THE USES OF DEMOGRAPHIC DATA

• Introduction
• Data Quality & Availabilty
• Mortality within Southern Africa
• Planning for Malaria Control in the SAMC Area
• Tables

Introduction

• The population at risk of malaria

Risk groups with low immunity to malaria may be the result of age (under-five year olds), pregnancy and migration. The size of these risk groups can be estimated using demographic data.

• Population distribution and density

Demographic data can be used to document the spatial distribution of a population at a variety of subnational scales from the provincial and district levels down to the ward and sub-ward levels. A proper understanding of the distribution of population within countries can help MCP’s target resources effectively.

• Migration pattern

The movement of people can have a major impact on malarias mission. For example, non- or low-immune migrants moving to malaria-endemic areas can cause a sharp upturn in malaria mortality. Equally, migrants can bring in drug-resistant strains of malaria into previously unaffected areas. Changes in population density due to migration can lead to changes in the ecology of areas that can increase mosquito breeding sites. For example, dam building in rapidly growing rural areas and development of peri-urban areas and ‘urban agriculture’ in towns and cities. MCPs need to understand where major population movements are occurring and their composition (e.g. age of migrants) and nature (e.g. permanent, forced, temporary, circular).

• Population growth

Demographic data provides information on how quickly populations are growing. Medium-to-high birth rates in SAMC countries mean population growth rates range between 2 and 3% per annum. MCPs need to appreciate the population they serve is growing and at different rates within their country (due to differences in mortality, fertility and, especially, migration).

• Malaria mortality

Knowing the contribution of malaria to mortality is vital in order to evaluate the impact MCPs have on malaria control. The quality and quantity of cause-specific mortality data ranges from poor to moderate in most SAMC countries. Consequently, there are many problems in estimating malaria mortality from existing data. Whenever malaria mortality estimates are calculated the methodology used should be clearly stated and the limitations of the data acknowledged.

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DATA QUALITY AND AVAILABILITY

The quality and availability of demographic data vary considerably within the SAMC programme area. It is important to determine how rates or totals are calculated and for what period. As censuses are taken every 10 years, census data quickly become out-of-date. Often Central Statistical Offices (CSOs) provide population projections for the 10 year period between censuses. However, these projections are based on assumptions that may not reflect the true situation. For example, the assumption made by many CSOs that mortality rates would continue to fall has been violated by the impact of HIV on mortality. Equally, projections for small areas within countries (the district level and below) are liable to have a wide margin of error.

Within the SAMC programme area the main sources of demographic data are censuses, Demographic and Health Surveys (DHS), and vital registration systems.

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MORTALITY WITHIN SOUTHERN AFRICA

Mortality levels within SAMC countries have risen markedly in the last decade. This is primarily due to high HIV prevalence levels. Estimating the precise impact of HIV on mortality is very difficult and is reflected in the wide range mortality estimates available for SAMC countries.

Table 3.1. Estimates of the crude death rate (1996), infant mortality (1996), under-five mortality (1995-2000) (WHO, 1998) and maternal mortality (1990) (UNICEF, 1998).

The contribution of malaria to mortality varies considerably between SAMC countries because of differences in malaria endemicity, prevention and treatment as well as differences in the incidence of other infectious diseases (e.g. HIV), health service provision and socio-economic conditions. However, even in countries where malaria is confined to limited areas of the country, malaria mortality can be high among vulnerable groups, particularly in epidemic years. For example, in 1996 the malaria epidemic in Zimbabwe meant malaria was the leading cause of maternal mortality being responsible for 40% of maternal deaths.

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PLANNING FOR MALARIA CONTROL IN THE SAMC AREA

The estimated total population of SAMC countries in 1998 was 142m (see Table 4.1). The population of SAMC countries varies considerably: South Africa and Tanzania make up over 50% of the SAMC population while Botswana, Namibia and Swaziland make up only 3%. Equally, population density varies widely within the SAMC region ranging from 2.0 in Namibia to 87.6 people per km² in Malawi.

Table 4.1. Total population and population density of SAMC countries, 1998 (UN 1995; WHO 1998; INE 1999).

The SAMC countries have relatively young populations (Table 4.2). However, age distribution does vary between countries (Figure 4.1) with the percentage of the population under 16 years ranging from 37% (South Africa) to 48% (Angola) and for under-fives from 13% (South Africa) to 20% (Angola).

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Table 4.2. Estimated population by age-group and by country, 1998 (WHO 1998, SAMC estimate for Mozambique)

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The population that is at greatest risk of malaria consists of those with low or no immunity to malaria. In non-endemic areas, all age groups are at risk of malaria. However, in endemic areas under-five year olds and pregnant women form the two main risk groups due to their low immunity to malaria. Within the SAMC area there are approximately 23 million children under-five years of age (see Table 4.2).

The estimated total number of births per year can be used as a proxy for the number of pregnant women per year (see Table 4.3).

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Table 4.3. Estimated number of women aged 15-49 years, estimated crude birth rate and estimated number of births for SAMC countries, 1998 (WHO 1998, SAMC estimate for Mozambique)

Table 4.4. Percentage of the population living in malarious areas and the number of under-fives and pregnant women at risk of malaria for SAMC countries.

Table 4.5. Population and urban growth rates per annum and % of population living in urban areas by SAMC country (UNICEF, 1998)