
amounts. After calculating the costs of medical education to the
governments in each of the nine countries, we calculated the
average number of working years for doctors in each destination
country, the average age at emigration for each source country,
and the fixed deposit interest rate in each country.
Average working years for doctors
The average age that family and general practitioners retire is
63 years in Australia and the United Kingdom, 62 in Canada,
and 64 in the United States. We applied these retirement ages
to the African international medical graduates who emigrated
to these countries. We conservatively set the age of migration
at age 30.37 Therefore an African international medical graduate
would work a maximum of 33 years in Australia and the United
Kingdom, 32 in Canada, and 34 in the United States. Thus by
using data on the age distribution of doctors by age category
(<35, 35-44, 45-54, 55-64, ≥65, unknown age) for Australia,
Canada, the United Kingdom, and the United States, we
determined the average number of working years for each age
group of African international medical graduates currently
practising in the four destination countries. To calculate the
value for the unknown age category, we averaged the number
of working years from the age groups. We carried out a
sensitivity analysis that assumed workers had remained working
in their source country for a further 7.2 years.38
Lost returns on investment
To calculate the lost returns on investment for source countries
when a doctor emigrates, we multiplied the total cost of
educating a doctor by a compounding factor.39 40 In algebraic
terms, the lost return from a government’s investment in the
education of a doctor who eventually emigrates to a destination
country would be:
LR=EC(1+r)t
where LR is the lost return on investment, EC is the cost of a
doctor’s education, and (1+r)tis the annual compound factor
for interest. Within the compounding factor, r is the interest rate
for a fixed savings deposit and t is the time from start of
investment. The formula gives the future value of the investment
lost in t years after educating a doctor—assuming the interest
is compounded on a yearly basis. The time from start of
investment is the average work life of the doctor, calculated as
the difference between average retirement age (62-64) in each
destination country and the average age at emigration from each
of the nine source countries. For each African country we
calculated the lost return on investment for one emigrant doctor
for each age category in each destination country. In turn, using
the appropriate age distributions as well as the number of doctors
working in the destination countries, we multiplied these costs
by the estimated number of doctors in each category and
summed, yielding the lost returns on investment.
Calculating number of international medical
graduates in the destination countries
We calculated confidence intervals for the number of African
educated doctors working in destination countries by multiplying
the confidence intervals for the proportion of such doctors. The
estimated proportion was obtained by dividing the reported
number of doctors who emigrated to the destination countries
by the total number of doctors in each sub-Saharan African
country. The confidence intervals were then calculated using Z
intervals for proportions. Using the upper and lower bounds of
these confidence intervals we repeated the calculations for the
lost returns on investment.
Sensitivity analysis
A sensitivity analysis was carried out in two steps by considering
factors that reduce the estimated loss in investment, a best
scenario, and its counterpart, the worst scenario. We obtained
the best scenario estimate by reducing the years over which the
principal is compounded, by reducing the public’s cost in the
case when students go to private schools and reducing medical
school costs by removing non-tuition fees. The mean time from
end of school to emigration is conservatively estimated as 7.2
years.38 We used a weighted average to account for the various
ages of the doctors working abroad. Rather than use the midpoint
of each age category to calculate the amount of time over which
to compound, we used the extremity of the intervals to minimise
the compounding time. Only Nigeria and Tanzania have private
medical schools, so the number of doctors in these countries
was reduced by the percentage of private medical schools. For
the remaining countries, the cost of primary and secondary
schools was reduced by the percentage of students attending
private schools as reported by Unesco. The worst scenario
compounds costs over the full length of a doctor’s career using
the deposit rate for each country (see web extra of data for our
analyses).
Results
Full data were available for nine of 17 countries with prevalence
thresholds for HIV/AIDS above 5% or with more than one
million patients. Figure 1⇓shows the flow of countries through
the study.
Table 1⇓displays important health indicators and statistics for
the medical schools in the African source countries. South
Africa, Nigeria, and Kenya had the largest number of people
with HIV. South Africa had the highest density of doctors (8
per 10 000 population), whereas Nigeria had the largest number
of medical schools (n=21).
Using country specific statistics on gross domestic products,
the public expenditure on primary and secondary education for
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RESEARCH
each student for primary schools ranged from $490.0
(Zimbabwe) to $8448.5 (South Africa) and for secondary
schools ranged from $336.2 (Ethiopia) to $9866.9 (South Africa,
table 2⇓).
Table 3⇓shows the estimated government subsidised tuition
costs for a doctor’s education in the nine source countries.
Medical school costs for each student were highest in South
Africa ($40 383), which also had the highest total education
cost for each medical student ($58 698). At the other end of the
spectrum, Uganda had the lowest medical school costs ($18
870).
Table 4⇓shows the estimated compounded lost investment for
each country, calculated using data on age distribution and
number of African trained migrant doctors reported by the
authorities in Australia, Canada, the United Kingdom, and the
United States. The estimated loss of returns from investment
for all doctors working in the destination countries was $2.17bn
(95% confidence interval 2.13bn to 2.21bn). Table 4 shows the
costs for each country. These ranged from $2.16m for Malawi
(1.55m to 2.78m) to $1.41bn for South Africa (1.38bn to
1.44bn).
Relative burden on health systems
The estimated compounded lost investment for South Africa,
accounting for more than 50% of the estimated compounded
lost investment for all nine countries, was much larger than that
observed in the other countries. Figure 2⇓displays the loss in
relative terms. The size of each bubble represents the ratio of
the estimated compounded lost investment over gross domestic
product. From this perspective, Zimbabwe and South Africa
seem to have the largest losses. The y axis corresponds to the
ratio of (domestically trained) doctors working abroad in the
target countries and those currently working domestically.
Ethiopia, Zambia, and South Africa faired the worst.
Sensitivity analysis
Table 5⇓shows the results for the sensitivity analysis. Applying
the best scenario assumption, the conditions decreased the
estimated investment costs to $1.41bn. Compounding over the
full length of a doctor’s career and using the deposit rate for
each country (the worst scenario) led to substantial increases in
investment loss. Half the estimated losses increased by more
than 10-fold. In absolute numbers, South Africa had the largest
change, from $1.41bn to $9.76bn. In total the countries would
have lost $13.53bn.
Savings in destination countries from
recruited doctors
Destination countries do not have to provide medical school
training to doctors who successfully pass licensing examinations.
Therefore destination countries benefit from not having trained
recruited doctors. Based on the number of doctors working from
the nine source countries and the average cost of medical
education in these countries, this equals a saving of at least
$621m for Australia, $384m for Canada, $2.7bn for the United
Kingdom, and $846m for the United States; $4.55bn in total.
As the United Kingdom had the largest number of African
doctors practising, its savings were the largest.
Discussion
Ethiopia, Kenya, Malawi, Nigeria, South Africa, Uganda,
Tanzania, Zambia, and Zimbabwe have lost more than $2bn
from training doctors who then migrated to one of the four
developed countries: Australia, Canada, United Kingdom,
United States. Medical education is typically highly subsidised
by the public sector in African nations, with more than half of
the medical schools in sub-Saharan Africa either offering free
tuition or charging less than $1000 yearly.8 19 At the same time,
destination countries have saved billions of dollars in training
costs by recruiting doctors who have been trained abroad. As
international efforts are focusing on strengthening health
systems, the development of human resources should be a core
component of support from developed nations.
Strengths and weaknesses of the study
Our study has several strengths and limitations. Strengths
included the use of conservative estimates of costs and lost
investments compared with interest rates often reported by
differing international financial institutions; we chose interest
rates on the lower end of available data to avoid the
overestimation of lost investments. When, for example, we
applied a sensitivity analysis examining deposit rates, the lost
investment increased to over $10bn. We do not know the number
of doctors who emigrated to the destination countries but never
entered medical practice nor did we quantify the number of
doctors practising outside the four destination countries in
settings such as Saudi Arabia, a popular destination for new
graduates. Both of these limitations may result in underestimates
of the true loss to the source countries under study. However,
we did not consider the number of doctors who return to their
source countries nor examine the benefits of doctors sending
financial resources back to families in the home countries. While
these factors may mitigate the losses, little is known about how
widespread or systematic they may be. Remittance by all
professionals to sub-Saharan Africa in 2010 is estimated at
$21.5bn, a growth of 5.5% from the previous year.41 A recent
survey estimated that doctors typically remit $4500 yearly to
their source countries.38 Remittances typically go to family
members rather than the state and so it is impossible to quantify
the impact of remittances on the local economy.
To the best of our ability we assessed whether education in the
source countries is government supported, private, or a
combination of the two, but recognise that this may change over
differing time periods and differing governments. For example,
Uganda has recently changed its public university coverage to
focus solely on science, thereby increasing the number of
medical school attendees with government coverage. Our study
assumes that students go directly from secondary school to
medical school and does not account for those who have
received previous medical training, including former nurses and
clinical officers. We used the current gross domestic product
as a proxy of costs for primary and secondary schools. Gross
domestic product in sub-Saharan African countries has
fluctuated over the past four decades and it is possible that a
different gross domestic product would alter our study findings
for pre-university education. Finally, although confidence
intervals are provided, these assume a fixed interest rate through
time. Given the current poor economic climate, these results
are conservative and we acknowledge a higher degree of
variance.
Comparison with other studies
Three previous studies attempted to quantify the economic value
of losing health staff, but these analyses were limited to
particular countries (Ghana, Kenya, and Malawi).39 40 42 Other
studies found that doctors typically migrate from African
countries to more developed countries—namely, Australia,
Canada, the United Kingdom, and the United
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RESEARCH
States4 12 18 43 44—but do not attempt to quantify the economic
implications of such migration patterns. Our study focused on
the direct costs of educating doctors in the source countries.
Additional economic costs to the loss of doctors from these
source countries occur, including the lost investment on the
education of other health workers. A previous analysis that
examined a case study of only Ghanaian doctors in the United
Kingdom estimated a saving in current training cost to the
United Kingdom of about £65m from the employment of 293
Ghanaian doctors working in 2004.42 A recent survey of African
doctors working in Canada and the United States showed that
most doctors emigrate immediately after training, but, when
considering all respondents to the survey, the average number
of years working in the source countries was 7.2.38 The author
implies that during this period doctors may have already repaid
their debt to the source country.45 Many of the countries we
surveyed employ a lower cadre of health workers for many
common health provisions, including the care of people with
HIV/AIDS, including non-doctor clinicians,46 nurses,47 and
community health workers.48 Other notable economic issues
relevant to the lost investment in doctors include the lack of
specialised medical care available and the morbidity and
mortality associated with it. Although our study examined only
doctors, the emigration of nurses and pharmacists from the
source countries has also been important. We also recognise
that developing countries experience an out-migration of health
workers to other developing countries, and future research
should attempt to estimate losses in other regions.
Possible mechanisms and implications for
clinicians or policy makers
The new code of practice on the international recruitment of
health personnel suggests that source and destination countries
could benefit by crafting bilateral agreements that acknowledge
the transfer of staff from developing countries to developed
ones, and provide technical assistance and other support to
countries that are losing trained health professionals. Our study
highlights that the loss to developing countries is substantial
and that any compensation should be more than token: the lost
return on investments in medical education is one way to attach
a value to the amount of technical or other compensatory
assistance that recipient countries should provide. In 2008, the
United States’ President’s Emergency Plan for AIDS Relief
(PEPFAR) re-authorisation legislation recognised the need to
build an infrastructure for health workers and committed to the
expansion of medical training and research capabilities through
African academic centres, by contributing $130m to improve
and achieve large numbers of health staff over the next five
years.49 Contributions from Australia, Canada, and the United
Kingdom to medical education have been substantially lower.50-52
Our results indicate that South Africa incurs the highest costs
for medical education and the greatest lost returns on investment
for all doctors currently working in destination countries. These
findings are supported by statistics on human health resources.
South Africa has the highest density of doctors per population.
However, the distribution of doctors in South Africa is
unbalanced and there is a 14-fold difference in density of doctors
between urban and rural settings.17 Previous estimates indicate
that up to 30% of South African doctors have emigrated to the
destination countries we examined, many during apartheid.53 In
addition, interviews with health workers revealed that 58% were
intending to emigrate to these countries.53 Thus, South Africa,
although producing a large number of doctors, also loses the
most to developed countries. Conservative estimates indicate
that South Africa requires three times its current workforce to
meet the requirements of providing care for AIDS.54 Any future
approaches to improving the numbers of doctors will need to
recognise that additional educational opportunities may lead to
additional lost investments.
Unanswered questions and future research
Previous research has focused on the number of health workers
working in the destination countries4 12 44 and on the ethics of
recruitment of health staff.55-58 Less research has examined the
impact of the density of health workers on morbidity and
mortality in the source countries. With a new emphasis on
strengthening health systems by major international donors,
questions are arising about what investments should be made
to strengthen a health system and what measures should be used
to determine the strength of a health system. Canada, the United
Kingdom, and the United States have clearly stated that maternal
and child health will be the focus of present investments,
steering away from disease specific investments such as
HIV/AIDS.59 There is a clear need to recognise that measuring
the effectiveness of a health system is a complex endeavour that
may result in unclear findings. The support for education and
retention of health staff represents one major way to ensure that
general and specialty healthcare are available in these source
countries. With the exception of the United States, our chosen
destination countries have not targeted medical or health training
as a focused supportive role. Recent studies have indicated that
although the capacity for medical education is expanding in
Africa, substantial support is needed to improve weaknesses in
infrastructure and that retention strategies need to be developed
to reinforce the number of teaching staff, who are also among
those medical staff who emigrate.19
Conclusions
Countries in sub-Saharan Africa are losing considerable
investments in medical education through the emigration of
doctors to wealthier destination countries. The new voluntary
code urges the government, private agencies, and
non-government agencies that benefit from the immigration of
doctors to increase their technical and financial support to
enhance the strengthening of health systems in developing
countries with critical shortages in health workforce. Efforts to
increase support can include training, financial compensation,
and population specific interventions. These should be
commensurate with the benefits enjoyed by recipient countries.
We thank Peter Arnold (Australian Medical Council) for access to data;
Meredith Fordyce and Mark Doescher (Department of Family Medicine
Research Section, University of Washington) for access to data on
African medical graduates practising in the United States; and Niyi
Awofeso, Ike Anya, Eben Mouton, and Jimmy Volmink for access to
country costs. EJM is supported by a Canada Research Chair from the
Canadian Institutes of Health Research. IB is supported by a
CIHR-Health Canada Research Chair in Health Human Resources
Policy. JN is supported through a National Institutes of Health mentored
patient oriented research career award (K23 AI068582-01).
Contributors: EJM and NF conceived the study. EJM, CGA-Y, MA, NF,
ILB, NB, and AH designed the study. EJM, AH, JN, CGA-Y, MA, AM,
and SK identified the data and obtained the data. SK carried out the
statistical analysis. NF, RSH, NB, and EJM supervised the project.
CGA-Y, MA, AM, ILB, NF, AH, SL, and EJM prepared the first draft of
the manuscript. All authors revised the manuscript for important
intellectual content. All authors approved the final version for publication.
EM will act as guarantor.
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RESEARCH
What is already known on this topic
A lack of adequately trained health workers contributes to weakened health systems
African doctors frequently emigrate for better opportunities
The impact of doctors’ emigration on investments in the health system of individual countries is unknown
What this study adds
Among the nine sub-Saharan African countries most affected by HIV/AIDS, more than $2bn of investment was lost through the emigration
of trained doctors
South Africa and Zimbabwe had the greatest economic losses from such emigration
Australia, Canada, the United Kingdom, and the United States benefit importantly from the recruitment and licensure of doctors educated
elsewhere
Funding: This study received no direct funding. No funding agency has
seen this study.
Competing interests: All authors have completed the ICMJE uniform
disclosure form at www.icmje.org/coi_disclosure.pdf (available on
request from the corresponding author) and declare: no support from
any organisation for the submitted work; no financial relationships with
any organisations that might have an interest in the submitted work in
the previous three years; and no other relationships or activities that
could appear to have influenced the submitted work. JN and SL work
at universities that have received Medical Education Partnership
Initiatives (MEPI) funding from the President’s Emergency Plan for AIDS
Relief.
Ethical approval: This study was approved by the University of British
Columbia. No informed consent was required as no patients were
enrolled and only secondary data were used.
Data sharing: The technical appendix, statistical code, and dataset are
available from the corresponding author at Edward.mills@Uottawa.ca.
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Accepted: 23 September 2011
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Cite this as: BMJ 2011;343:d7031
This is an open-access article distributed under the terms of the Creative Commons
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Tables
Table 1| Statistics on health status and human resources in nine sub-Saharan African countries included in analysis
Doctors per 10 000
population
No of medical
schools
Year of available data on
medical school costs
Estimated No of people* with
HIV
HIV prevalence (%) in 15-49
year olds, 2007Country
<11220101 005 0002.1Ethiopia
1320101 750 0007.8Kenya
<0.512009930 00011.9Malawi
32520092 600 0003.1Nigeria
8820095 700 00016.9South Africa
<0.5520101 400 0005.7Tanzania
142010940 0005.4Uganda
1120091 100 00014.3Zambia
2220091 300 00015.3Zimbabwe
Data from UNAIDS 2010 update, sub-Saharan African Medical Schools Study, and World Health Report.
*Adults and children.
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Table 2| Expenditure on primary and secondary schools in nine sub-Saharan African countries, using the most recent year for which data
were available
Cost per student
YearGDP (current $ per capita)
Expenditure per student
YearCountry Secondary schoolPrimary schoolSecondary school*Primary school*
336.2941.52008934.09.012.62007Ethiopia
1396.82831.420081573.022.222.52006Kenya
686.0647.92008794.021.610.22003Malawi
7481.43740.720082203.056.628.32008Nigeria
9866.98448.5200810278.016.013.72008South Africa
1579.22165.820081400.0NA22.92007Tanzania
1548.0621.920081217.021.27.32009Uganda
669.2550.620081430.07.85.52005Zambia
630.0490.02008500.021.014.02001Zimbabwe
GDP=gross domestic product; NA=not available.
*As percentage of GDP per capita.
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Table 3| Expenditure on medical schools in nine sub-Saharan African countries included in analysis
Total education cost per
student ($) (government
funded)
Total cost of primary
and secondary school
Total cost of medical
school ($)Exchange rate to % (July 2011)
Government subsidised cost
(local currency)Country
29 898127828 6201 Ethiopian birr=0.06485 927Ethiopia
36 453422832 2251 shilling=0.0122 652 500Kenya
34 286133432 9521 kwacha=0.00664 969 161Malawi
36 41011 22225 1881 Nigerian naira=0.00663 860 100Nigeria
58 69818 31540 3831 rand=0.13280 364 79South Africa
27 256374523 5111 shilling=0.0007337 335 000Tanzania
21 040217018 8701 shilling=0.0004849 155 400Uganda
27 749122026 5291 kwacha=0.0002127 073 700Zambia
38 620112037 500$1=$137 500Zimbabwe
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BMJ 2011;343:d7031 doi: 10.1136/bmj.d7031 (Published 24 November 2011) Page 10 of 13
RESEARCH
Table 4| Estimated lost investment from training doctors in nine high prevalence HIV countries who are currently practising in Canada,
the United States, the United Kingdom, or Australia
Estimated lost investment for source countriesNo of source
country doctors
Destination country
Average
savings
Source
country
All doctors in destination
countries ($, millions)
(95% CI)
Average per doctor
in destination
country ($)
Per doctor in destination country ($,
all age groups)
in destination
countries (95%
CI)
interest
rate (%)
24.63 (22.85 to 26.40)43 39443 752567 (526 to 608)Canada1.80Ethiopia
43 883USA
37 883UK
40 589Australia
16.75 (14.97 to 18.50)50 74853 461328 (293 to 363)Canada1.81Kenya
53 623USA
46 253UK
49 577Australia
2.16 (1.55 to 2.78)51 23861 92641 (2 to 53)Canada2.75Malawi
62 412USA
49 722UK
55 415Australia
654.27 (649.57 to658.50)89 238104 3627106 (7059 to
7152)
Canada4.75Nigeria
107 001USA
71 757UK
87 354Australia
1412.70 (1382.51 to
1435.95)
127 221150 27310 822 (10 644 to
11 000)
Canada4.27South
Africa 153 327USA
107 178UK
127 669Australia
3.49 (2.81 to 4.17)4461647 60081 (65 to 97)Canada2.60Tanzania
47 930USA
38 676UK
42 831Australia
13.61 (12.31 to 14.85)32 92634 830409 (371to 447)Canada2.36Uganda
35 024USA
28 843UK
31 622Australia
12.14 (10.68 to 13.58)57 41266 703206 (181 to 231)Canada4.00Zambia
67 889USA
48 574UK
57 164Australia
39.61 (35.87 to 43.27)101 440120 295380 (344 to 416)Canada5.1*Zimbabwe
123 804USA
80 555UK
99 650Australia
*Inflation rate.
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RESEARCH
Table 5| Sensitivity analysis of estimated lost investment using variations on time working in destination countries, interest rates, and
cost of education
Estimated lost investment for source countries ($, millions)
Source country
Compounding over full length of career and using
deposit rate
Assuming later emigration and attendance at
private schoolsAll doctors from source countries
260.3221.7624.63Ethiopia
59.0211.8916.75Kenya
5.151.402.16Malawi
2297.82387.14674.26Nigeria
9764.50960.881412.70South Africa
68.360.483.49Tanzania
103.978.3313.61Uganda
276.429.3712.14Zambia
699.1723.1439.61Zimbabwe
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BMJ 2011;343:d7031 doi: 10.1136/bmj.d7031 (Published 24 November 2011) Page 12 of 13
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Figures
Fig 1 Flow of countries through study
Fig 2 Loss of doctors to destination countries, compared with burden of HIV in nine African source countries. Size of each
bubble represents ratio of estimated compounded lost investment over gross domestic product, and y axis corresponds to
ratio of doctors working in target countries and doctors currently working domestically
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BMJ 2011;343:d7031 doi: 10.1136/bmj.d7031 (Published 24 November 2011) Page 13 of 13
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