Mapping Selected Human Development Indicators in Sub-Saharan Africa

Abstract

Human development indicators (HDIs) are used in measuring poverty and are diverse, ranging from income distribution, nutritional, health and environmental variables to housing quality among others. This paper is concerned with the spatial variation of selected HDIs in countries of sub-Saharan Africa (SSA). The temporal analysis is used in determining the performance of each country, in terms of an improvement or a decline with respect to a particular indicator of human development. For instance, in assessing the change in a country's per capita Gross National Product (GNP) over a period spanning twenty years, the trend in performance between 1980 -1999 was analysed in a GIS environment and mapped. The resultant patterns of different HDIs will be useful in determining the appropriate line of action to take since these give better insight into the prevailing human development situations at both national and regional levels. Such analysis will invariably be a valuable input into development planning, policy formulation and execution by regional bodies such as the Economic Community of West African States (ECOWAS), Southern African Development Community (SADC) as well as the African Union (AU). A very crucial effort at developing Africa at this instance is the initiative tagged "New Partnership for Africa's Development" (NEPAD) aimed at co-ordinating, harmonising and rationalising the policies and strategies of all African member states for sustainable development. Thus, this paper is an attempt to give a performance picture of various HDIs in SSA and to demonstrate the usefulness of maps as crucial tools for better understanding of human development trend both at national and regional levels in the sub-Saharan African region. In contrast to other regions of the world, SSA is confronted with poverty related problems which are being aggravated by the inability to reposition favourably in the current globalisation process.

Full text

Proceedings of the 21st International Cartographic Conference (ICC) Durban, South Africa, 10 – 16 August 2003
‘Cartographic Renaissance’ Hosted by The International Cartographic Association (ICA)
ISBN: 0-958-46093-0 Produced by: Document Transformation Technologies
MAPPING SELECTED HUMAN DEVELOPMENT INDICATORS
IN SUB-SAHARAN AFRICA
Akinyemi, F.O.
Department of Geography. Obafemi Awolowo University.
Ile-Ife, 220001, Osun State, Nigeria. E-mail: bakin_yem@yahoo.com
ABSTRACT
Human development indicators (HDIs) are used in measuring poverty and are diverse, ranging from income
distribution, nutritional, health and environmental variables to housing quality among others. This paper is concerned
with the spatial variation of selected HDIs in countries of sub-Saharan Africa (SSA). The temporal analysis is used in
determining the performance of each country, in terms of an improvement or a decline with respect to a particular
indicator of human development. For instance, in assessing the change in a country’s per capita Gross National Product
(GNP) over a period spanning twenty years, the trend in performance between 1980 - 1999 was analysed in a GIS
environment and mapped. The resultant patterns of different HDIs will be useful in determining the appropriate line of
action to take since these give better insight into the prevailing human development situations at both national and
regional levels. Such analysis will invariably be a valuable input into development planning, policy formulation and
execution by regional bodies such as the Economic Community of West African States (ECOWAS), Southern African
Development Community (SADC) as well as the African Union (AU). A very crucial effort at developing Africa at this
instance is the initiative tagged “New Partnership for Africa’s Development” (NEPAD) aimed at co-ordinating,
harmonising and rationalising the policies and strategies of all African member states for sustainable development.
Thus, this paper is an attempt to give a performance picture of various HDIs in SSA and to demonstrate the usefulness
of maps as crucial tools for better understanding of human development trend both at national and regional levels in the
sub-Saharan African region. In contrast to other regions of the world, SSA is confronted with poverty related problems
which are being aggravated by the inability to reposition favourably in the current globalisation process.
Keywords: Human development indicators, Poverty, GIS, Sub-Saharan Africa.
1. INTRODUCTION
Africa is the only continent where poverty is on the rise despite the huge human and natural resources. On average,
over forty percent (40%) of Sub-Saharan Africa’s 659 million people live below the international poverty line of US$1
a day (a much higher proportion than in any region of the world except South Asia). At least fifty percent (50%) of the
people below the poverty line are from five East African countries and Nigeria. On the economic front, Africa’s share
of world trade has plummeted, accounting for less than two percent (1).
Currently, access to social services (a principal indicator of poverty) in most SSA countries is the lowest in the world.
More than 140 million young people in Africa are illiterate, and Africa is the only region where the number of children
out of schools is rising. The average gross primary school enrolment rate, which declined in many African countries
during the 1980s, is currently only sixty-seven percent (67%) compared with ninety-four percent (94%) for South Asia
and 117 percent for East Asia. Health services are falling behind demand in most countries in SSA with more than 200
million Africans having no access to health services. This is reflected in an average infant mortality rate of 93 per 1,000,
which is higher than South Asia's 84 per 1,000, Latin America's 46 per 1,000 and East Asia's 36 per 1,000. Moreover,
above 250 million lack access to safe drinking water. One African in five is affected by armed conflict and the number
of civilian casualties of war is higher than in other regions (2).
According to the World Bank (3), the depth of poverty (how far incomes fall below the poverty line of US$1) in Sub
Saharan Africa is typically greater than elsewhere in the world. This makes human development indicators (especially
Health and Education) to be a major theme on which the “New Partnership for Africa’s Development” (NEPAD:
Initiative of the Committee of African Heads of State and Government) draft action plan focuses (4).
In their second meeting, the committee in underlining the centrality of its commitment to peace and development in
Africa, outlined seven priority areas of which the two most relevant to this study appear below:
! Support efforts at developing early warning systems at continental and sub-regional levels, including the
development of strategic analysis and database systems;
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! Enhance capacity to conduct thorough inclusive strategic assessments of situations in regions affected by conflicts.
Furthermore, this study is related to global poverty reduction and the Millennium Development as stated in the United
Nations Millennium Declaration Goals in three areas, namely:
! Promoting universal primary education
! Fighting the spread of HIV/AIDS and other infectious diseases; and
! Bridging the digital divide (5).
Thus, the aim of this study, that is, mapping the trend of HDIs in SSA using GIS capabilities could serve as a means to
better understand the current situation of human development within the context of these strategic, priority areas for
Africa's development.
General uses of GIS would be for data assembly (for large and diverse data), spatial analysis/query and basic map
production. An important area of specific application of GIS to human poverty related problems would be the
integration of different HDI data sets in a common GIS database to provide a spatial framework for poverty analysis,
alleviation and monitoring. Providing the spatial dimension to HDIs means locating or mapping these indicators where
they occur as it is in the real world. Knowing the 'where' of poverty, that is, the spatial distribution of poverty at the
provincial, city, neighbourhood levels has been the most required information among policy decision makers in support
of their decision making and planning processes, particularly in the allocation of anti-poverty programmes (6).
2. STUDY AREA
The area of focus is ‘sub-Saharan Africa’, a nomenclature used in many official publications (e.g. World Bank), to refer
to those countries from Mauritania in the northwest of Africa downwards to South Africa (see Figure 1). In terms of
aggregate economic or welfare terms, South Africa ought to be excluded but it is included with respect to poverty
among majority of her people. Culturally and economically the countries from Egypt to Morocco are quite distinct
from tropical Africa, and are better classified with the Middle East (7).
Figure 1. Sub-Saharan Africa
3. METHODOLOGY
The use of GIS for human poverty related problem solving is advantageous over other kinds of information systems.
GIS helps to integrate large volumes of spatial data with non-spatial data (socio-economic, demographic data) from
different sources, analyses relationships between these variables and enables the visualisation of such data in map form.
These maps show the spatial incidence of HDIs and aid the determination of where interventions are needed. Such
better understanding is beneficial to policy makers, as it would facilitate obtaining maximum results from poverty
reduction efforts.
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HDIs are quite numerous which necessitated the selection of few representative variables in this study. These are the
Human Poverty Index (HPI), which comprises of life expectancy, adult illiteracy rate, Gross National Product (GNP:
per capita); and percentage of population living below US$1 and US$2 per day. Values of these HDIs were derived
from two separate publications of the African Development Bank (ADB), which are all secondary data
sources (8 and 9).
4. MAPPING AND INTERPRETATION OF THE HUMAN POVERTY INDEX (HPI)
The Human Poverty Index (HPI) is a composite index of deprivations of basic human capabilities in three fundamental
dimensions. These are a long and healthy life, as measured by the percentage of people not expected to survive to the
age of 40 years; knowledge as measured by adult illiteracy rate. Lastly, is deprivation in economic provisioning, from
private and public income, as measured by GNP per capita (Purchasing power parity prices). Furthermore, the
percentage of people lacking access to health services, safe water and the like can be integrated to reflect local
conditions (10 and 11).
4.1 Life expectancy
Life expectancy as an indicator of human development is measured by the percentage of the population not expected to
survive to the ages of 40 and 60 years for developing and developed countries respectively. In 1995, the World Summit
for Social Development targeted the year 2000 for increasing life expectancy in developing countries to an average of
60 years, however, improvement in life expectancy has been slow in SSA (11 and 3). Figure 2 shows the spatial
variations in the percentage of each country's population not expected to survive to the age of 40 years as at 1998.
Figure 2. Population not expected to survive to the age of 40 years (percentage)
By inference, countries with lower percentage values of people not expected to survive to 40 years have better life
expectancy. Examples of such are Ghana, Sudan, Cameroon, and Madagascar. In the same vein, the higher the
percentage values for a country, the higher the number of people in the population expected to die before the age of 40
years. Life expectancy in SSA is the lowest in the world, and continues to decrease with HIV/AIDS incidence rates of
more than 25% in some countries, mostly in East and Southern Africa (1).
4.2 Adult Illiteracy Rate
Prominent among the factors that exacerbate poverty in SSA is the lack of access to education, which inhibits the poor
from participating in economic growth. Figure 3 shows the rate of adult illiteracy as a percentage of each country's
population as at 1998.
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Figure 3. Distribution of Adult Illiteracy Rate (Percentage)
The figure reveals that countries with the highest rate of adult illiteracy are all located in West Africa, that is, Niger,
Senegal, Guinea Bissau, Burkina Faso and Benin. Tackling Africa's development challenges will require more than
just a change in the allocation of resources. African governments as well as regional bodies will need to embark on
inclusive policies to accommodate marginalised groups to meet the challenges of poverty reduction and human
development. Accelerated human development will be achieved thorough public investment in education, especially
with a redirection towards attaining universal primary education. Basic education increases the rate of return on
investment since it enables acquisitions of essential skills to enhance labour productivity and income (8).
4.3 Gross National Product (GNP) Per Capita
Gross National Product (GNP) measures the total domestic and foreign value added claimed by the residents of a
country. It comprises Gross Domestic Product (GDP) plus net factor income from abroad, which is the income
residents receive from abroad for factor services less similar payments made to non-residents who contribute to the
domestic economy (8). Figures 4a, 4b and 4c show the spatial variations in GNP across SSA between
1980-1999.
Figure 4a. Distribution of GNP in 1980 Figure 4b. Distribution of GNP in 1999
From figures 4a and 4b, the GNP of each country between 1980 - 1999 can be compared in relation to that of other
countries. From these figures, the dynamics of GNP in each country within this twenty-year period is not really vivid.
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This is because slight changes in the GNP of a country may be hidden within the class range used for symbolisation.
The trend in GNP is better understood by a close study of figure 4c.
Figure 4c. Pattern of Gross National Product Dynamics between 1980 - 1999
About seventy percent (70%) of the countries of SSA suffered a decline in their GNP between 1980-1999. Examples
are Nigeria, Zimbabwe and Democratic Republic of Congo where political instability and armed conflict impacted
negatively on their economic performance. Twenty-five percent (25%) of the countries experienced an improvement in
their GNP such as South Africa, Swaziland and Guinea. The remaining five percent (5%) recorded virtually the same
GNP over this period, namely, Rwanda and Malawi. The implication of these findings is that the growth of income in
SSA has been dismal within the twenty-year period under reference.
4.4 Human Poverty Index
The HPI is a composite index of deprivations of basic human capabilities, which summarises the three fundamental
dimensions discussed in the foregoing subsections. The HPI for each country as published by the ADB report was
analysed and mapped (see figures 5a and 5b).
Figure 5a. Human Poverty Index for 1995 Figure 5b. Human Poverty Index for 1998
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In figures 5a and 5b, the HPI value for each country in SSA for 1995 and 1998 are shown respectively. The lower the
HPI for a country the better the living standard. Conversely, the higher the HPI value in a country, the higher the level
of human poverty experienced. Within the three-year reference period, the trend of HPI in each country is shown in
figure 5c. This figure is the result of the analysis (query) seeking to know the countries in which the HPI either
increased (worsening poverty) or decreased (declining poverty). From the figures, it can be deduced that countries
with the highest HPI values are mainly landlocked countries and predominantly in West and Central Africa. A
probable cause could be the fact that many of these countries experienced drought or adverse weather conditions that
undermined agricultural production, along with political and civil unrest disturbances that impacted
adversely on them (8).
Figure 5c. Human Poverty Index Dynamics (1995 – 1998)
5. INTERNATIONAL DEVELOPMENT GOAL ON POVERTY
The International Development Goal on Poverty calls for a reduction (by half) of the proportion of people living on less
than a dollar a day by 2015. Performances towards the end of the twentieth century indicated that most regions of the
world were expected to reach this goal (see table 1). Sub-Saharan Africa however is an exception, where growth is
expected to fall short (12).
Table 1. Percentage of people living on less than $1 per day in 1987, 1990 and 1998
Percentage of people living on less than $1 a day
Regions 1987 1990 1998
East Asia and the Pacific
(Excluding China)
26.6
23.9
27.6
18.5
14.7
9.4
Eastern Europe and Central Asia 0.2 1.6 3.7
Latin America and the Caribbean 15.3 16.8 12.1
Middle East and North Africa 4.3 2.4 2.1
South Asia 44.9 44.0 40.0
Sub-Saharan Africa 46.6 47.0 48.1
Source: Issue Briefs (2001)
It is to be noted that there are weaknesses inherent in these estimates since up-to-date survey and price data are not
available for all countries, and the quality of household surveys vary. Despite these weaknesses, the estimates provide a
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fairly reliable view of poverty trends at the aggregate level, due to the substantial increases in the coverage of household
surveys and in data accuracy over the past few years (13).
Figures 6a and 6b show the percentage of population living below US$1 (extreme poverty line) and US$2 (moderate
poverty lines) per day respectively in SSA.
Figure 6a. Percentage of population living below US$1 per day
Figure 6b. Percentage of population living below US$2 per day
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Poverty in Africa hinges on a whole range of circumstances operating together at global, regional, national, local and
even personal scales. However, the relative importance of the various factors and the scales of analysis do differ greatly
from place to place. In some places global factors, such as fall in commodity prices may be of critical significance,
while in other places a local conflict may have caused people to be especially poor. Irrespective of the poverty
indicators used, poverty is on the increase in SSA as a region (7).
6. CONCLUSION
In this paper, we have sought to analyse and map the trend of several HDIs with due concentration on indicators
comprising the human poverty index. Although the trend may not be too vivid in all countries, there seems to be a
correlation between the indicators examined in some countries like Ethiopia, Central African Republic, Mali, Sierra
Leone and Niger. With very high HPI values and declining GNP, 70% of their population live below US$1 and US$2
per day, while above 50% of their population are not expected to reach 40 years of age.
Success at improving human development in SSA will depend to a large extent on a better understanding of how each
country fared over a reference period of time in relation to a given indicator and why they fared thus. These are
essential factors in understanding why poverty is increasing in SSA, in contrast to other regions of the world. However,
behind all these statistics and maps are the poor (individuals and households) whose collective lives amount to the
aggregate picture of each country.
Poverty is certainly widespread and in some cases sufficiently extreme in Sub-Saharan Africa. If early warning systems
at continental and sub-regional levels coupled with good governance and implementation of poverty reduction strategies
are put in place, human development will improve considerably in the sub-Saharan region of Africa.
7. REFERENCES
[1] G8 (2002a) Building a New Partnership for Africa's Development. http://www.g8.gc.ca/summitafrica-e.asp
(accessed 26th April, 2002).
[2] World Bank, Taking Action for Poverty Reduction in Sub-Saharan Africa: Report of an African Region Task
Force, Report No. 15575-AFR, May 1996.
[3] World Bank, A continent in Transition: Sub Saharan Africa in the Mid-1990s, African Region, November, pp12-
35, (1995).
[4] NEPAD_Abuja (2002) Communiqué issued at the end of the Second Meeting of the Heads of State and
Government Implementation Committee of the NEPAD, Abuja, 26 March 2002. www.gov.za.com2meet.html
(accessed 20th May, 2002).
[5] G8 (2002b) Summit Priorities. http://www.g8.gc.ca/summitafrica-e.asp (accessed 26th April, 2002).
[6] A.P. Manansala, Poverty Monitoring System in Angeles City, Philippines. Unpublished M.Sc. Thesis, Division
of Urban Planning and Management, International Institute for Aerospace Survey and Earth Sciences (ITC)
Enschede, The Netherlands, (1999).
[7] A. O’Connor, Poverty in Africa: A Geographical Approach. Belhaven Press, London, (1991).
[8] African Development Bank (ADB) African Development Report: Regional Integration in Africa. Oxford:
Oxford University Press. (2000)
[9] African Development Bank (ADB) Gender, Poverty and Environmental Indicators. African Development Bank.
(2001/2002)
[10] United Nations Development Programme (UNDP) Human Development report. New York: Oxford University
Press. (1997)
[11] United Nations Development Programme (U.N.D.P.) Poverty Report: Overcoming Human Poverty. New York.
United Nations Development Programme. (2000)
[12] Issue Briefs (2001) 2001 Poverty Update. The World Bank Group. (Website accessed 30th September, 2001:
http://www.worldbank.org/html/extdr/pb/index.htm).
[13] PovertyNet (2001) Income Poverty: The Latest Global Numbers. (Website accessed 1st November, 2001:
http://www.worldbank/org/index.htm).
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MAPPING SELECTED HUMAN DEVELOPMENT INDICATORS
IN SUB-SAHARAN AFRICA
Akinyemi, F.O.
Department of Geography. Obafemi Awolowo University.
Ile-Ife, 220001, Osun State, Nigeria. E-mail: bakin_yem@yahoo.com
BIOGRAPHY
Dr. Felicia O. Akinyemi lectures at the Department of Geography, Obafemi Awolowo University, Ile-Ife, Nigeria. A
cartographer by profession, Dr. Akinyemi received her B.Sc. (Geography) degree from the University of Benin, Benin
City, Nigeria; M.Sc. Geography (cartography) from the University of Lagos, Nigeria; PGD in Geoinformation
Production and Management (Photogrammetry and Remote Sensing) from the Regional Centre for Training in
Aerospace Surveys, Ile-Ife, Nigeria and a Doctorate in Geography (GIS/Cartography) from the University of Lagos,
Nigeria.
Her research interests are in the application of geoinformation to urban development especially in developing a spatial
decision support tool for urban poverty management, designing a GIS database for climate change impact assessment
for West Africa and landuse change mapping.
Currently, she is a member of the National Executive Council of the Nigerian Cartographic Association, ISPRS
Technical Commission VI/WG III on “International Cooperation and Technology Transfer”, Joint ICA/ISPRS Work
Group on “Incremental Updating and Versioning of Spatial Data Bases” and Chair, United Nations Group of Experts on
Geographical Names (UNGEGN) Africa West. She was born in 1970 and is married having a family with two
children.
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