Introduction: population size and growth
Population dynamics – the evolution of population size and its age structure, as determined by fertility, mortality and migration – are fundamental to economic and social development. Population growth in SADC is rapid by contemporary global standards. From 217 million in 2020, population has grown to 363 million in 2020, representing an average annual rate of increase of 2.6%[1]. Growth in the current decade is expected to be almost as rapid, at 2.5% per annum, taking the population to 465 million[2]. By way of comparison, the population of the European Union (now excluding the United Kingdom) was 447 million and the population of the United States was 331 million in 2020.
The Democratic Republic of Congo had the largest population, at 90 million in 2020, nearly a quarter of the entire SADC population. Tanzania had the next largest population at 60 million, followed by South Africa at 59 million. Next in line came Angola at 33 million, Mozambique at 31 million and Madagascar at 28 million. Malawi had 19 million, Zambia 18 million and Zimbabwe 15 million. All the other countries had fewer than three million apiece. South Africa’s share of the SADC population dropped from 20.7% to 16.3% between 2000 and 2020. The share of the northern arc of countries (Angola, DRC, Tanzania and Mozambique) grew from 52.8% to 58.8%.
Fertility
The prime cause of rapid population growth is high fertility. The standard measure of fertility is the total fertility rate, defined as the number of live births a woman would have if successively exposed to the fertility rate by age in a particular year. Countries move through fertility transitions at different times and at different rates, from TFRs of five or more to TFRs of two or below. Table 1 shows the distribution of countries by stage of the fertility transition they reached in 2020.
Table 1
Stage |
TFR range |
Countries |
None or early |
5 and above |
DRC, Angola |
Early middle |
3 to 4.9 |
Mozambique, Tanzania, Zambia, Malawi, Comoros, Madagascar, Zimbabwe, Namibia, Lesotho, Eswatini |
Late middle |
2.1 to 2.9 |
Botswana, Seychelles, South Africa |
Complete |
2 and below |
Mauritius |
The correlate of high fertility is a youthful population. In eight countries – Angola, DRC, Mozambique, Zambia, Tanzania, Malawi, Zimbabwe and Madagascar – more than half of the population is under twenty. A further consequence is a high degree of population momentum. Population momentum explains why a population will continue to grow even if the fertility rate were to drop to replacement levels instantly. Population momentum occurs because it is not only the number of children per woman that determine population growth, but also the number of women in reproductive age. A youth bulge takes time to work through the reproductive age range. Population momentum is defined as the ratio of the ultimate population to the current population with the TFR set at the replacement level. For the SADC population as a whole, it was 1.71, compared with 1.26 for the world, with Africa excluded. So even if fertility were to drop to replacement immediately and stay there, the ultimate SADC population would be 637 million. Of course, that is not going to happen. The United Nations medium variant projection for 2050 is 712 million, with continued growth after that date.
Mortality
Two measures of mortality are presented here: the infant mortality rate (IMR - the number of infants dying before their first birthday per thousand live births), and the life expectancy at age one (e1 – the number of additional years that survivors live on average from the first birthday, at current mortality rates. Table 2 classifies countries by high and low levels of infant mortality and high and low levels of life expectancy at age one.
Table 2
IMR less than 40 |
IMR of 40 or more |
|
e1 of 65 or more |
Botswana Madagascar Mauritius Seychelles |
Comoros Malawi Zambia |
e1 less than 65 |
Namibia South Africa |
Angola DRC Eswatini Lesotho Mozambique Tanzania Zimbabwe |
The two measures are correlated, but not perfectly. Comoros, Malawi and Zambia have relatively high infant mortality for their life expectancies at age 1, whereas the opposite is the case in Namibia and South Africa.
Migration
Migration has a range of possible meanings. First, there is immigration and emigration to and from a country. Net migration is immigration less emigration, and the net migration rate is net migration per thousand of the resident population. Secondly, there is the stock of international migrants: people who have migrated into a country and are still present there. Thirdly, there is migration to and from urban areas within a country.
Analysis is limited by lack of information. We have no up to date estimates of immigration and emigration. We do have estimates of net migration. The annual net migration rate into SADC as a whole was low (–0.1 per thousand) between 2015 and 2020. Annual net migration rates at or above two per thousand were found in Zimbabwe (-8.4), Eswatini (-7.4), Lesotho (-4.8), Comoros (-2.1), Seychelles (-2.0) and South Africa (+2.5). We also have information on the stock of international migrants. The countries with the highest percentages are Seychelles (13.3%), South Africa (4.8%), Botswana (4.7%) and Namibia (4.3%).
Urbanization[3]
Statistics on urbanization are complicated by the fact that there is no uniform definition of what ‘urban’ means. Each country has its own definition, so that cross-country comparisons should be made with caution. The proportion of the SADC population which was urban by each country classification was 36.5% in 2000, rising to 46.0% in 2020 and is expected to rise to 51.4% by 2030. This implies a growth in the urban population of 3.8% per annum on average between 2000 and 2020 and 3.7% between 2020 and 2030, implying a doubling of the urban population every eighteen years. Meeting the associated infrastructure development challenge is a major problem in most SADC countries. The counterpart of rapid urbanization is slower population growth in rural areas: 1.8% per annum on average between 2000 and 2020 and an expected 1.4% between 2020 and 2030.
Population density
SADC countries occupy just under ten million square kilometres, excluding land under water. Average population density in 2020 was 37 per square kilometer. The average conceals substantial variation across countries. The three island countries of Mauritius, Comoros and Seychelles, as well as Malawi have densities of above 200 per square kilometre. After them come Lesotho (71), and Tanzania and Lesotho (both 67). The least densely populated countries are Nambia (3), Botswana (4), Zambia (24) and Angola (26). These densities are relatively light compared with both east African countries to the north of SADC and West African countries, where high and rising densities may produce a Malthusian crisis in coming decades.
Conclusion
The two major demographically based challenges facing SADC are the ability of SADC economies to provide livelihoods for rapidly rising populations and to provide infrastructure for even more rapidly growing urban populations. These challenges will be explored in later briefs.
Charles Simkins
Head of Research
charles@hsf.org.za
Annexure – Supporting table
Population |
Average annual growth |
Median age |
Population momentum |
Total fertility rate |
Life expectancy at age 1 |
Infant mortality rate |
Per cent urban |
Net migration rate |
Migrant stock (%) |
|
2020 ('000) |
2000-20 |
2020 |
2020 |
2015-20 |
2015-20 |
2015-20 |
2020 |
2015-20 |
2019 |
|
Source |
1 |
1 |
1 |
1 |
1 |
2 |
1 |
3 |
||
Angola |
32866 |
3.5% |
16.7 |
1.84 |
5.6 |
63.6 |
65 |
66.8 |
0.2 |
2.0 |
Botswana |
2352 |
1.8% |
24.0 |
1.72 |
2.9 |
70.2 |
31 |
70.9 |
1.3 |
4.7 |
Comoros |
870 |
2.4% |
20.4 |
1.43 |
4.2 |
66.6 |
55 |
29.4 |
-2.4 |
1.4 |
DRC |
89561 |
3.3% |
17.0 |
1.77 |
6.0 |
63.4 |
68 |
45.6 |
0.3 |
1.1 |
Eswatini |
1160 |
0.7% |
20.7 |
1.81 |
3.0 |
60.8 |
43 |
24.2 |
-7.4 |
2.8 |
Lesotho |
2142 |
0.3% |
24.0 |
1.02 |
3.2 |
56.0 |
65 |
29.0 |
-4.8 |
0.6 |
Madagascar |
27691 |
2.9% |
19.6 |
1.86 |
4.1 |
67.5 |
30 |
38.5 |
-0.1 |
0.1 |
Malawi |
19130 |
2.7% |
18.1 |
1.93 |
4.3 |
65.2 |
43 |
17.4 |
-0.9 |
1.0 |
Mauritius |
1272 |
0.4% |
37.5 |
1.11 |
1.4 |
74.6 |
11 |
40.8 |
0.0 |
2.3 |
Mozambique |
31255 |
2.9% |
17.6 |
1.84 |
4.9 |
62.5 |
56 |
37.1 |
-0.2 |
1.1 |
Namibia |
2541 |
1.8% |
21.8 |
1.58 |
3.4 |
64.2 |
34 |
52.0 |
-2.0 |
4.3 |
Seychelles |
98 |
1.0% |
34.2 |
0.96 |
2.5 |
73.1 |
11 |
57.5 |
-2.1 |
13.3 |
South Africa |
59309 |
1.4% |
27.6 |
1.49 |
2.4 |
64.4 |
28 |
67.4 |
2.5 |
4.8 |
Tanzania |
59734 |
2.9% |
18.0 |
1.79 |
4.9 |
66.6 |
43 |
35.2 |
-0.7 |
0.7 |
Zambia |
18384 |
2.9% |
17.6 |
1.85 |
4.7 |
65.3 |
47 |
44.6 |
-0.5 |
1.0 |
Zimbabwe |
14863 |
1.1% |
18.7 |
1.66 |
3.6 |
62.3 |
40 |
32.2 |
-8.2 |
2.8 |
Total |
363228 |
2.6% |
1.75 |
64.8 |
43.0 |
46.0 |
-0.1 |
Sources
- United Nations, World Population Prospects 2019
- United Nations, World Urbanization Prospects 2018
- United Nations, Department of Economic and Social Affairs data
[1] All population estimates are taken from the United Nations, World Population Prospects, 2019.
[2] This is based on the WPP medium variant projection.
[3] All data in this section are taken from the United Nations, World Urbanization Prospects 2018