Evidence of Crisis and Analysis of Contributing...

The State of theHealth Workforce inSub-Saharan Africa:Evidence of Crisis and Analysisof Contributing Factors

Bernhard Liese

The World Bank/Georgetown University

Gilles Dussault

The World Bank

Africa Region

The World Bank

Washington, D.C.

Africa Region Human DevelopmentWorking Paper Series

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Copyright © September 2004Human Development SectorAfrica RegionThe World Bank

The findings, interpretations, and conclusionsexpressed herein are entirely those of the authors They do not necessarily represent the views of the World Bank Group, its ExecutiveDirectors, or the countries that they representand should not be attributed to them.

Cover design by Word ExpressTypography by Word Design, Inc.Cover photo:

Table of Contents

Foreword . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .v

Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .vii

I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1

II. Country Estimates of the Health Sector Workforce . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2

III. Trends in the Health Workforce . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6

IV. Geographical Imbalances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .8

V. Impact of Economic Reform Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10

VI. International Migration of Health Professionals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .12Factors Contributing to Emigration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14

VII. Impact of HIV/AIDS on the Health Sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .17

VIII. Achieving the Millennium Development Goals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .20

IX. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .22

Annex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .24

Notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .38

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .39

FiguresFigure 1: Average Health Workforce Availability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4Figure 2: Trend of Africa’s Physician to Population Ratio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6Figure 3: Trend of Africa’s Nurses to Population Ratio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7Figure 4: Niger Health Personnel Distribution by Region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .9Figure 5: Health Personnel from Zambia and Zimbabwe Registered in the UK . . . . . . . . . . . . .13Figure 6: Health Personnel in South Africa 1996 vs. 2001 . . . . . . . . . . . . . . . . . . . . . . . . . . . . .15Figure 7: Proportion of Health Workers Who Intend to Migrate . . . . . . . . . . . . . . . . . . . . . . . .15

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Figure 8: Distribution of Increased Labor Costs due to HIV/AIDS in Zimbabwe . . . . . . . . . . . .18Figure 9: Projected Health Workers with AIDS in Botswana . . . . . . . . . . . . . . . . . . . . . . . . . . .18Figure 10: Estimates of Shortages of Health Workers in SSA . . . . . . . . . . . . . . . . . . . . . . . . . . .21

BoxesBox 1: Malawi Faces Grave Health Personnel Shortage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3Box 2: The Impact of Structural Adjustment Programs in Cameroon and Ghana . . . . . . . . . . . .11Box 3: Ghana’s Loss of Health Sector Workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14Box 4: Impact of HIV/AIDS on Kenya’s Health Workforce . . . . . . . . . . . . . . . . . . . . . . . . . . . .19

TablesTable 1: Classification of Sub-Saharan Countries by HRH Ratios and Languages . . . . . . . . . . . .5Table 2: Projection of the Cost of the Health Personnel Brain Drain for Ghana . . . . . . . . . . . . .16Table 3: WHO Estimates of Health Personnel per 100,000 Population for SSA . . . . . . . . . . . . .24Table 4: WHO Estimates of Health Personnel per 100,000 Population, Averages . . . . . . . . . . .26Table 5: Trends in Physicians 1960-1998 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .26Table 6: Trends in Nurses 1960-1998 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .27Table 7: Health Personnel Statistical Database . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .28Table 8: Brain loss in 9 SSA countries, by profession . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .35

Foreword

he declaration and acceptance of theMillennium Development Goals her-alded renewed commitment by coun-tries and the international community

to work towards the achievement of a betterquality of life for all the people of the develop-ing world. At least 4 of the 8 goals are healthrelated and provide the impetus for govern-ments, bilateral and multilateral developmentagencies working in the health sector to devel-op effective strategies to attain these goals.

Yet, for many African countries, it will behard, if not impossible to achieve the goalsby 2015. The key obstacle is now recognizedas the lack of a stable human resource base inthe health sector. Absolute shortages, internaland external migration, inadequate remuner-ation and incentive mechanisms, maldistribu-tion and training and education issues ofhealth workers, as well as macroeconomicpolicy constraints (often highlighted by theBank, the Fund and other internationalfinancial institutions) are identified as rootcauses for the present situation. The realiza-tion that there are health work-force issues ofsuch serious dimensions has led the usage ofthe phrase “The African health workforcecrisis”.

This report is an attempt to systematicallydocument and evaluate the state of the healthworkforce in Africa. It draws on academicpublished literature (which is limited), theWHO statistical database (which is incompleteand only sporadically updated), studies ofbilateral donors , national documents, andnewspaper articles. The report shows clearlythat for more than a decade HR issues havereceived very little attention. Ministries ofFinance often consider HR as a recurrentexpenditure and a drain on the budget ratherthan a critical investment and input to theattainment of positive health outcomes. Demo-tivation of the health workforce has reachedalarming levels and resulted in their migrationto the developed world. Increasing nursingshortages in many high income countries suchas the UK, USA, France, and Canada have ledto a dramatic increase in emigration of highlyskilled health personnel particularly fromAnglophone and now from Francophonecountries in Africa.

The situation has been compounded by theHIV/Aids epidemic which has put additionalstrains on the health care sector. The diseaseburden has escalated, productivity of healthworkers has diminished and a great number of

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health workers have succumbed to the epidem-ic, thus aggravating the crisis.

The report shows that Africa faces a crisisand offers recommendations for action. It sug-gests the need to recognize the importance toalign health sector, civil service and macroeco-nomic policies; it stresses that countries mustoffer internally competitive wages and nonfi-nancial incentives; and proposes to invest intotraining that is specifically oriented to the

needs of national markets. Our hope is that thereport will stimulate further work on thisimportant issue.

Ok PannenborgSenior Health Advisor and Sector Leaderfor Health, Nutrition and PopulationHuman DevelopmentAfrica Region

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Acknowledgement

We would like to thank our colleagues, Christoph Kurowski and Demissie Habte, for shar-ing their data and experience and their guidance. We would also like to thank Ying Zhou,who provided superb research support, and Elsie Lauretta Maka, who has overseen the pub-lication of this report.

CHAPTER 1

Introduction

n 2000, all 189 United Nations mem-ber states endorsed the MillenniumDevelopment Goals (MDGs). This rep-resented an unprecedented agreement

within the development community about keydevelopment outcomes (OECD, 2002). TheMDGs are a set of 8 goals, 18 targets and 48performance indicators relating to povertyreduction by 2015. Of these goals, four aredirectly related to better health outcomes: two-third reduction of infant and under five mor-tality, three-fourth reduction of maternal mor-tality, halt and reverse HIV/AIDS, tuberculosis,and malaria epidemics, and halve the propor-tion of people suffering from hunger. By someestimates, US$46 billion per year is required toscale up health services in low-income coun-tries (WHO CMH, 2001). The majority ofthese funds would be used to expand thecapacity of human resources in health,1 as thisis a prerequisite for increasing the access to

essential health services and for bringing downthe disease burden to the level of the MDGs(WHO CMH, 2001).

This paper examines some of the issues ofhuman resources in the health sector, focusingon the situation in Africa in view of its partic-ularly critical state. First, we examine the cur-rent state of the health sector workforce,including the latest statistics and trends. Sec-ond, we analyze the economic factors thatinfluence the availability of human resources.Next, we take a close look at the brain lossphenomenon, or exodus of trained health careprofessionals from the country or from the sec-tor. Then, a discussion of the impact of theHIV/AIDS epidemic on the workforce itselfand working conditions follows. Last, we con-clude with some issues that governments anddevelopment partners need to tackle to addressthe growing human resources crisis in theAfrican health sector.

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CHAPTER 2

Country Estimates of the Health Sector Workforce

p-to-date reliable statistics on humanresources for health (HRH) in Africaare scant, and when available theyremain difficult to standardize and

compare internationally.2 Despite this datachallenge, published figures of health person-nel to unit population ratios from the 1960sthrough the mid-to-late 1990s—and somemore recent figures—clearly indicate that aserious crisis in human resources exists. Thesevere shortage and imbalanced distribution oftrained health personnel poses a serious obsta-cle to the achievement of the MDGs and to theimprovement of the overall health of the poor.Here is a quantitative overview of the extent ofthis crisis.

Latest WHO Statistics

There are a range of indicators that measurethe level of human resources employed in acountry’s health services. The principal indica-tor is the stock of health personnel, typicallymeasured as the proportion of health workersamong the total population. Though this indi-cator is theoretically simple, there are a num-ber of practical difficulties when comparing itacross countries. Occupational classifications

are country specific, as well as the methodused to count the number of such persons ineach occupations (such as the distinctionbetween headcount data and full-time equiva-lent data) (Diallo et al., 2003). Further, theactual roles and scope of practice of healthcare workers also vary, making them difficultto compare. Finally, this indicator depends onthe accurate measurement of the denominator,e.g. total population. In many low-incomecountries, and especially in Africa, census datado not exist and when they do are often unre-liable.

Health care-related occupations are mainlycategorized under two groups according to theInternational Standard Classification of Occu-pations:

1. “professionals” (physicians, nurses andmidwifes, and other health professionals,such as dentists and pharmacists); and

2. “technicians and associate professionals”(medical assistants, dental assistants,physiotherapists, opticians, sanitarians,nursing and midwifery associate profes-sionals and traditional medicine practi-tioners) (Diallo et al., 2003).

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Country Estimates of the Health Sector Workforce 3

Box 1: Malawi Faces Grave Health Personnel Shortage

The World Bank sponsored a Health, Nutrition, and Population Project in Malawi from1991–2000. The Implementation Completion Report (ICR) found that under-staffed andunder-supplied facilities have become increasingly common, with adverse effects on quality ofcare. A survey conducted by KPMG in 1999 showed that many district hospitals do not havephysicians, that lower-level staff were performing higher-skill functions, and that even in terti-ary facilities patients rarely see a physician.

Among SSA countries, Malawi has consistently had one of the worst health worker to pop-ulation ratios, with 2.22 physicians per 100,000 people, compared to 4.55 in Kenya and 9.09in Zambia (Picazo, 2002). Currently 50% of the available nursing posts are unfilled. Malawihas struggled with low numbers of health professionals in the past, but the situation hasbecome more acute due to: 1) low pay and poor staff benefits of government workers; 2) anexodus of government workers to the private sector, which offers better salaries and benefits;and 3) the increasing demand for skilled nurses in neighboring countries and in Europe.

The Malawi Nursing and Midwifery Council has also insisted they should produce higherskilled registered nurses (mainly hospital-based, with a longer and more expensive trainingperiod) rather than the lower skilled, but more cost-effective community health nurses. In addi-tion, a lack of nursing tutors, severe scarcity of secondary school graduates, limited scienceeducation, and increasing death and morbidity from the AIDS epidemic all continue to con-tribute to the Malawi nursing shortage. Without improvements in training and remunerationof health professionals, Malawi will continue to lose valuable human resources.

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Figure 1: Average Health Workforce Availability (1995–2002)

Source: WHO Statistical Information Service. Figures are from one year between 1994-1998, with the except of Nigeria for which figures arefrom 1992. May be accessed at http://www3.who.int/whosis.

4 The State of the Health Workforce in Sub-Saharan Africa

Although health personnel to populationratios are somewhat problematic for the vari-ous reasons listed above, they do provide theclearest starting point in recognizing the extentof the crisis.

The World Health Organization (WHO)Statistical Information Service lists such ratiosfor most countries. Tables 3 and 4 in theAnnex list the data for physicians, nurses, mid-wives, and pharmacists for all availableAfrican countries and selected others for com-parison. The figures for Africa are appallinglylow, especially when compared to other emerg-ing and developed countries (Figure 1 and seeBox 1 for the case of Malawi). The averageratio of physicians per 100,000 people in sub-Saharan Africa (SSA) was a meager 15.5, com-pared to an average of 311.0 in nine selectedindustrialized countries. For nurses, the samecomparison was 73.4 in SSA and 737.5 inindustrialized countries. On average, Africancountries had about 20 times fewer physiciansand 10 times fewer nurses than developedcountries. Even compared to other emergingcountries, SSA numbers are strikingly low. ForIndia, Korea, Singapore, and Vietnam, theaverage number of physicians per 100,000people was 106.3; for nurses it was 220.4..

Out of 48 African countries, thirteen3 hadfewer than five physicians per 100,000 people,and, except for Burkina Faso, Mozambique,and Tanzania, those same countries had fewerthan 20 nurses per 100,000 people (Table 3 inthe Annex). Further, there is significant indi-vidual variation among countries throughoutthe continent. For example, Burkina Faso has 4physicians and 26 nurses per 100,000 people

compared to Egypt with 218 physicians and284 nurses per 100,000 people. However,some other SSA countries are faring a little bet-ter: Botswana has 28.7 physicians and 241.0nurses per 100,000 people, while Congo has25.1 physicians and 185.1 nurses per 100,000people. While pharmacists play a key role inpeople’s access to medicines, very little datahas been collected on their numbers. As can beseen from the Table 3 in the Annex, only ahandful of countries report data. This dataproblem is not specific to SSA but applies toother middle or high income countries as well.

Based on the ratio of physicians and nursesto population, we divided the SSA countriesinto four groups. We use a physician to100,000 population ratio of 10 and a nurse topopulation ratio of 20, respectively, as thethreshold to categorize each country into eithera top or bottom group (Table 1). Thirty threeout of 43 analyzed countries (about 78%) havemore than 20 nurses per 100,000 population,and only 18 out of the 43 countries (about42%) have more than 10 physicians per100,000 population. A total of ten countrieshave less than 10 physicians and less than 20nurses per 100,000 population. There are nocountries with 10 or more physicians per100,000 population and less than 20 nurses.

A majority of Lusophone and Arabic speak-ing countries have more than 10 physicians per100,000 population, and all of their nurses topopulation ratios are above 20. In contrast,more than half of the Anglophone countriesand almost two third of the Francophonecountries have less than 10 physicians per100,000 population.

Country Estimates of the Health Sector Workforce 5

Table 1: Classification of Sub-Saharan Countries by HRH Ratios and Languages

More than 20 Nurses Less than 20 Nurses

More than Anglophone: Botswana, Kenya, Namibia, 10 Physicians Nigeria, South Africa, Sudan, Swaziland

Francophone: Benin, Congo, Guinea, Mauritius, Senegal, Seychelles

Lusophone: Cape Verde, Guinea Bissau, Anglophone: Gambia, Liberia, UgandaSao Tome and Principe

Francophone: Burundi, CAR, Chad, Arabic: Djibouti, Mauritania Madagascar, Mali, Togo

Less than Anglophone: Ghana, Lesotho, Sierra Leone, Other: Ethiopia10 Physicians Tanzania, Zambia, Zimbabwe

Francophone: Burkina Faso, Cameroon, Cote d’Ivoire, DR Congo, Niger,

Lusophone: Angola, Mozambique

Arabic: Somalia,

Other: Eritrea

Source: Annual statistics from the World Bank and WHO. See: World Bank. 1978 and 1980. World Development Report: World DevelopmentIndicators; World Bank. 1993. World Development Report: Investing in Health. p. 208; and WHO. 1998. WHOSIS database. Available athttp://www3.who.int/whosis.

CHAPTER 3

Trends in the Health Workforce

he production or supply of health sec-tor workers does not even come closeto keeping pace with the rate of popu-lation growth.4 Although these statis-

tics paint a discouraging picture, they provideonly part of a larger picture. Issues of healthworker distribution within a country and

workplace conditions further compound thecurrent crisis.

Figures 2 and 3 compare the trends in physi-cian and nurse to population ratios since 1960of eight sub-Saharan countries for which thedata was available with Morocco and India.The following are a few key observations

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Figure 2: Trend of Afruca’s Physician to Population Ratio (1960–2002)


Trends in the Health Workforce 7

based on country data reported in Tables 5 and6 in the Annex:

When compared to figures from either the1970s or 1980s, 7 out of the 8 SSA countries5

experienced a decline in physicians per100,000 population in the 1990s. Five of theAfrican countries6 experienced the same trendfor nurses. By 2002 the situation had slightlyimproved in three countries but deteriorated inMadagascar.

The physician to population ratio has stag-nated or declined in nearly every SSA country,since 1960. Meanwhile, India has made con-siderable progress—increasing its physician topopulation ratio from 17.2 per 100,000 popu-lation in 1960 to 51.2 by 2002, and improvingits nurse to population ratio from 10.4 per100,000 population to 62.9 over the sameperiod. Morocco also experienced improve-ment in the health personnel ratio during thistime period.

These figures indicate that ameliorating thehuman resources for health situation in SSA isan enormous challenge that must be surmount-ed to adequately serve poor populations. Theexperience of India shows that it can be done.

In addition to these figures, confirmationthat the crisis continues and may be worseningwas presented at a recent Consultation of 17African countries organized by the World Bankand WHO. Background papers documentedthe following:

• In 1998, medical physician vacancy ratesin the public sector were reported at 43%in Ghana and 36% in Malawi.

• In 1998, the public sector nurse vacancyrate was reported at 48% in Lesotho.

• Fifty percent of physicians in public serv-ices in Namibia are reported to be expa-triates.

• Cameroon has had no recruitment ofhealth personnel in the public sector for15 years.

• Data from Ghana, Zambia, and Zimbab-we suggest that annual losses from publicsector health employment continue atrates of 15% to 40% (WHO/WB, 2002).

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Figure 3: Trend of Africa’s Nurses to Population Ratio (1960–2002)


CHAPTER 4

Geographical Imbalances

eyond national-level shortages ofhealth personnel, imbalances in geo-graphic distribution—especially be-tween rural and urban areas—exacer-

bate the health workforce crisis (Dussault andFranceschini, 2003). In Ghana, Guinea, andSenegal, more than 50% of physicians are con-centrated in the capital city where less than20% of the population lives (Ghana MoH,2002). In many countries, a similar situationexists for nurses, pharmacists, and medicaltechnicians. For example, 55% of pharmacistsin Ghana work in the Greater Accra region,which has 16% of the total population; only2% of Ghanaian pharmacists work in theNorthern Region, with 10% of the population(Ghana MoH, 2002).

Other recent reports describe this urban-rural split dramatically. In Chad, for example,the capital region of N’Djaména was reportedto have 71 physicians per 100,000 population,whereas the rural Chari-Baguirmi region hadonly 2 physicians per 100,000 (Wyss et al.,2002; Wyss et al., in press, cited in Kurowski,2003). A report from Mali shows a similarimbalance. Nationwide, Mali was reported tohave about 5.15 physicians per 100,000 peo-

ple, but that ratio ranged from 18.7 in the cap-ital region (Bamako) to a mere 1.9 in theKoulikoro region (Ministère de Santé, Mali,2002).

In Niger, recent data on the regional distri-bution of health personnel show that mosthealth professionals concentrate in urban areas(Figure 4). In the capital, Niamey, the physi-cians to population ratio is about 24 timeshigher than in the Tillaberi region; the nursesand the midwives to population ratios are 7and 17 times, respectively, higher than in theMaradi region (World Bank, 2002b).

Studies on the health workforce in Tunisia(which has much more adequate nation-wideratios), Angola, and South Africa equallyshow geographical imbalances, implying thatthe urban-rural split is likely to be found con-tinent-wide (Bchir and de Brouwere, 2000;Fresta, Fresta, & Ferrinho, 2000). This indi-cates that rural populations have much lessaccess to health care services than do urbandwellers, and are often forced to travel signif-icant distances to find any health care, evenfor their most basic needs. This adds to thecosts of services and can even be a deterrent touse services.

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Figure 4: Niger Health Personnel Distribution by Region (2000)

Source: World Bank, 2002b.

CHAPTER 5

Impact of Economic Reform Processes

he crisis in the African health work-force has been emerging over severaldecades. Starting from very low levelsin the 1960s, many countries’ work-

forces progressed somewhat in the 1970s andearly 1980s, but stagnated or even declined inthe late 1980s and the 1990s following thewell-known wave of economic crises that hitthe continent. Macroeconomic constraints dis-couraged the expansion of personnel and serv-ices; thus, the international community andlow-income country governments have givenlittle attention to health-workforce issues inthe past two decades. The health workforcewas seen as a drain on the budget rather thanan asset for poverty reduction, and unemploy-ment of health professionals even appeared incountries where needs were enormous.7 Somecountries even enacted complete freezes onrecruitment of certain health personnel (Ngu-for, 1999; WHO/WB, 2002).8

The consequences of a series of reformprocesses, starting in the mid-1980s, has large-ly determined the present situation. Whenmany African countries were confronted witha dramatic fall in public revenue from exportsof commodities, a series of important econom-ic reforms were introduced. In many of thecountries, the reforms were executed through

structural adjustment programs (SAP) of theWorld Bank and International Monetary Fund(IMF). A central tenet of these reforms includ-ed better control of public wages, reduction ofpublic expenditures, privatization of publicenterprises, elimination of subsidies, liberaliza-tion of the economy, and devaluation of thecurrency in order to achieve sustained growth.

Results of these measures on public servants,particularly on health personnel, were not dra-matically different from one country to anoth-er. The impact is a lasting one, largely deter-mining the attitudes of health providers andthe actual availability of health personnel. Inmost countries, the SAP reforms went alongwith public service reform and decentralizationof the health sector. Case studies for Cameroonand Ghana, where detailed research is avail-able including interview surveys with healthpersonnel, are illustrative of the impacts (SeeBox 2).

Between 1981 and 1991, the Bank conduct-ed 55 civil service reform operations in Africa.More than half of these operations were struc-tural adjustment loans. But the functionalreviews failed to mention the impact on thehealth and education sector. A review of theWorld Bank’s operations on macroeconomicsin Africa between 1995 and 2002 found that

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Impact of Economic Reform Processes 11

while half of the operations discussed theimpact of changes in public expenditure onhealth, the impact on the health workforce wasnot mentioned in any of the documents.Although one third of the operations apparent-

ly were associated with changes in the wagebill for public sector health employees, only10% of the operations mentioned the implica-tions to the health workforce (Elmendorf,2003).

Box 2: The Impact of Structural Adjustment Programs in Cameroon and Ghana

In Cameroon, government reform was initiated in the early 1980s as part of their StructuralAdjustment Program (SAP) administered by the World Bank and International Monetary Fund(IMF). Measures affecting the health sector resulted in suspending recruitment, strict imple-mentation of retirement at 50 or 55, limiting employment to 30 years, suspension of any finan-cial promotion, reduction of additional benefits (housing, travel expenses, etc.), and two salaryreductions—totaling 50%—and a currency devaluation resulting in an effective income loss of70% over 15 years. In addition, paramedical training for nurses and laboratory technicianswas suspended for several years and schools closed.

The overall effect was dramatic. In 1999, the health sector budget had shrunk to 2.4% ofthe national budget, from 4.8% in 1993. These adjustments occurred while in the private sec-tor (40% of service provision—mostly denominational) wages substantially increased, adjust-ing again for the effects of the devaluation. Thus, the spread between public and private healthworker income is large. Not surprisingly, in 1999, jobs in the public sector were about 80%unfilled, and Cameroon had a truly de-motivated national health workforce.

Notwithstanding the efforts of many health workers to provide services, in general, a lais-sez faire attitude prevails—with under the table payments, absenteeism and a lack of attentionto quality. The perception of punishment inflicted by the IMF and the World Bank is still com-mon. On the positive side, however, budgets have been decentralized and are now availablelocally, and the private sector has been strengthened. The serious shortage of health workers,though, has lead to the direct recruitment of qualified personnel by communities and hospi-tals, which have the financial resources.

In Ghana, the reform process focused on national democratization, decentralization, and thecreation of the Ghana health services. While the civil service lost 32,000 jobs between 1987-1989, the health sector remained somewhat a priority and faired better than other sectors.There was also meaningful sector reform with emphasis on the quality of services. Healthworkers have received some benefits—such as first priority housing in rural areas andincreased salaries in urban areas. Despite the well-documented severe shortage of health work-ers and significant brain drain, the motivation of the health workforce remains good in Ghana(Wiskow, 1999).

CHAPTER 6

International Migration of Health Professionals

migration of highly skilled personsfrom developing to developed countrieshas increased in the last decade (Lowelland Findlay, 2001). Growing concerns

among many rich countries about actual orfuture shortages9 has initiated large-scalerecruitment of foreign-trained health workers.Foreign-trained health professionals are esti-mated to represent more than a quarter of themedical and nursing workforces of Australia,Canada, the UK, and the US (OECD, 2002),and the needs are rapidly growing. This trendis expected to increase, with health profession-als being increasingly recruited from SSA. Thenumber of overseas trained nurses and mid-wives registering with the United Kingdom Co-operative Council from SSA10 increased from905 in 1998/99 to 2133 in 2000/01 (Mar-tineau et al., 2002). Figure 5 illustrates thisaccelerating trend with a depiction of Zambia’sand Zimbabwe’s loss of nurses and midwivesto the U.K. It has been estimated that 15,000foreign nurses were recruited in the U.K. in2001 and that 35,000 more are needed by2008 (USAID SARA, 2003).

The permanent departure of skilled labor, or“the emigration or flight of skilled human cap-ital from one country to the other in search ofbetter returns to one’s knowledge, skills, quali-

fications, and competencies” (Lowell and Find-lay, 2001) is depleting human capital in manydeveloping countries and further reducing thepossibility for strong economic growth.11 Sim-ply put, the emigration of an individual is aloss because s/he is an investment loss to hercountry, since s/he will not apply the educationgained in-country. The UN Commission forTrade and Development estimated that eachmigrating African professional represents aloss of US$184,000 to Africa. Paradoxically,Africa spends US$4 billion a year on thesalaries of 100,000 foreign experts (Seepe,2001).

In Ghana, for example, a continuous flow ofphysicians, nurses, midwives, and pharmacistshave left the country directly after receivingtheir degrees (See Box 3). According to itsHealth Minister, Kenya has only retained 600of 6,000 physicians trained in public hospitals.This number rose to 1200 after increasingcompensation for physicians, which is stillbelow the requirement. Similarly, 4,000Kenyan nurses have left for the UK and the US(BBC, 2003). In Zimbabwe, only 360 of 1,200physicians trained during the 1990s were prac-ticing in their country in 2000; half of thosetrained in Ethiopia and Zambia have also emi-grated (Frommel, 2002). Table 8 in the Annex

12

E

International Migration of Health Professionals 13

summarizes earlier studies of the sub-Saharanbrain drain.

A pattern has emerged where physicians andnurses are continually moving to countrieswith a perceived higher standard of living, cre-ating what has been referred to as a “carousel”of movement (Martineau, Decker, and Bun-dred, 2002). Canada for instance recruits pri-mary care physicians from South Africa towork in remote areas, leaving South Africa tofill vacancies by recruiting from Zimbabwe,Botswana, Malawi, and other African coun-tries. More than 600 South African physiciansare registered in New Zealand, at a cost toSouth African taxpayers of roughly US$37 mil-lion, reports the University of Western Cape,South Africa. As of 1999, 78% of rural physi-cians in South Africa were from abroad, most-ly from Cuba (OECD, 2002). South Africapresents a rare case because it is one of the fewdeveloping countries that pays comparativelyhigher salaries and is, thus, able to compensatefor emigration. Yet WHO data, summarized inFigure 6, show that the country still experi-enced a strong net loss of health personnel. Theratios of physicians and nurses per 100,000population dropped by 55% and 70%, respec-tively, between 1996 and 2001. For the many

sub-Saharan countries not able to pay compet-itive salaries and, therefore, not able to attracthealth personnel from abroad the situation iseven more critical.

This brain loss is a particular problem inAfrica where the challenge of developing andretaining human resources is extremely diffi-cult and fundamental for development(Wadda, 2000). Worsening economic condi-tions and severely declining or stagnantsalaries and benefits contribute to the loss ofhealth personnel. Although data on this phe-nomenon is sketchy, the International Officefor Migration estimates that 300,000 Africanprofessionals live and work in the West (Shinn,2002).

The brain drain will remain a relevant forcefor the foreseeable future and entails signifi-cant costs to sub-Saharan Africa. As summa-rized in Figure 7, a study of migration issues insix African countries found that 68% of healthworkers in Zimbabwe intend to migrate, 49%in Cameroon, and about 60% in Ghana andSouth Africa (Awases, Gbary, and Chatora,2003). A study by the Ministry of Health inGhana (2002) projects that the costs willamount to US $55 million between 2001 and2006 (Table 2). The largest fractions of these

1583

52

221

40

1086

0

200

400

600

800

1000

1200

1999 2000 2001

Num

ber o

f Nur

ses a

nd M

idw

ives

Zambia Zimbabwe

Figure 5: Health Personnel from Zambia and Zimbabwe Registered in the UK

Source: Loewenson and Thomson, 2002.


costs are the lost investment in physicians’ andpharmacists’ training.

Factors Contributing to Emigration

To exactly define the factors contributing toemigration is a difficult task because mosthealth professionals do not report their inten-

tion to emigrate, nor the reasons why they doso; they simply vacate their posts, resign, orask for leave without pay for an indefinite peri-od of time (Awases, Gbary, and Chatora,2003). The causes and extent of emigrationvary from one country to another, but lack ofjob opportunities, low wages, and a poorworking environment are the most commonlycited causes. Negative side effects of SAPs,

Box 3: Ghana’s Loss of Health Sector Workers

The State of Ghanaian Economy Report 2002 shows that 31% of trained health personnel,including physicians, nurses, midwives, and pharmacists, left the country between 1993 and2002 (Safo, 2003). Table 1 below shows trends in employment of human resources in healthby the government of Ghana between 1996 to 2002 based on a government report. While bothreports signify the extensive degree of brain loss in Ghana, it is questionable whether any ofthe currently existing records demonstrate accuracy, consistency, and reliability, since varia-tions occur from report to report. As seen in Table 2 below, the University of Ghana MedicalSchool, the School of Medical Sciences of KNUST, and the UDS Medical School train onlyapproximately 150 medical officers annually. However, 50% of every graduating class leavesthe country within the second year, while 80% have left by the fifth year (Safo, 2003).

This exodus of medical officers is mirrored in other health sector professions. Out of 944pharmacists trained between 1995 and 2002, a total of 410 were presumed to have left thecountry by the end of 2002. The number of nurses and midwives immigrating to foreign coun-tries is greatest compared to all other categories; of the 10,145 trained between that same peri-od, 1,996 were deemed to have left Ghana by the end of 2002 (Safo, 2003).

Table 1: Public Sector Health Staff, Ghana

CATEGORY 1996 1998 2000 2002

Physicians 1,154 1,132 1,015 964Nurses (including auxiliaries) 14,932 15,046 13,742 11,325Pharmacists 230 200

Source: Ghana MoH. (2002). Human Resources Projections from Internal Report.

Table 2: Annual Output of Trained Public Sector Health Staff, Ghana

CATEGORY Annual Production

Physicians 150*Professional Nurses 500Midwives 200Community Health Nurses 200

Source: Ghana MoH. (2002). Human Resources Projections, Internal Report.*Safo, A. (2003). 604 physicians abandon Ghana. Public Agenda

International Migration of Health Professionals 15

with their associated measures to eliminate orreduce budget deficits and public expenditure,downsizing or retreat of government from eco-nomic activity, and the liquidation or privati-zation of enterprises, have also led to the emi-gration of professionals (Mato, 2002). Awases,Gbary, and Chatora (2003) report that otherde-motivating factors include a lack of oppor-

tunities for continuing education and training,mediocre quality of training, and inadequateday care facilities for their children.

Political instability, lack of security and anenvironment of abject poverty have also beencited as factors contributing to out-migration.Today, health professionals in SSA work inextraordinary circumstances. The pressure of

5625

472

140

0

100

200

300

400

500

Heal

th P

erso

nnel

pe

r 100

,000

Pop

ulat

ion

Physicians Nurses

1996 2001

Figure 6: Health Personnel in South Africa 1996 vs. 2001

Source: WHO, 2003.

49

62

38

58

26

68

0

10

20

30

40

50

60

70

Cameroon Ghana Senegal South Africa Uganda Zimbabwe

Perc

enta

ge

Figure 7: Proportion of Health Workers Who Intend to Migrate

Source: Awases, Gbary, and Chatora, 2003.


having too many patients increases daily stresslevels and leads to poor quality of care. Poorworking conditions are reported to seriouslyundermine health systems performance bythwarting staff morale and motivation, anddirectly contributing to problems in recruit-ment and retention (WHO, 1996). These“push” factors are compounded by “pull” fac-

tors, including active recruitment strategies byagencies from rich countries. While the manyaforementioned factors may de-motivate anddiscourage health care workers, other studieshave found that most individuals who do stayin the health sector, work hard and receiverecognition and status from colleagues andfamily (Stillwell, 2001).

Table 2: Projection of the Cost of the Health Personnel Brain Drain for Ghana (in millions of US$)

2001 2002 2003 2004 2005 2006 Total

Physicians 3.60 3.84 4.02 4.14 4.38 4.50 24.48Pharmacists 3.82 4.14 3.58 3.15 2.77 2.51 19.97LabTechnician 0.11 0.15 0.10 0.08 0.07 0.06 0.57GenNurses 1.31 1.31 1.32 1.33 1.33 1.33 7.93Midwives 0.36 0.36 0.36 0.37 0.37 0.37 2.19C.H. Nurses 0.06 0.06 0.07 0.07 0.08 0.08 0.42Total 9.26 9.87 9.45 9.14 8.99 8.86 55.57

Source: Ghana Ministry of Health Report, 2002.

CHAPTER 7

Impact of HIV/AIDS on the Health Sector

hile we have touched upon someof the issues affecting the number,distribution, and performance ofworkers in the health sector, the

enormous impact of the HIV/AIDS epidemicmerits its own discussion. The epidemic hasimpacted health sector workforce in two ways:1) direct costs—labor loss, disability and deathbenefits, and increasing medical aid costs; and2) indirect costs—increased absenteeism,reduced productivity, and stressed workforcefrom additional staff recruitment and trainingof personnel (Kinoti, 2001). See Box 4 for thecase of Kenya.

With a generalized epidemic of HIV/AIDS inmany African countries, health care workersthemselves are being infected, as they are partof the adult, sexually active population. Theimpact of HIV/AIDS is serious and is estimat-ed to be the cause of between 19-53% of alldeaths of government health employees inAfrican countries today (Tawfik and Kinoti,2001). This results in personnel attrition due todeath and absenteeism due to sickness. Forexample, by some estimates a person livingwith AIDS may be away from work for up tohalf the time of their final year of life (Tawfikand Kinoti, 2001). Caring for ill family mem-bers or dependents and attending funerals also

contributes to worker absenteeism. Studies inZimbabwe indicate that almost 60% ofincreased labor costs are attributed toHIV/AIDS absenteeism (Whiteside and Sunter,2001). For a distribution of these costs see Fig-ure 8.

Caring for AIDS patients has made the workenvironment more complex, difficult andstressful as well as a chilling place to work—with the fear of infection and also with a con-stant observance of patients dying. One studyof Zairian nurses indicated that they had to“work significantly more, sometimes at doubleeffort, to care for AIDS patients” (Lombela,1996; cited in Kinoti, 2002).

The HIV/AIDS epidemic has placed addi-tional strain on the health care sector and con-tributed to the human resource crisis. But theextent of the impact of HIV/AIDS on thehealth care sector is not fully known. Morecomprehensive country-level assessments ofthe impact are needed.

In 2000, ABT Associates undertook a healthsector assessment in Botswana (using a 25%prevalence rate as baseline) which projectedHIV-related morbidity and mortality amonghealth workers (Figure 9). The model takesinto consideration the demographic profiles ofhealth workers, leading to two estimations,

17

W


non-age adjusted and age adjusted. The non-age adjusted estimation assumes that healthworkers have the same HIV/AIDS prevalenceas the general 20-64 age group population.

As illustrated by Figure 9, 2% to 3% ofhealth workers had AIDS in 2001. Assumingno interventions are taken to reverse the epi-demic, 6% to 9% of health workers will be liv-

ing with HIV/AIDS by 2010. The Abt healthsector assessment also showed that the project-ed cumulative AIDS deaths in Botswanaamong health workers will increase from 5%of current health workforce in 2000 to about17% by 2005 and 40% of current healthworkforce by 2010.

40%

16%

17%

9%

6%

5%7% HIV Absenteeism

AIDS Absenteeism

Burial

Recruitment

Funeral

Health Care

Training

Figure 8: Distribution of Increased Labor Costs due to HIV/AIDS in Zimbabwe

Source: Whiteside and Sunter, XXXX.

0123456789

10

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

Perc

ent

Not age adjusted Age adjusted

Figure 9: Projected Health Workers with AIDS in Botswana (2000 to 2010)

Source: ABT Associates, 2000.

Impact of HIV/AIDS on the Health Sector 19

Box 4: Impact of HIV/AIDS on Kenya’s Health Workforce

Since the first HIV/AIDS case was reported in Kenya in 1984, a total of 1.75 million adultshave been infected. The current prevalence rate of HIV/AIDS is at 9.4%. Assuming a similarinfection rate, 3,500 health workers in Kenya are infected by HIV. The disease caused about55,000 deaths, mainly among young people, including health workers.

A recent study of the impact of HIV/AIDS on the health workforce in Kenya collected datafrom 6 sampled hospitals between 1996 to 2002. The study shows that HIV/AIDS caused anincreased demand for health services. Between 1996 and 2002 there has been a 40% increasein total admissions due to HIV/AIDS. Bed occupancy by HIV related illness is high and is asso-ciated with long stays and frequent re-admissions. Overall, fifty percent of the Medical wards’patients are admitted with HIV/AIDS related illness.

Kenya recently introduced VCT and PMTCT and rapidly scaled up these interventions usingthe existing health workforce. There are strong indicators of overload among the serviceproviders. Ideally a counselor is expected to have an average of 160 clients per month. Thestudy showed that, among the sampled hospitals, each VCT provider had 349 clients, whileeach PMTCT provider had 560 clients per month. Current staffing levels are not adequate tocope with the workload for HIV/AIDS and other services.

Among the sampled facilities, there is a trend toward death becoming the primary reasonfor health personnel attrition (Figure 1). Of the 170 deaths with record of cause, 45% are dueto AIDS related illnesses (pneumonia, tuberculosis, chronic diarrhea and immunosuppression).Further, these deaths occur predominantly among relatively young people (age 15 to 49).

Figure 1: Cause of Health Personnel Attrition

Source: Cheluget, Ngare, Wahiu, et al, 2003.

31.427.7

20.2

13.7

6.30

5

10

15

20

25

30

35

Death Voluntary/Retrechment

Resignation Dismissal Others

Perc

enta

ge

CHAPTER 8

Achieving the Millennium Development Goals

n 2003, Kurowski et al. undertook casestudies of Tanzania and Chad to lookat the ‘role and importance’ of humanresources for scaling up health services

in low-income countries. This study examinedthe size, structure, and compositions of thehealth workforces; and estimated futurehuman resource availability and requirementsfor scaling up priority interventions, as recom-mended by the Commission on Macroeconom-ics and Health.

The study indicates that future staff avail-ability is grossly insufficient for the scaling upof priority interventions, accounting for only40% and 20% of requirements in Tanzaniaand Chad, respectively, by 2015. Shortages arelikely to be greater than indicated, since thetotal health workforce would not be availablefor the provision of priority interventions.Even if training capacities would be immedi-

ately increased by 50%, the 2015 workforcewould constitute only 45% and 25% of totalhuman resource requirements. In Figure 14,Kurowski et al. estimate the shortage of healthworkers for all low and lower-middle incomecountries in SSA.

The study also identified four priority issuesfor scaling up, which merit further research: 1)geographical imbalances must be better under-stood and overcome; 2) more needs to beknown about health staff attrition rates—espe-cially due to emigration—which has implica-tions for training; 3) how can staff productivi-ty (estimated at approximately 50% to 65%)be improved through better staff management;and 4) alternative service delivery mechanismsneed to be developed. Finally, the authorsurged decades-long international commitmentto scaling up, to ensure that the efforts madeare not wasted.

20

I

Achieving the Millennium Development Goals 21

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000N

umbe

rs o

f Hea

lth

Pers

onne

l

Physicians Nurses

HR Availability HR Requirements

Figure 10: Estimates of Shortages of Health Workers in SSA

Source: Kurowski, 2003.

CHAPTER 9

Conclusion

iven the crisis of human resources inthe health sector of sub-SaharanAfrica outlined in this paper, thehealth-related MDGs are arguably

difficult targets for most African countries toattain. However, MDGs are useful in high-lighting underlying problems or constraintshindering their attainment.

Some of the key issues that African govern-ments and development partners should focuson, to address this human resource crisis,include:

• Instituting a consultative process in whichall stakeholders collectively developstrategies to address the crisis facing thehealth workforce.

• Recognizing the importance to alignhealth sector, civil service and macroeco-nomic policies and their objectives toimprove the health workforce (and healthsector) performance.

• Acknowledging that African countriesmust offer internally competitive wagesand benefit packages to retain highlytrained staff; this includes increasing com-pensation so that workers receive a living

wage, and do not have to seek outsideemployment or under-the-table paymentsfor services to survive.

• Investing into training capacities, in par-ticular training that is specifically orient-ed to the needs of national markets tostem brain drain.

• Improving training and knowledgeregarding HIV/AIDS to decrease risk forworkers, address fears and misconcep-tions, and improve patient care.12

• Investing into HIV/AIDS prevention andcare to mitigate the impact of the epidem-ic on the demand for health services andto prevent any further depletion of theworkforce.

• Exploiting alternative service deliverymechanisms (community based, syn-dromic approaches) to reduce the work-load of health personnel.

• Improving the non-monetary incentiveframework faced by health personnel (e.g.continuous training, supervision, appro-priate equipment) to improve motivation

22

G

Conclusion 23

and thus the productivity and quality ofthe health workforce.

The limited availability of human resourcesin Africa is likely to singularly determine the

pace of scaling-up services and to limit thecapacity to absorb additional financialresources. More importantly, it is likely to bethe most significant impediment towards theattainment of the health related MDGs.

Annex

Table 3: WHO Estimates of Health Personnel per 100,000 Population for SSA

Country Physicians1 Nurses1 Midwives2 Pharmacists2

Algeria 85.0 300.0 NA NAAngola 5.0 114.0 4.3 NABenin 10.0 20.0 7.9 NABotswana 28.7 241.0 0.0 NABurkina Faso 4.0 26.0 3.4 NA

Burundi 0.5 1.0 NA NACameroon 7.4 36.7 0.5 NACape Verde 17.1 55.8 NA NACAR 3.5 8.8 4.9 NAChad 2.5 15.0 2.3 NA

Congo 25.1 185.1 24.9 NACôte d’Ivoire 6.8 44.1 15.0 NADR Congo 9.0 31.2 NA NADjibouti 13.0 64.0 NA 2.0Egypt 218.0 284.0 NA 56.0

Eritrea 5.1 21.0 2.2 NAEthiopia 3.0 6.0 NA NAGambia 3.5 12.5 8.2 NAGhana 9.0 64.0 53.2 NAGuinea 13.0 55.7 5.2 NA

Guinea-Bissau 16.6 109.3 12.7 NAKenya 14.1 108.0 NA NALesotho 7.0 33.0 47.0 NALiberia 2.3 5.8 4.3 NALibya 120.0 360.0 NA 23.0

Madagascar 8.7 18.8 10.7 NAMali 4.4 12.6 3.0 NAMauritania 13.8 62.4 10.1 NAMauritius 85.0 232.9 NA NA

24

Annex 25


Morocco 49.0 101.0 NA 11.0

Mozambique 2.4 20.5 NA NANamibia 29.1 165.8 116.5 NANiger 3.3 23.1 5.5 NANigeria 26.9 66.2 52.4 NASao Tome and Principe 46.7 127.4 29.6 NA

Senegal 10.0 50.0 6.6 NASeychelles 132.4 467.6 394.6 NASierra Leone 8.8 90.7 4.7 NASomalia 4.0 20.0 NA 0.1South Africa 25.1 140.0 NA NA

Sudan 16.0 86.0 NA 1.1Swaziland 15.1 40.0 NA NATanzania 4.1 85.2 44.8 NATogo 5.6 16.7 10.4 NATunisia 70.0 286.0 NA 17.0

Uganda 4.7 5.6 13.6 NAZambia 6.9 113.1 NA NAZimbabwe 5.7 54.1 28.1 NAAfrica Region Average 25.1 93.5 30.9 NA1 Source: WHO 20032 Source: WHO Statistical Information Service. Figures are from one year between 1994-1998, with the exception of Nigeria for which figures arefrom 1992. May be accessed at http://www3.who.int/whosis.


Table 4: WHO Estimates of Health Personnel per 100,000 Population, Averages


Sub-Saharan Africa Average 15.5 73.4 30.9 1.1SSA without South Africa Average 15.2 71.8 30.9 1.1North African Average3 108.4 266.2 NA 26.8Four Emerging Countries:India 51.2 62.9 NA NAKorea 180.0 341.0 NA NASingapore 140.0 421.1 NA NAViet Nam 53.8 56.6 17.6 NAFour Emerging Countries’ Average 106.3 220.4 NA NAIndustrialized Countries:Australia 247.4 769.5 40.0 NACanada 187.0 748.0 NA NAFrance 329.7 668.6 21.7 100.0Germany 363.2 954.8 11.3 57.7Italy 606.5 446.5 29.2 102.0Japan 201.5 821.3 18.9 NARussia 420.4 793.0 62.5 6.2UK 164.0 497.0 43.3 58.2USA 279.0 939.0 NA NAIndustrialized Countries’ Average 311.0 737.5 32.4 64.8

1 Source: WHO 20032 Source: WHO Statistical Information Service. Figures are from one year between 1994 and 1998, with the exception of India for which figuresare from 1992. May be accessed at http://www3.who.int/whosis.3 Algeria, Egypt, Libya, Morocco, and Tunisia

Table 5: Trends in Physicians 1960-19981,2

Country 1960 1975/77 1988/92 1992/98 2002

Burkina Faso 1.7 1.8 3.0 3.4 4.0Cameroon 2.5 6.1 8.0 7.4 7.4CAR 2.8 5.7 4.0 3.5 3.5Ghana 8.2 10.0 4.0 6.2 9.0India 17.2 27.6 41.0 48.0 51.2Kenya 9.5 8.4 14.0 13.2 14.1Madagascar 10.4 9.8 12.0 10.7 8.7Morocco 10.6 9.9 21.0 46.0 49.0Tanzania 4.8 6.5 3.0 4.1 4.1Tunisia 10.0 20.8 53.0 70.0 70.0Zambia 8.3 9.8 9.0 6.9 6.91 Measured as physicians per 100,000 population. Figures are from an individual year within the given period.2 Annual statistics from the World Bank and WHO. See: World Bank. 1978 and 1980. World Development Report: World Development Indicators;World Bank. 1993. World Development Report: Investing in Health. p. 208; and WHO. 1998. WHOSIS database. Available athttp://www3.who.int/whosis.

Annex 27

Table 6: Trends in Nurses 1960-19981,2

Country 1960 1975/77 1988/92 1992/98 2002

Burkina Faso 1.7 1.8 3.0 3.4 4.0Cameroon 2.5 6.1 8.0 7.4 7.4CAR 2.8 5.7 4.0 3.5 3.5Ghana 8.2 10.0 4.0 6.2 9.0India 17.2 27.6 41.0 48.0 51.2Kenya 9.5 8.4 14.0 13.2 14.1Madagascar 10.4 9.8 12.0 10.7 8.7Morocco 10.6 9.9 21.0 46.0 49.0Tanzania 4.8 6.5 3.0 4.1 4.1Tunisia 10.0 20.8 53.0 70.0 70.0Zambia 8.3 9.8 9.0 6.9 6.91 Measured as nurses per 100,000 population. Figures are from an individual year within the given period.2 Annual statistics from the World Bank and WHO. See: World Bank. 1978 and 1980. World Development Report: World Development Indicators;World Bank. 1993. World Development Report: Investing in Health. p. 208; and WHO. 1998. WHOSIS database. Available athttp://www3.who.int/whosis.


Tabl

e 7:

Hea

lth P

erso

nnel

Sta

tistic

al D

atab

ase

IMR

Phys

icia

ns

Nur

ses

Mid

wiv

esDe

ntis

tsPh

arm

acis

ts

GDP

Inco

me

Popu

latio

n IM

R 20

00-

per 1

00,0

00

per 1

00,0

00pe

r 100

,000

pe

r 100

,000

pe

r 100

,000

(2

002)

leve

l1Re

gion

2(2

002)

1990

2002

(199

5-19

99)

Year

(199

5-19

99)

Year

(199

5-19

99)

Year

(199

5-19

99)

Year

(199

5-19

99)

Year

Afgh

anis

tan

13

27,9

63,0

0016

716

511

1997

1819

971

1997

219

97Al

bani

a$1

,071

24

3,19

5,10

037

2312

919

9838

019

9859

.119

9431

.519

9640

.619

94Al

geria

$1,6

572

531

,320

,000

4239

84.6

1995

297.

819

95…

…28

.219

95…

…Am

eric

an S

amoa

70,0

000

Ando

rra

54

70,0

000

625

319

9828

319

989.

419

9853

.119

9889

.119

98An

gola

$598

11

13,8

96,0

0016

615

47.

719

9711

4.5

1997

4.3

1997

019

97…

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tigua

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arbu

da$9

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56

68,8

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1211

3.6

1996

330.

319

96…

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637

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2516

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419

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97…

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men

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24

3,07

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9848

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56

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Aust

ralia

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801

42

19,5

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9883

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1998

4019

98…

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stria

$33,

480

44

8,14

0,90

08

530

219

9853

219

9818

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9747

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97Az

erba

ijan

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14

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084

7736

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9876

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9813

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9827

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9833

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98

Baha

mas

$13,

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56

313,

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2413

151.

819

9622

9.7

1996

……

25.4

1996

……

Bahr

ain

$11,

070

55

671,

970

1513

100

1997

283

1997

919

9720

1997

Bang

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sh$3

961

313

5,68

0,00

096

5120

1997

1119

97…

……

……

…Ba

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56

269,

380

1412

125.

419

9333

0.3

1993

……

16.1

1993

……

Bela

rus

$1,5

792

49,

930,

800

1817

443

1998

1182

1998

67.6

1998

40.6

1998

30.7

1998

Belg

ium

$31,

333

44

10,3

20,0

008

539

519

9810

7519

9665

1996

68.2

1998

145

1998

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36

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330

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54.8

1996

8219

96…

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96…

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nin

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11

6,60

3,40

011

194

5.7

1995

20.4

1995

7.9

1995

0.3

1995

……

Berm

uda

56

60,0

000

Bhut

an$5

801

385

0,82

00

7416

1995

3919

9556

1995

……

……

Boliv

ia$9

472

68,

697,

100

8760

129.

919

9769

.419

97…

…21

.119

97…

…Bo

snia

&He

rzeg

ovin

a$1

,671

24

4,12

0,60

018

1514

319

9845

219

9835

.819

9119

1998

1119

98Bo

tsw

ana

$4,2

333

11,

711,

800

4580

23.8

1994

219.

119

940

1994

2.2

1994

……

Braz

il$4

,644

26

174,

490,

000

5031

127.

219

9641

.319

96…

…85

.119

96…

…Br

unei

$17,

650

52

350,

630

106

84.8

1996

401.

519

96…

…12

.819

96…

…Bu

lgar

ia$1

,733

24

7,86

8,00

015

1434

519

9871

319

9870

.619

9858

.619

9818

.519

98Bu

rkin

a Fa

so$2

581

111

,831

,000

118

104

3.4

1995

19.6

1995

3.4

1995

0.3

1995

……

Buru

ndi

$143

11

7,07

1,00

011

411

4…

……

……

……

……

…

Annex 29

IMR

Phys

icia

ns

Nur

ses

Mid

wiv

esDe

ntis

tsPh

arm

acis

ts

GDP

Inco

me

Popu

latio

n IM

R 20

00-

per 1

00,0

00

per 1

00,0

00pe

r 100

,000

pe

r 100

,000

pe

r 100

,000

(2

002)

leve

l1Re

gion

2(2

002)

1990

2002

(199

5-19

99)

Year

(199

5-19

99)

Year

(199

5-19

99)

Year

(199

5-19

99)

Year

(199

5-19

99)

Year

Cam

bodi

a$3

251

212

,487

,000

8097

29.7

1998

73.8

1998

28.8

1998

1.8

1998

……

Cam

eroo

n$7

111

115

,523

,000

8596

7.4

1996

36.7

1996

0.5

1996

0.4

1996

……

Cana

da$2

3,59

04

631

,414

,000

75

229.

119

9589

7.1

1996

……

58.6

1997

……

Cape

Ver

de$1

,571

21

458,

030

4529

17.1

1996

55.6

1996

……

1.5

1996

……

Caym

an Is

land

s5

635

,000

0Ce

ntra

l Afri

can

Repu

blic

$348

11

3,82

8,00

011

511

53.

519

958.

819

954.

919

950.

219

95…

…Ch

ad$2

481

18,

144,

400

118

117

3.3

1994

14.7

1994

2.3

1994

0.2

1994

……

Chan

nel I

slan

ds5

414

9,00

07

6Ch

ile$5

,436

36

15,5

79,0

0016

1011

0.3

1994

47.2

1996

……

41.5

1996

……

Chin

a$9

422

21,

281,

000,

000

3831

161.

719

9898

.619

983.

919

98…

……

…Co

lom

bia

$2,2

742

643

,745

,000

2919

116

1997

48.3

1994

……

40.3

1994

……

Com

oros

$436

11

585,

940

8859

7.4

1997

34.1

1997

1419

9714

1997

……

Cong

o, D

em. R

ep.

$87

11

53,7

97,0

0012

812

96.

919

9644

.219

96…

…1.

119

96…

…Co

ngo,

Rep

$87

11

53,7

97,0

0012

812

925

.119

9518

5.1

1995

24.9

1995

……

……

Cook

Isla

nds

$00

8381

9019

9720

019

9730

1997

9019

97…

…Co

sta

Rica

$3,9

273

63,

941,

800

150

141.

119

9710

9.1

1997

……

39.4

1997

……

Côte

d'Iv

oire

$712

11

16,7

75,0

0010

010

29

1996

31.2

1996

1519

96…

……

…Cr

oatia

$5,5

493

44,

376,

900

117

229

1998

474

1998

3319

9865

.719

9845

.519

98Cu

ba2

611

,263

,000

117

530.

419

9767

7.6

1997

……

84.5

1997

……

Cypr

us$1

4,80

05

476

4,97

011

525

519

9644

719

9665

1995

104

1995

Czec

h Re

publ

ic$5

,691

34

10,2

10,0

0011

430

319

9888

619

9844

.719

9862

1998

44.3

1998

Denm

ark

$39,

211

44

5,37

3,30

08

429

019

9472

219

9421

.119

9788

.619

9518

.219

94Dj

ibou

ti$7

752

565

6,51

011

910

014

1996

7419

961.

719

962

1996

Dom

inic

a$3

,157

36

71,8

0019

1449

.319

9641

5.5

1996

……

5.6

1996

……

Dom

inic

an R

epub

lic$2

,129

26

8,63

4,70

053

4121

5.6

1997

29.9

1997

……

23.4

1997

……

Ecua

dor

$17,

046

26

13,1

12,0

0043

2416

9.6

1997

70.1

1997

……

63.9

1997

……

Egyp

t, Ar

ab R

ep.

$1,2

502

566

,372

,000

7635

202

1996

233

1996

2519

9656

1996

El S

alva

dor

$1,7

632

66,

523,

900

4633

107.

119

9734

.919

97…

…35

.619

97…

…Eq

uato

rial G

uine

a$1

,541

11

481,

420

122

101

24.6

1996

39.5

1996

2.2

1996

119

96…

…Er

itrea

$166

11

4,30

8,80

092

723

1996

1619

962.

219

960.

119

96…

…Es

toni

a$5

,000

34

1,35

8,00

012

1129

719

9862

519

9837

.419

9867

.919

9853

.519

98(c

ontin

ued

non

next

pag

e))


Tabl

e 7

(con

tinue

d)

IMR

Phys

icia

ns

Nur

ses

Mid

wiv

esDe

ntis

tsPh

arm

acis

ts

GDP

Inco

me

Popu

latio

n IM

R 20

00-

per 1

00,0

00

per 1

00,0

00pe

r 100

,000

pe

r 100

,000

pe

r 100

,000

(2

002)

leve

l1Re

gion

2(2

002)

1990

2002

(199

5-19

99)

Year

(199

5-19

99)

Year

(199

5-19

99)

Year

(199

5-19

99)

Year

(199

5-19

99)

Year

Ethi

opia

$124

11

67,3

35,0

0012

811

6…

……

……

……

……

…

Faer

oe Is

land

s5

450

,000

0Fi

ji$2

,910

22

823,

300

2518

47.6

1997

195.

119

97…

…4.

319

97…

…Fi

nlan

d$3

2,57

54

45,

199,

000

64

299

1998

2162

1998

7819

9893

.719

9814

519

98Fr

ance

$30,

667

44

59,4

42,0

007

430

319

9749

719

9621

.719

9667

.819

9610

019

97Fr

ench

Pol

ynes

ia$1

9,89

55

223

9,80

018

10

Gabo

n$4

,405

31

1,29

0,60

060

60…

……

……

……

……

…Ga

mbi

a, T

he$3

701

11,

375,

700

103

913.

519

9712

.519

978.

219

970.

519

97…

…Ge

orgi

a$5

371

45,

177,

000

2424

436

1998

474

1998

31.1

1998

35.3

1998

9.2

1998

Germ

any

$32,

807

44

82,4

95,0

007

435

019

9895

719

9811

.319

9775

.919

9857

.719

98Gh

ana

$432

11

20,0

71,0

0074

576.

219

9672

1996

53.2

1996

0.2

1996

……

Gree

ce$1

4,15

74

410

,631

,000

105

392

1995

257

1992

18.5

1993

102

1995

69.2

1988

Gren

ada

$3,5

163

610

1,71

030

2049

.519

9736

7.7

1997

……

8.6

1997

……

Guam

52

159,

350

96

Guat

emal

a$1

,545

26

11,9

92,0

0060

4393

.319

9727

1997

……

1319

97…

…Gu

inea

$628

11

7,74

4,40

014

510

913

1995

55.7

1995

5.2

1995

……

……

Guin

ea-B

issa

u$1

931

11,

252,

700

153

130

16.6

1996

109.

419

9612

.719

960.

919

96…

…Gu

yana

$938

26

771,

970

6554

18.1

1997

84.2

1997

……

3.8

1997

……

Haiti

$344

16

8,28

6,50

010

279

8.4

1992

10.7

1997

……

1.2

1992

……

Hond

uras

$711

26

6,75

5,10

047

3183

.219

9725

.519

97…

…16

.819

97…

…Hu

ngar

y$5

,735

34

10,1

66,0

0015

835

719

9838

519

9818

.619

9842

.419

9847

.319

98

Icel

and

$31,

835

44

283,

990

63

326

1997

865

1998

85.9

1998

105

1997

83.1

1997

Indi

a$4

941

31,

048,

300,

000

8067

4819

9245

1992

……

……

……

Indo

nesi

a$1

,060

12

211,

720,

000

6033

1619

9450

1994

2619

94…

……

…Ira

n, Is

lam

ic R

ep.

$1,7

872

565

,540

,000

5435

8519

9625

919

9616

1996

1119

96Ira

q2

524

,256

,000

4010

755

1998

236

1995

5.7

1998

11.8

1998

Irela

nd$3

0,15

74

43,

877,

600

86

219

1998

1593

1998

411

1998

46.2

1998

77.8

1998

Isra

el$1

7,06

75

56,

494,

200

106

385

1998

613

1998

18.6

1998

116

1998

60.5

1998

Italy

$21,

233

44

57,9

19,0

008

455

419

9729

619

8929

.219

8264

.419

9710

219

96

Annex 31

IMR

Phys

icia

ns

Nur

ses

Mid

wiv

esDe

ntis

tsPh

arm

acis

ts

GDP

Inco

me

Popu

latio

n IM

R 20

00-

per 1

00,0

00

per 1

00,0

00pe

r 100

,000

pe

r 100

,000

pe

r 100

,000

(2

002)

leve

l1Re

gion

2(2

002)

1990

2002

(199

5-19

99)

Year

(199

5-19

99)

Year

(199

5-19

99)

Year

(199

5-19

99)

Year

(199

5-19

99)

Year

Jam

aica

$2,1

742

62,

612,

900

1717

140.

119

9664

.519

96…

…9

1994

……

Japa

n$4

4,10

84

412

7,14

0,00

05

319

3.2

1996

744.

919

9618

.919

9668

.619

96…

…Jo

rdan

$1,6

612

55,

171,

300

3527

166

1997

296

1997

4919

9777

1997

Kaza

khst

an$1

,893

24

14,7

95,0

0042

8135

319

9864

919

9856

.119

9825

.119

9865

.719

94Ke

nya

$325

11

31,3

45,0

0063

7813

.219

9590

.119

95…

…2.

219

95…

…Ki

ribat

i$5

752

294

,700

6551

29.6

1998

235.

819

98…

…4.

919

98…

…Ko

rea,

Dem

. Rep

.1

222

,519

,000

2642

297

1995

180

1995

6019

95…

……

…Ko

rea,

Rep

.$1

4,28

04

247

,640

,000

85

136.

119

9729

1.2

1997

……

33.4

1997

……

Kuw

ait

$13,

345

55

2,10

3,90

014

918

919

9747

519

9726

1997

3519

96Ky

rgyz

Rep

.$1

3,34

51

42,

103,

900

149

301

1998

750

1998

72.8

1998

27.4

1998

6.7

1998

Lao,

PDR

$477

12

5,53

0,10

012

087

24.3

1996

107.

719

96…

…4.

319

96…

…La

tvia

$3,1

003

42,

335,

000

1417

282

1998

549

1998

33.2

1998

43.5

1998

……

Leba

non

$2,8

683

54,

441,

200

3228

210

1997

100

1997

8019

9750

1997

Leso

tho

$577

11

2,08

6,70

010

291

5.4

1995

60.1

1995

4719

950.

519

95…

…Li

beria

$199

11

3,29

5,10

015

715

72.

319

975.

919

974.

319

970.

119

97…

…Li

bya

35

5,53

3,90

034

1612

819

9736

019

9613

1996

2319

96Li

thua

nia

$2,6

593

43,

476,

000

108

395

1998

884

1998

43.5

1998

6119

9857

.819

98Lu

xem

bour

g$5

6,51

34

444

3,50

07

527

219

9878

219

9821

.919

9865

.819

9869

.419

98

Mac

edon

ia, F

YR$2

,418

24

2,03

8,00

032

2220

419

9848

819

9866

.619

9851

.919

9814

.919

98M

adag

asca

r$2

171

116

,437

,000

103

8410

.719

9621

.619

9610

.719

961

1996

……

Mal

awi

$162

11

10,7

43,0

0014

611

4…

……

……

……

……

…M

alay

sia

$4,8

113

224

,305

,000

168

65.8

1997

113.

319

9727

.119

978.

619

97…

…M

aldi

ves

$1,9

902

328

6,68

080

5840

1995

113

1995

185

1995

……

……

Mal

i$3

131

111

,346

,000

152

141

4.7

1994

13.1

1994

319

940.

119

94…

…M

alta

$10,

098

55

397,

000

95

261

1998

1100

1993

77.1

1993

35.8

1998

49.3

1998

Mar

shal

l Isl

ands

$1,5

542

253

,200

6354

42.2

1996

148.

819

9610

.119

965.

119

96…

…M

aurit

ania

$513

11

2,82

8,00

012

012

013

.819

9562

.419

9510

.119

952

1995

……

Mau

ritiu

s$4

,537

31

1,21

2,40

021

1785

1995

232.

919

95…

…13

.519

95…

…M

exic

o$3

,713

36

100,

920,

000

3724

186.

419

9086

.519

95…

…65

.919

90…

…M

icro

nesi

a Fe

d. S

ts.

$3,7

132

210

0,92

0,00

037

2457

.319

9927

919

990.

819

9912

.219

99…

…(c

ontin

ued

on n

ext p

age)


Tabl

e 7

(con

tinue

d)

IMR

Phys

icia

ns

Nur

ses

Mid

wiv

esDe

ntis

tsPh

arm

acis

ts

GDP

Inco

me

Popu

latio

n IM

R 20

00-

per 1

00,0

00

per 1

00,0

00pe

r 100

,000

pe

r 100

,000

pe

r 100

,000

(2

002)

leve

l1Re

gion

2(2

002)

1990

2002

(199

5-19

99)

Year

(199

5-19

99)

Year

(199

5-19

99)

Year

(199

5-19

99)

Year

(199

5-19

99)

Year

Mol

dova

, Rep

.$7

291

44,

255,

000

3027

350

1998

874

1998

87.1

1998

41.2

1998

67.5

1994

Mon

aco

54

30,0

000

066

419

9516

2119

9535

.719

9512

119

9521

819

95M

ongo

lia$4

401

22,

448,

500

7761

243.

319

9830

7.3

1998

……

13.5

1998

……

Mor

occo

$1,4

761

529

,641

,000

6639

4619

9710

519

974

1997

1119

96M

ozam

biqu

e$2

291

118

,438

,000

143

125

……

……

……

……

……

Mya

nmar

12

48,8

95,0

0091

7729

.719

9926

.119

9922

.119

992.

119

99…

…

Nam

ibia

$2,4

122

11,

823,

200

6555

29.5

1997

168

1997

116.

519

974

1997

……

Nau

ru3

$00

6555

157

1995

588

1995

……

……

……

Nep

al$2

411

324

,122

,000

100

04

1995

519

957.

419

95…

……

…N

ethe

rland

s$3

1,16

04

416

,144

,000

75

251

1990

902

1991

9.1

1997

47.1

1996

17.4

1997

New

Zea

land

$19,

024

44

3,86

9,60

08

621

7.5

1997

771

1997

56.2

1997

3919

97…

…N

icar

agua

$437

16

5,33

4,90

052

3685

.619

9791

.919

97…

…18

.619

97…

…N

iger

$207

11

11,5

42,0

0019

115

63.

519

9722

.919

975.

519

970.

219

97…

…N

iger

ia$2

481

113

2,78

0,00

011

411

018

.519

9266

.119

9252

.419

922.

619

92…

…N

iue3

$00

114

110

130.

419

9647

8.3

1996

8719

9687

1996

……

Nor

way

$38,

843

44

4,53

8,70

07

441

319

9818

4019

9859

.119

9811

819

9857

.119

98

Oman

$6,2

773

52,

539,

400

2512

133

1998

325

1998

919

9819

1998

Paki

stan

$527

13

144,

900,

000

9684

5719

9734

1996

2.3

1997

3419

96Pa

lau

$5,4

353

219

,900

024

110.

419

9814

419

985.

619

9811

1998

……

Pana

ma

$3,8

392

62,

940,

400

2719

166.

819

9514

4.1

1997

……

83.8

1997

……

Papu

a N

ew G

uine

a$8

561

25,

373,

300

7970

7.3

1998

6719

98…

…2.

719

98…

…Pa

ragu

ay$1

,703

26

5,51

0,00

030

2610

9.8

1997

23.9

1997

……

22.8

1997

……

Peru

$2,4

042

626

,749

,000

5830

93.2

1997

115.

219

97…

…39

.619

97…

…Ph

ilipp

ines

$1,1

952

279

,944

,000

4529

123

1996

418

1996

163

1996

5219

96…

…Po

land

$3,7

623

438

,626

,000

198

236

1997

527

1990

64.3

1997

45.6

1997

53.5

1997

Portu

gal

$13,

151

44

10,0

32,0

0011

531

219

9837

919

988.

319

8433

.319

9875

.319

98

Qata

r5

561

0,49

019

1112

619

9628

919

9621

1996

5119

96

Rom

ania

$1,6

112

422

,355

,000

2719

184

1998

409

1998

39.6

1998

23.9

1998

7.3

1998

Russ

ian

Fede

ratio

n$2

,734

24

144,

070,

000

1718

421

1998

821

1998

62.5

1998

32.2

1998

6.2

1998

Annex 33

IMR

Phys

icia

ns

Nur

ses

Mid

wiv

esDe

ntis

tsPh

arm

acis

ts

GDP

Inco

me

Popu

latio

n IM

R 20

00-

per 1

00,0

00

per 1

00,0

00pe

r 100

,000

pe

r 100

,000

pe

r 100

,000

(2

002)

leve

l1Re

gion

2(2

002)

1990

2002

(199

5-19

99)

Year

(199

5-19

99)

Year

(199

5-19

99)

Year

(199

5-19

99)

Year

(199

5-19

99)

Year

Rwan

da$2

951

18,

163,

000

107

96…

……

……

……

……

…

Sam

oa$1

,491

22

176,

200

3320

34.4

1996

155

1996

3619

964

1996

……

San

Mar

ino

54

30,0

000

425

219

9050

819

9026

1990

36.4

1984

52.1

1990

Sao

Tom

e &

Prin

cipe

$347

11

154,

210

6957

46.7

1996

127.

419

9629

.619

965.

219

96…

…Sa

udi A

rabi

a$6

,614

35

22,1

16,0

0034

2316

619

9733

019

9716

1997

2119

97Se

nega

l$6

281

110

,007

,000

9079

7.5

1995

22.1

1995

6.6

1995

1.2

1995

……

Seyc

helle

s$5

,715

31

83,5

9017

1313

2.4

1996

467.

619

9639

4.6

1996

12.2

1996

……

Sier

ra L

eone

$165

11

5,23

5,50

018

518

27.

319

9633

1996

4.7

1996

0.4

1996

……

Sing

apor

e$2

7,25

45

24,

164,

000

73

162.

719

9849

2.1

1998

……

28.9

1998

……

Slov

ak R

ep.

$27,

254

34

4,16

4,00

07

335

319

9870

819

9539

.319

9548

.219

9833

.819

98Sl

oven

ia$1

2,32

65

41,

992,

000

84

228

1998

681

1998

32.7

1990

60.8

1998

36.3

1998

Solo

mon

Isla

nds

$527

12

443,

300

2920

1419

9511

919

95…

…7

1995

……

Som

alia

11

9,39

0,80

013

313

34

1997

2019

970.

219

970.

119

97So

uth

Afric

a$4

,183

21

43,5

80,0

0045

5656

.319

9647

1.8

1996

……

17.8

1996

……

Spai

n$1

7,88

54

441

,180

,000

84

424

1997

458

1997

16.2

1988

38.5

1997

113

1997

Sri L

anka

$891

23

18,9

68,0

0019

1736

.519

9910

2.7

1999

41.9

1999

2.5

1999

4.5

1999

St. K

itts

& N

evis

$6,1

253

645

,980

3020

117.

119

9749

7.6

1997

……

19.5

1997

……

St. L

ucia

$3,7

093

615

8,52

019

1747

.319

9726

319

97…

…6.

219

97…

…St

. Vin

cent

&

the

Gren

adin

es$2

,471

26

116,

720

2122

87.7

1997

238.

619

97…

…5.

319

97…

…Su

dan

$356

11

32,3

65,0

0075

659

1996

5819

960.

719

961.

119

96Su

rinam

e$1

,057

26

422,

570

3526

25.2

1996

156.

319

96…

…0.

919

96…

…Sw

azila

nd$1

,528

21

1,08

8,20

077

106

15.1

1996

……

……

……

……

Swed

en$3

2,11

74

48,

924,

000

63

311

1997

821

1997

71.8

1991

152

1997

67.3

1998

Switz

erla

nd$4

6,99

34

47,

227,

500

75

323

1998

779

1990

26.5

1990

48.8

1997

61.5

1998

Syria

n Ar

ab R

ep.

$801

25

17,0

05,0

0037

2314

419

9818

919

9874

1998

5319

98

Tajik

ista

n$4

531

46,

315,

700

980

201

1998

484

1998

65.4

1998

18.4

1998

1219

98Ta

nzan

ia$2

041

135

,181

,000

102

104

4.1

1995

85.2

1995

44.8

1995

0.7

1995

……

Thai

land

$2,9

862

261

,613

,000

3424

2419

9587

1995

……

……

……

Tim

or-L

este

753,

000

085

Togo

$324

11

4,76

6,60

088

797.

619

9529

.719

9510

.419

950.

719

95…

…(c

ontin

ued

on n

ext p

age)


Tabl

e 7

(con

tinue

d)

IMR

Phys

icia

ns

Nur

ses

Mid

wiv

esDe

ntis

tsPh

arm

acis

ts

GDP

Inco

me

Popu

latio

n IM

R 20

00-

per 1

00,0

00

per 1

00,0

00pe

r 100

,000

pe

r 100

,000

pe

r 100

,000

(2

002)

leve

l1Re

gion

2(2

002)

1990

2002

(199

5-19

99)

Year

(199

5-19

99)

Year

(199

5-19

99)

Year

(199

5-19

99)

Year

(199

5-19

99)

Year

Tong

a$1

,750

22

101,

160

2517

4419

9731

5.1

1997

3119

979.

219

97…

…Tr

inid

ad &

Tob

ago

$5,4

663

61,

318,

300

2117

78.8

1994

286.

819

94…

…8.

419

97…

…Tu

nisi

a$2

,580

25

9,78

8,30

037

2170

1997

286

1997

1319

9717

1997

Turk

ey$2

,942

24

69,6

26,0

0061

3612

119

9810

919

9864

.419

9821

1998

33.6

1998

Turk

men

ista

n$1

,787

24

5,54

5,40

080

6930

019

9758

719

9778

.419

9721

.619

9733

.519

97Tu

valu

3$0

080

6930

1999

300

1999

9019

9910

1999

……

Ugan

da$3

671

123

,395

,000

100

79…

…18

.719

9613

.619

960.

219

96…

…Uk

rain

e$1

,038

24

48,7

17,0

0018

1729

919

9873

619

9858

.719

9839

1998

46.7

1997

Unite

d Ar

ab

Emira

tes

$15,

590

55

3,04

9,20

012

818

119

9734

119

9626

1996

8119

96Un

ited

King

dom

$23,

015

44

58,8

58,0

008

616

419

9349

719

8943

.319

8939

.819

9258

.219

92Un

ited

Stat

es$3

1,97

74

428

8,37

0,00

09

727

919

9597

219

96…

…59

.819

96…

…Ur

ugua

y$5

,463

36

3,38

1,00

020

1437

0.3

1996

7019

96…

…12

6.3

1996

……

Uzbe

kist

an$5

251

425

,391

,000

5352

309

1998

1011

1998

67.5

1998

24.4

1998

3.1

1998

Vanu

atu

$1,1

762

220

5,57

052

3412

1997

260

1997

……

……

……

Vene

zuel

a, R

B$2

,978

36

25,0

93,0

0023

1923

6.3

1997

64.4

1997

……

57.1

1997

……

Viet

Nam

$2,9

781

225

,093

,000

2319

4819

9856

1998

17.6

1998

……

……

Yem

en, R

ep.

$314

15

18,6

01,0

0098

7923

1996

5119

951.

619

964

1996

Zam

bia

$410

11

10,4

61,0

0010

811

26.

919

9511

3.1

1995

……

……

……

Zim

babw

e$5

221

112

,967

,000

5376

13.9

1995

128.

719

9528

.119

951.

319

95…

…

1 Th

e m

easu

re fo

r inc

ome

leve

l, 1,

2, 3

, 4, a

nd 5

cor

resp

onds

to lo

w in

com

e, lo

wer

mid

dle

inco

me,

upp

er m

iddl

e in

com

e, h

igh

inco

me

OECD

, and

hig

h in

com

e no

n-OE

CD c

ount

ries,

resp

ectiv

ely.

2 Th

e m

easu

re fo

r reg

ion,

1, 2

, 3, 4

, and

5 c

orre

spon

ds to

SSA

, EAP

, SA,

ECA

, and

MEN

A co

untri

es, r

espe

ctiv

ely.

3 N

o W

DI d

ata.

Sour

ce: C

ourte

sy o

f Chr

isto

pher

Kur

owsk

i

Annex 35

Table 8: Brain loss in 9 SSA countries, by profession

Country Physicians Nurses and Others

Cameroon 49% of health workers have intention to emigrate (p.47) (Awases, Gbary, and Chatora, 2003).

Ghana 600 Ghanaian medical practitioners are Ghana has lost about 2,500 nurses to Europe practicing in New York. 62% of health workers from 1999 to 2002 according to the president of have intention to emigrate (p.47) (Frimpong, 2002). the nurse association of Ghana (Awases, Gbary,

and Chatora, 2003).604 (70%) out of 604 out of the 871 (70%) medical officers trained between 1993-2002 left the Ghana lost 328 nurses in 1999 which was country (Safo, 2003). equivalent of its annual output (Loewenson and

Thomson, 2002).UNDP notes that in Africa, the loss of physicians has been the most striking. At least 60% of physicians trained in Ghana during the 1980s have left the country (Mutume, 2003).In 1999, 40 of Ghana’s 43 final year medical students planned to leave immediately after graduation, while 70% of its 1995 graduates had already emigrated by 1999 (Loewenson and Thomson, 2002).

Kenya Kenya estimated that only 600 physicians work in public hospitals out of more than 5000 registered. The rest have moved abroad or are working in private sector (Pang, Lansang, and Haines, 2002)

Malawi In 2001, the School of Medicine stated that: Outof a group of 35 RN graduates, some went towork with NGOs and 4 went directly overseas.Four of their teachers also went to work over-seas (p.30) (Martineau et al, 2001).

The Nursing Association reports that in 2001, 100nurses applied for references application towork abroad and 80 have made similar requestup to September 2002 (Hornby, Kathyola, andMartineau, 2002).

Nurses and midwives registering with the UK CC(Loewenson and Thomson, 2002):

1998/1999: 11999/2000: 152000/2001: 45

Senegal 38% of health workers have intention to emigrate (p.47) (Awases, Gbary, and Chatora, 2003).

(continued on next page)


Table 8 (continued)


South Africa 58% of health workers have intention to More than 300 South African specialist nurses emigrate (p.47) (Awases, Gbary, and Chatora, are thought to leave the country every month 2003). (Tettey, 2003).In the past four years(1998-2002), South Africa has 600 of its medical graduates (trained at a Nurses and midwives from South Africa cost of US$ 37 million) registered in New registering with the UK CC (Loewenson and Zealand (Lancet, 2002). Thomson, 2002):

1998/1999: 59910% of Canada’s hospital-based physicians are 1999/2000: 1460South African graduates (Loewenson and 2000/2001: 1086Thomson, 2002).

South Africa medical school suggest that a third to a half of its graduates emigrate to the developed world (Pang, Lansang, and Haines, 2002).

Uganda Uganda produces 150 physicians per annum, Uganda produces 200 registered nurses/estimated migration is 30% for physicians midwives per year, more than 10% of these (Omaswa, 2003). professionals are estimated to migrate

(Omaswa, 2003).Many Ugandan physicians left for more affluent countries. One of South Africa’s medical schools has several senior faculty from Uganda (Bundred and Levitt, 2000).

26% of health workers have intention to emigrate (p.47) (Awases, Gbary, and Chatora, 2003).

Zambia Zambia’s medical school in Lusaka has trained Nurses and midwives from Zambia registering over 600 Zambian medical graduates in its 23 with the UK CC (Loewenson and Thomson, 2002):years, but only 50 work in the Zambia public 1998/1999: 15sector health service now (Bundred and Levitt, 1999/2000: 402000). 2000/2001: 83

The Zambian public health system has retained The principal reason for staff losses is salary, only about 50 of more than 600 physicians with a large number of nurses and midwives trained in the country since independence leaving Zambia for jobs in the UK and the US. (Loewenson and Thomson, 2002). The Zambian government recently increased the

salaries of nurses and midwives, but complaintsthat the salaries remain insufficient even afterthe increase are widespread. Therefore, it is notclear that this recent salary increase willinfluence staff loss rates (Huddart, Lyons, andFurth, 2003).

(conbtinued on next page)

Annex 37


Zimbabwe 68% of health workers have intention to 18,000 Zimbabwean nurses work abroad emigrate (p.47) (Awases, Gbary, and Chatora, (Mangwende, 2002).2003).

Nurses and midwives from Zimbabwe registering About 200 physicians left Zimbabwe for with the UK CC (Loewenson and Thomson, 2002):Botswana and South Africa in 1992. Of 1200 1998/1999: 52Physicians trained in Zimbabwe during the 1999/2000: 2211990s, only 360 were still practicing in the 2000/2001: 1086country in 2001. (= 840 went abroad) (Loewenson and Thomson, 2002).

Non-specific UN Commission for Trade and Development estimated that each migrating African professional rep-resents a loss of US$184,000 to Africa. Paradoxically, Africa spends US$4bn a year on the salariesof 100,000 foreign experts (Seepe, 2001).

Notes

1. In many countries, up to three quarters ofrecurrent health expenditures are used onstaffing costs and wages.

2. At the time of writing, the most currentand comprehensive data available is compiledby the WHO, using a variety of national healthsurveys. More information on this topic can befound in Diallo et al. (2003).

3. Burkina Faso, Burundi, Central AfricanRepublic, Chad, Ethiopia, Gambia, Liberia,Mali, Mozambique, Niger, Somalia, Tanzania,and Uganda.

4. As of 2002, SSA had an estimated popu-lation of 693 million, which is expected toincrease to 1081 million by 2025, (PopulationReference Bureau, World Population DataSheet, 2002).

5. Cameroon, CAR, Ghana, Kenya, Mada-gascar, Tanzania, and Zambia.

6. Burkina Faso, Cameroon, CAR, Ghana,and Madagascar.

7. CREDESS, Paris, 1999 data for IvoryCoast, unpublished.

8. See, for example, the case of Cameroon,Congo, and Cote d’Ivoire.

9. These are attributable to demographicfactors (an aging population which requires

more services, a smaller pool of recruits for thehealth professions), social and cultural factors(more career options available to young peo-ple, particularly to women), work related fac-tors (lower attractiveness of health occupationsperceived as demanding and not well reward-ed).

10. Statistics available for South Africa,Zimbabwe, Nigeria, Ghana, Zambia, Kenya,and Malawi.

11. This is often described as “brain drain”,an expression traditionally used to describe thepermanent emigration of qualified persons.The notion of “brain loss” is more compre-hensive, as it also encompasses losses due topeople leaving the health sector to take otherjobs which reward them better.

12. An example of an interesting and poten-tially effective measure is the InternationalCouncil of Nurses supported Zambian NursesAssociation partnership with the ZambianMinistry of Health in the administration of aprogram to provide free testing and treatmentfor pregnant nurses and other health workers(see ICN, http://www.icn.ch/PR26_03.htm).

38

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