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The Economic Costs of Malaria in South Africa: Malaria and the DDT Issue, by Richard Tren; Foreword by Donald Roberts

The Economic Costs of Malaria in South Africa

Malaria Control and the DDT Issue

 

Richard Tren


Executive Summary

Malaria is one of the world's most serious tropical diseases and imposes very significant economic costs on some of the poorest nations on earth. This study estimates the direct and indirect costs of malaria to South Africa and examines the issues surrounding the use of DDT as an anti-malaria insecticide.

Early records of malaria cases by Europeans in the late 19th and early 20th centuries show that malaria was a severe inhibitor of economic development and caused large economic costs. The current malarial areas in South Africa today are about one fifth of the size they were at the beginning of the 20th century. The historical success in controlling malaria is due in very large part to the use of DDT in malaria vector control.

In recent years, however, there has been a sharp rise in the number of malaria cases in South Africa, and indeed throughout Southern Africa. This rise is due to a number of factors, such as high rainfall in recent years, increased migration and a reduction in the use of DDT in vector control. The rise in malaria cases imposes heavy costs on the local and national economies. The economic cost (direct costs include the costs of care and control of malaria, and indirect costs include the losses in productivity and lost future earnings from death) of malaria in South Africa is conservatively estimated to be around R124 million (US$20 million) in 1997/98. Malaria in selected Southern African countries could cost as much as US$1,000 million, or 4% of GDP in 1998. In South Africa, malaria usually occurs in rural areas with agricultural and labour intensive industries. The incidence of malaria in these areas has severe economic impacts and as in the past, continues to hamper economic development

For a number of reasons, DDT is being phased out of the malaria control programmes in South Africa. Numerous environmentalist organisations have lobbied strongly for the banning of DDT, despite the success of the insecticide in saving lives and preventing disease in developing countries. While DDT is not an ideal insecticide, it does have numerous advantages over the alternative insecticides and has a proven track record. Although DDT is currently used by a number of Southern African countries in malaria control programmes, the UNEP Governing Council is pressing for the banning of DDT and eleven other persistent organic pollutants (POPs).

The potential banning of DDT highlights a trend whereby environmental pressure from mostly developed countries imposes standards on developing countries where they are neither accepted nor appropriate. While there are alternatives to DDT, these are all more expensive and frequently more complicated to use than DDT. The banning of DDT would not only remove an important anti-malaria weapon, but will result in countless deaths and very significant economic costs (perhaps as much as US$480 million) on countries that can ill afford it.


Foreword: DDT is Still Needed for Malaria Control

Donald R. Roberts

Donald R. Roberts, Ph.D., has worked in the area of malaria vector ecology and malaria control for 32 years. He has conducted field studies in Southeast Asia, the Middle East and in several countries of the Americas. He has published over 80 peer-reviewed papers and holds one patent. In recent years his research has focused on applications of remote sensing and geographical information system technologies to the study and control of malaria. His research also has emphasised studies to elucidate actual functions of insecticide residues in controlling malaria. Dr. Roberts created the project and directed the early phase of research at the Walter Reed Army Institute of Research on enzyme-linked imunosorbent assays for detecting malaria sporozoites in Anopheles mosquitoes. He was also a principal participant in the research that led to incrimination of Culicoides paraensis as the vector of Oropouche virus in urban areas of the Amazon Basin.  

Eliminating DDT: The Issues

The United Nations Environment Programme (UNEP) is negotiating a legally binding agreement for global elimination of DDT (UNEP, 1998), along with other persistent organic pollutants (POPs). Reports in the popular press suggest that global elimination of DDT is a lofty and desirable goal (Kirby 1999, Denyer 1999). However, modern trends of increasing malaria that accompanies decreasing numbers of DDT-sprayed houses reveal a devastating cost for DDT elimination (Mouchet et al 1997, Roberts et al 1997).

As will be shown later, DDT elimination has been an important goal of certain environmental groups and in the foreign policies of developed countries and in the politics of many UN organisations. The result of these policies and politics is that many developing countries have already been forced to abandon their public health use of DDT. Almost without exception, where this has occurred, malaria rates have increased (Figure 1). Today, if UNEP negotiations are successful in the unconditional banning of DDT, which is the intent; even more millions will suffer increased death and disease from malaria.

As stated by Heppner and Ballou (1998), "More cases of malaria are expected to occur in 1998 than in 1958.." This is a sobering assessment of our backward march to the pre-DDT era of rampant, uncontrolled malaria. The re-emergence of this highly preventable disease speaks to the limited role of poor countries and poor people in international politics. Even the fact that this disease has been allowed to re-emerge with limited international notice attests to the political invisibility of threatened populations.

The re-emergence of malaria in the Americas and declining use of DDT for control are illustrated in Figure 2. In 1959, the house spray rate of DDT for 21 countries of the Americas was 71.55 houses per 1,000 inhabitants. This rate was reduced 81% by 1989. Since 1989, most countries of the Americas have stopped using DDT and numbers of malaria cases are growing at unprecedented rates. The relationship between reduced numbers of houses sprayed with DDT and increased numbers of malaria cases is irrefutable (PAHO, 1991, 1994, 1997, Mouchet et al 1997, Roberts et al 1997).

Just as the pressures on developing countries to stop using DDT are diverse and multi-layered (discussed below), the arguments for and against DDT are diverse and multi-layered (see Taverne 1999). Some environmentalists argue that there are effective alternative insecticides and DDT is no longer needed. This argument ignores hopes of environmental groups to even stop the use of potential DDT alternatives, e.g., organophosphate and pyrethroid insecticides (Congressional Research Service Report, 1993 and World Wildlife Fund, 1998). As warned by the American Crop Protection Association in 1998 (Kenworth 1999), "..sooner or later, virtually all pesticides and pesticide uses will be jeopardised." Additionally, the environmentalist argument does not account for prohibitive costs of the alternative insecticides. The more naïve even argue that integrated vector management should replace use of all insecticides for malaria control (World Wildlife Fund, 1998). Unfortunately there are no cost-effective, broadly applicable methods of environmental management for malaria control. So, in reality, promoting the application of these methods is like promoting the use of a malaria vaccine when there is no vaccine. Some DDT opponents propose that predictions of increased disease are expected and are consistent with the unrealistic predictions that accompanied actions to eliminate other toxic substances, e.g., freon, Alar, chlordane, and use of DDT in agriculture. However, as shown in Figure 2, we do not need to wait for global elimination of DDT in order to know the end result. DDT elimination has been underway since the late 1970s and we know with certainty that numbers of malaria cases spiral out of control when endemic countries stop spraying internal house walls. In a recent US Environmental Protection Agency (EPA) Risk Assessment Forum Project (Crisp et al 1998), it was determined that "in a risk assessment paradigm for human health, relevant and adequate epidemiological studies and case reports for the agent(s) are preferable." Well, in the case of DDT and malaria control, the studies and case reports have been performed. Most endemic countries have experimented with alternatives to DDT and countries generally increase use of alternative insecticides when DDT is banned. Despite their use of alternative insecticides, rapidly increasing malaria is the legacy of DDT elimination. Increased malaria is probably due to some combination of factors, e.g., countries not being able to afford to spray a sufficient number of houses with more expensive insecticides and/or alternative insecticides not being as effective or not lasting long enough to bring about adequate levels of control.

Without doubt, the insecticide and pharmaceutical industries have received direct benefits from DDT elimination. The former industry has benefited because countries purchased more expensive insecticides and the latter benefited from selling more drugs to treat an ever-increasing number of malaria cases. Regardless of benefits that accrue to these industries, the wealthy multinational environmental groups, such as the World Wildlife Fund (WWF); Physicians for Social Responsibility (PSR); International Pesticide Action Network (PAN); International Organisation of Consumer Unions (IOCU); and the Environmental Liaison Center (ELC), who influence foreign policies of industrialised countries and UN organisations are the primary proponents for global DDT elimination (World Wildlife Fund, 1998 and Pan American Health Organisation, 1993). Additionally, United Nations organisations such as UNEP, the World Health Organisation (WHO), and Food and Agriculture Organisation (FAO) are full participants in this environmental agenda.

Although most knowledgeable people are concerned about environment issues, when the environmental agenda eliminates a critical public health tool, it is time to ask a number of questions, to include how large a public health price and who pays? Of the world's estimated 6.8 billion people, 4.4 billion live in developing countries. Within developing countries, 2.64 billion have no access to basic sanitation and 1.45 billion are without safe drinking water (United Nations Human Development Report of 1998). Unfortunately, a large proportion of these poor and disadvantaged people live in malaria endemic countries. The price for DDT elimination is already enormous and it is being paid in daily instalments of lost health and lost lives for hundreds of millions of the world's poorest and most disadvantaged people.

Role of the World Health Organisation

Over the years, WHO experts, WHO Expert Committees and WHO statistical reports have consistently shown that DDT is the most cost effective, and time-tested tool for preventing transmission of human malaria. These reports document, in the clearest of terms, how DDT freed 32% of the world's population from the risk of malaria, and for most of the last 50 years, how DDT continued to protect hundreds of millions of people in malaria endemic countries (Brown 1976, WHO 1984).

As unequivocally stated in a statistical report (WHO 1992) "...annual cost of programmes based on intradomiciliary spraying as the main intervention ranged from US$ 0.5-5 per capita of actually protected population. In most of these countries, DDT was the insecticide used, and a shift to alternative, more toxic and costly insecticides could lead to considerable increases." Also, WHO safety evaluations, as recent as 1993, have uniformly and consistently concluded that DDT is safe for humans and acceptable for use in malaria control (WHO 1994).

Yet, since 1979, WHO strategies have specifically de-emphasised use of house spraying for malaria control (Roberts et al . 1997). Discussions with malariologists in developed and developing countries alike and publications of prominent health workers suggest that a scientific explanation of the global strategies does not exist. Likewise there appears to be no consensus of support for WHO's de-emphasis of house spray programmes (Farid 1991 and Mouchet et al 1997).

In 1969, the great Venezuelan malariologist, Dr. Arnoldo Gabaldon, argued for establishing a WHO strategy that emphasised residual spraying of houses to maintain the successes of the eradication programme.

Changes in strategy are necessary - general public-health activities in hyperendemic areas are not effective in the presence of malaria; the funds they use might be better designated for efficient indoor residual spraying. (Litsios 1996)

Unfortunately, Dr. Gabaldon's arguments to WHO's Malaria Expert Committee were ignored and he subsequently disassociated himself from the 1969 report (Litsios 1996). In 1979 WHO adopted a new Control Strategy with four tactical variants. The causal link between decreasing numbers of sprayed houses and increasing malaria was ignored. The new strategy defined WHO's emphasis on curative measures and its unambiguous de-emphasis of preventive measures (WHO 1979, and Gilles and Warrell 1993). This strategy sent a clear and erroneous message to national programmes that DDT was not needed. De-emphasis of vector control measures was even more strongly worded in WHO's Global Malaria Control Strategy (GMCS) of 1992 (WHO 1993).

Pressure from WHO for changes in the organisational structure of malaria control programmes also obstructed continuation of house spray activities. The idea of placing malaria control in a primary health care organisational framework was formally presented to the World Health Assembly (WHA) in 1979 (WHO 1979). In 1985 the WHA adopted resolution 38.24 for incorporating vertically structured malaria control programmes into horizontally structured primary health care (PHC) systems (World Health Assembly 1985, and Gilles and Warrell 1993). A recent study by Thomson et al (1999) showed no significant difference in amount of malaria in children in villages with PHC services versus children in villages without PHC services.

Impact of Global Strategies

International assistance and political acceptability of malaria control programmes are generally contingent on compliance with WHO's global strategies. In other words, if a developing country wants external assistance, its proposal should comply with the WHO strategy and this means that vector control must be de-emphasised. Beyond this, assistance is often contingent on the specific non-use of DDT. For example, the US Agency for International Development (USAID) has invoked sections of the Foreign Assistance Act and USAID Regulation 16, published at 22 Code of Federal Regulations, Part 216 and USAID's pesticide procedures in section 216.3(b) for making decisions about foreign assistance to programmes in developing countries that used DDT for malaria control. The rationale is that DDT is not registered by the Environmental Protection Agency (EPA) for use in the US, consequently foreign assistance is not available to programmes that use DDT. This registration issue ignores the fact that DDT would not be registered by EPA because malaria is not a problem in the US. Also this interpretation ignores WHO's ruling that DDT is safe and effective for use in malaria control. Similar restrictions are employed by other industrialised countries to prevent continued use of DDT in developing countries.

The impact of these conditions is partly defined in the pace of countries abandoning DDT and, in some cases, all house-spray activities. In 1993, 8 of 11 malaria endemic countries of South America reported some low-level use of DDT for malaria control. French Guiana, Suriname and Guyana reported no spraying and were the most highly malarious countries of the Americas (PAHO 1994). In 1996, only Ecuador, Venezuela and Argentina reported use of DDT (PAHO 1997).

We should note that the early (pre-eradication) patterns of malaria response to house spray programmes in the Americas did not change during the eradication era. Where DDT had shown an ability to stop transmission, disease was eradicated, e.g., southern Brazil; but where transmission was not stopped, only variable levels of control were achieved, e.g., some countries of Central America and regions of the Amazon Basin.

We should also note that, just as the patterns of malaria response to DDT-sprayed houses did not change during the eradication programme, the same patterns held steady after eradication. So as house spray programmes declined, malaria rates increased and transmission reappeared in areas previously cleared of malaria. We should further note that these occurrences reflect a failure to use the chemical, not a failure of the chemical itself. During this time of increasing malaria, Mexico, Ecuador and Belize still used DDT to exert spectacular control over burgeoning malaria rates (Roberts et al 1997). Control was achieved in Mexico despite problems of vector resistance to DDT.

Reduced malaria rates in Mexico, Belize and Ecuador are in contrast to the increased numbers of malaria cases in many other countries of the Americas. In spite of their successes, Mexico and Ecuador were specifically identified for non-compliance with the GMCS in PAHO's 1997 report (PAHO 1997). Countries of Africa have also used DDT to exert renewed control over increasing malaria rates (Mouchet et al 1998).

One might argue that change has occurred; so now it is time to get on with the job of making WHO's global strategy a success. Unfortunately, the global strategy includes no broadly applicable and cost-effective preventive measures, so success is simply not possible. Emphasis on case treatment (the core tenet of the global strategy and the new 'roll back malaria' initiative) is laudable; but case treatment is basically curative, not preventive. Without doubt, de-emphasis of preventive measures has allowed the numbers of cases to increase in many rural and even urban environments.

Prior to the mid-1940s malaria was endemic in urban areas of the Amazon Basin. With the advent of DDT and organised house spray programmes, urban malaria largely disappeared. Unfortunately, persistent urban malaria is once again becoming a major health burden (Sandoval et al 1998, Guarda et al 1999).

The dichotomy of WHO's Malaria Expert Committee's consistent support for use of DDT versus WHO strategies that worked against use of house spray programmes suggest that global strategies have been political formulations unrelated to the opinions of malariologists or to health interests of people living in malaria endemic countries. In the international arena, defence of DDT for public health use is a WHO/PAHO responsibility. Overall, it is disappointing to examine how these organisations fulfil their responsibilities.

WHO's GMCS de-emphasises vector control measures. The more recent 'Role Back Malaria' initiative does not even mention the house spray approach to malaria control. The key negotiator for WHO's position on the DDT controversy is with the Panel of Experts on Environmental Management for Vector Control (PEEM). The PEEM was established in 1980 by FAO, UNEP and WHO to promote environmental management for vector control, i.e., to de-emphasise use of insecticides.

The Pan American Health Organisation has worked to obtain compliance of countries in the Americas with the GMCS. Unlike the WHO, PAHO has actually called for prohibition of continued DDT use for malaria control (PAHO, Division of Health and Environment 1994) and recommended that countries prohibit the purchase, distribution and use of DDT (PAHO 1993).

In 1995, a North American Commission for Environmental Cooperation (CEC) agreement forced Mexico to stop producing DDT and discontinue use of DDT for malaria control. The PAHO participated in the CEC meeting; but proceedings of that meeting reveal no PAHO defence for continued production or use of DDT. On the other hand, the Ministry of Health (MOH) of Mexico declared openly that DDT was an important and valuable component of its malaria control programme (Commission for Environmental Cooperation 1995). In spite of this, the government of Mexico signed the agreement. The signed agreement attests to the economical and political power of environmental movements within developed countries. The CEC agreement brings an end to the use of DDT for malaria control in Mexico and, more importantly, low cost availability of DDT for malaria control programmes throughout the Americas.

The Future

For certain, DDT is still needed for control of malaria. This does not mean that we should return to the wide scale use of DDT as employed during the eradication programme. Even today, formal WHO guidance for spraying houses is the same as employed in the eradication era (2 g of DDT/m2 of wall surface at intervals of 6 months). With research support, new and improved approaches to malaria control could have evolved from the wreckage of the eradication programme. For example, an annual or even semi-annual (bi-annual?) versus the standard 6-month spray cycle might have produced adequate levels of control in many environments (Rozendaal 1990, Roberts and Alecrim 1991). If effective, this change alone would have reduced amount of insecticide used in some control programmes by 50% or more. Partial spraying of houses might have produced control comparable to complete wall coverage (Casas et al 1998). Today, geographical information system and remote sensing technologies can be used to more accurately define risk factors and categorise houses by risk of malaria (Beck et al 1994, Pope et al 1994, Rejmankova et al 1995, Roberts et al 1995, Rejmankova et al 1998, Thomson et al 1999). Even in rural endemic areas, not all households are at equal risk of malaria transmission and we now have the technologies for accurately prioritising spray operations to increase the cost-effectiveness of limited malaria control resources.

Conclusion

In summation, there is hope for more cost-effective uses of DDT and other insecticides for malaria control. However, we are presently confronted by a global environmental agenda that opposes a major public health need. On the environmental side there is a clearly defined plan for DDT elimination through UNEP negotiations. On the public health side, there is no operable plan for controlling the current global epidemic of malaria or for controlling malaria once DDT is eliminated. So today, with malaria control positioned in organisational structures that are not compatible with vector control programmes; guided by strategies that de-emphasise vector control measures; pressured economically and politically by environmental groups and developed countries to eliminate use of DDT; combined with the political force of ongoing UNEP negotiations, the malaria endemic countries are experiencing an unmitigated disaster as numbers of malaria cases increase at unprecedented rates.

Need for Public Health Advocacy

Public health advocacy is needed to bring about an open debate of the DDT and malaria control issues. The outcome of such a debate is critical to hundreds of millions of people in malaria endemic countries. Public health professionals should not accede these issues to the exclusive domain of UN organisations, environmental groups and foreign policies of industrialised countries.

 

Figure 1. Standardized annual parasite indexes (IPAs) and house spray rates (HSRs) for 21 countries of the Americas, 1959-1995. Major changes in global malaria control strategies are depicted with arrows along the x-axis (WHA 31.45 for 1979; WHA 38.24 for 1985; and the Global Malaria Control Strategy for 1992). Block A represents a period of malaria control by spraying adequate numbers of houses with insecticide residues (primarily DDT). Block B represents a period of increasing malaria as the house-spray rates declined below effective levels. Open circles represent house-spray rates and solid squares represent standardized annual parasite indexes. (Graph copied from Roberts et al 1997)

 

Figure 2. Increases in annual parasite indexes for four categories of countries, South America, 1993-1995. For each country, the populations at moderate to high risk for malaria were adjusted to midyear (1994) values. (Graph copied from Roberts et al 1997)

 

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The Economic Costs of Malaria in South Africa

Malaria Control and the DDT Issue

 

Richard Tren

 

Acknowledgements

I am indebted to the following for their kind support, advice and information, without which this report would not have been possible: Roger Bate, Henk Bouwman, Ian Cooper, Colleen Fraser, Frank Hansford, Kelvin Kemm, Kobus La Grange, Danette Lombard, Lorraine Mooney, Jotham Mthembu, and Justin Wilkins. 

 

About the Author

Richard Tren is an economist, specialising in environmenal and natural resource issues. He was born and grew up in South Africa, but received most of his higher education in the UK. After reading economics at St.Andrews University in Scotland he went on to study at L'Universita Luigi Bocconi in Milan in 1993 and then worked in financial sector in London for two years. Mr. Tren then obtained his MSc in Environmental and Resource Economics from University College London and then returned to South Africa where he has since worked on a wide range of research projects. Mr. Tren has worked on several water resource projects for research institutions and for the South African government. He has recently become a Research Fellow of the Environment Unit at the institute of Economic Affairs. 

Introduction

Malaria is one of the most serious tropical diseases in the world and has been a health risk to humanity for many generations. Diseases referred to as deadly fevers, likely to be malaria, have been documented for thousands of years. Malaria was a very widespread disease, covering many areas of Europe, North America, South America, Asia and Africa.

It was only in 1897 that Dr. Ronald Ross of the British army, discovered the complex life cycle of the malaria parasite. Ross proved the link between the parasite of the genus Plasmodium that causes malaria and the Anopheles mosquito. Prevention of malaria had until this time concentrated mainly on the treatment of malaria patients, usually with the quinine. The discovery of the role that the Anopheles mosquito plays in the lifecycle of the malaria parasite led to arguably the most effective way of dealing with the disease - attacking the malaria vector, the Anopheles mosquito.

Vector control programmes began in earnest in the 1950s and saw the eradication of malaria in Europe and North America and dramatically reduced the incidence of malaria in many tropical countries in Asia, Africa and South America. These vector control programmes relied mainly on the pesticide, DDT, which proved to be remarkably effective in controlling the disease. In 1969 however, WHO abandoned its attempts to eradicate malaria globally, leaving many developing countries, particularly those in Sub-Saharan Africa with considerable problems associated with the disease.

Currently, malaria burdens mainly poor countries and causes between 300 and 500 million episodes of acute illness globally every year. Not only does malaria affect the poor, it is an important factor in ensuring that many countries and communities remain poor and is a major impediment to progress, particularly in Africa. This paper estimates some of the economic costs of malaria in South Africa and assesses the potential impacts of a ban of one of the most effective weapons against malaria, DDT. 

2. Methodology

An outbreak of malaria carries with it two categories of costs or damages. The first category consists of morbidity and mortality costs, which are made up of productivity losses through lost time and in the case of death, lost future earnings. The second category consists of the costs associated with taking action to avert and to treat the illness. This paper will attempt to measure each of these categories of costs in order to arrive at an estimate of the economic costs of an outbreak of malaria.

Perhaps the most rigorous economic method of valuing the economic costs of an illness is to measure the willingness to pay (WTP) to avoid illness, or the willingness to accept compensation (WTAC) as a result of the illness. Social benefits, or social welfare is made up of the sum of individual's willingness to pay for (or to avoid) change. Illness affects social welfare through the individual's inability to work and to contribute to social welfare. The impact of lost work affects not only the individual, but also the employer, the customers and the rest of society.

To estimate the different impacts on employers, individuals and customers would be extremely complicated, therefore it will be assumed that the interests of the individual are identical to that of the employer and customer. It will be assumed that each malaria sufferer is self-employed and therefore the losses in pre-tax income will be an adequate estimation of the social value of lost work.

Evaluating individuals' preferences towards illness may be a more rigorous approach to establishing the economic costs of a disease, however it relies on detailed information and primary data collection. Because of the time limits to this paper, no attempt will be made to estimate the WTP or WTAC to avoid disease. Rather a cost of illness (COI) approach will be adopted. This will estimate the social losses through lost work and the cost of treating malaria.

These costs will consist of:

(Paul and Mauskopf, 1991 - quoted in Pegram, G.C., Rollins, N., Espey, Q. 1998)

Lack of data will preclude the estimation of all of these costs, however as far as possible, all of these costs will be taken into account.

3. Malaria Incidence in South Africa

Nineteenth century European pioneers and travellers into the Northern Province, Mpumalanga and northern Kwazulu Natal soon recognised the threat and serious impact that malaria could have. Little data is available on the incidence of malaria at this time, however specific studies into the disease in the early twentieth century has shown the devastating effect that the disease had on the economy.

In South Africa, malaria is now only found in the low altitude areas of the Northern Province, Mpumalanga and the north east of Kwazulu Natal Province. The fact that the disease is contained to these areas is due in large part to the vector control programmes, which began in earnest after the Second World War. Prior to this, malaria occurred in much of the North West Province, areas of Gauteng (including Pretoria), much of Kwazulu Natal and even in the Northern Cape - an area five times larger than the area of its present distribution.

In 1905 a malaria epidemic in Durban alone resulted in 4 177 cases and 42 deaths and subsequent epidemics in Kwazulu-Natal and the lowveld (low altitude areas) of the Northern Province and Mpumalanga frequently brought economic activities to a standstill. Because of the changing socio-economic conditions of the country at the time, the impact of malaria was extremely severe. At this time, many labourers were brought into malarial areas to work on railway lines and to develop agricultural areas. Many of these labourers came from non-malarial areas and therefore had no immunity to the disease.

In 1932, malaria incidence extended as far south as Port St. Johns on the Eastern Cape coast, with a reported 22 132 deaths of malaria in Kwazulu Natal for 1932 alone when the population was only 1 819 000, representing a mortality rate of 1.2%. Malaria incidence in the Northern Province and Mpumalanga (then the Transvaal Province) was equally severe during this period. During April 1928 a survey found that 62% of Europeans and 74% of Natives (original terminology) in Rustenburg and Nylstroom were suffering from malaria (Dept of Health, 1997). Heavy rains in 1939 caused a number of outbreaks of malaria, one of the most severe occurring in the Oliphants valley and Sekhukhuneland (Northern Province). This outbreak led to the deaths of 9 311 people out of a population of 1 108 800 (0.8% mortality rate) which devastated farming and economic activities. (Dept. of Health, 1997)

Since the advent of the use of DDT in the vector control programmes (to be described in more detail below) after the Second World War, outbreaks of malaria have not been as serious, nor have they led to the number of deaths as witnessed prior to this period. The combination of agricultural and industrial development in the malarious areas during the 1960s and 70s with the increased concentrations of people in the homeland areas caused a general increase in the number of malaria cases.

A number of severe outbreaks in South Africa occurred following wet summers. One such outbreak in 1953 in the then Transvaal caused the number of infections to increase to 700 and varied from 104 to 251 during the three subsequent years. (Dept of Health, 1997)

Specific data for the number of cases and deaths as a result of malaria have only been kept since 1971 and are presented below. Of the approximate 40 million population of South Africa, 10%, or 4 million people live in a malaria risk area.

Table 1: Annual number of notified cases and deaths from malaria (1971 - 1998)

Year

Cases

Deaths

1971

364

5

1972

1 792

23

1973

331

12

1974

1 623

16

1975

1 821

4

1976

1 747

6

1977

3 513

1

1978

7 103

36

1979

2 022

12

1980

3 109

10

1981

2 343

9

1982

2 184

13

1983

2 130

13

1984

4 642

19

1985

11 358

32

1986

7 491

20

1987

10 374

10

1988

9 317

48

1989

7 055

30

1990

6 822

35

1991

4 693

19

1992

2 872

14

1993

13 285

45

1994

10 289

12

1995

8 750

44

1996

27 035

163

1997

23 120

104

1998

26 382

197

1999 (up to and including March)

15 819

92

Source: Department of Health, Pretoria

There has been a noticeable increase in the number of cases of, and deaths from malaria in recent years. Heavy rains have been experienced throughout South Africa and particularly in the low altitude malarial areas in the last three years. A study performed in the malarial areas showed that for one research station, Makatini, the rainfall and malaria cases were well correlated (r = 0.913, P<0.001), however the relationship for another research station, Ndumu, was far less well correlated (r = 0.643, P>0.05). (Sharp B. et al, 1988). While anecdotal evidence would suggest that the incidence of malaria and rainfall are very closely correlated, research suggests that this relationship is more complex.

Sharp et al, 1988 estimated that for the period between 1976 and 1985, imported malaria cases (mostly from Mozambique) accounted for 19% of the total cases. With the democratic changes in South Africa and the more relaxed policy towards border control, imported cases could account for a significant proportion of the total number of cases. Geographic Information Systems (GIS) for Kwazulu-Natal show markedly increased levels of malaria along the main corridors travelled by Mozambicans through Kwazulu-Natal from the southern border of Mozambique. (pers. comm. Jotham Mthembu, Kwazulu Natal Dept. of Health) Migration from other Southern African countries, such as Zimbabwe, Botswana and Malawi could account for some of the increase in malaria cases in recent years.

A change in the vector control programme, away from the use of DDT, which historically has been extremely successful in malaria control, towards synthetic pyrethroids could also account for some of the increase in malaria cases. A more detailed discussion of DDT and the vector control programme is given below. It is not within the scope of this paper to model the changes in malaria incidence with these factors, however it is accepted that the increases in malaria incidence in South Africa is due to a combination of them. (pers. comm. Danette Lombard, National Dept. of Health)

Age and Gender Analysis of Malaria Cases

In order to accurately estimate the economic impacts of malaria, it is important to know the age groups of malaria sufferers. If malaria occurs mainly in the working population (between the ages of 15 and 65) the disease is likely to incur far higher economic costs than if the disease affects only small children or only the elderly.

Table 2 gives a summary of the percentages of malaria cases within each age group for 1996, 1997 and 1998. In each case, the majority of the malaria cases were in the economically active age group of 15 years to 64 years. The percentages range from a low of 58.02% in 1997 to 62.75% in 1996. A large proportion (as much as 40.51% in 1998) of malaria cases was found in patients below the age of 15 indicating the heavy burden the disease places on children of school going age. Approximately 2.5% of malaria cases were found in people over the age of 65 in 1997 and 1998 and a slightly lower figure of 2.05% in 1996.

Table 2: Age breakdown of malaria cases, South Africa, 1996, 1997 & 1998*

 

1996

1997

1998

 

Age Group

Number of Cases

% cases of total

Number of Cases

% cases of total

Number of Cases

% cases of total

0 to 4 years

2 281

9.54

2 079

10.13

2 419

10.69

4 to 9 years

3 046

12.74

2 854

13.91

3 218

14.22

10 to 14 years

3 073

12.86

3 077

15.00

3 495

15.45

15 to 19 years

4 485

18.76

3 006

14.65

3 053

13.49

20 to 24 years

2 572

10.76

2 307

11.24

2 378

10.51

25 to 29 years

2 063

8.63

1 741

8.49

1 898

8.39

30 to 34 years

1 603

6.71

1 233

6.01

1 408

6.22

35 to 39 years

1 307

5.47

1 142

5.57

1 327

5.86

40 to 44 years

876

3.66

784

3.82

886

3.92

45 to 49 years

811

3.39

633

3.09

702

3.10

50 to 54 years

527

2.20

431

2.10

507

2.24

55 to 59 years

426

1.78

347

1.69

370

1.64

60 to 64 years

328

1.37

279

1.36

354

1.56

65 to 69 years

271

1.13

276

1.35

336

1.48

70 to 74 years

136

0.57

150

0.73

129

0.57

75 to 79 years

50

0.21

55

0.27

63

0.28

> 80 years

32

0.13

29

0.14

51

0.23

Total

23 903

100

20 517

100

22 628

100

Source: Medical Research Council

*Includes data for Northern Province, Mpumalanga and only Northern Kwazulu-Natal. Does not included data for malaria cases outside the three malaria provinces

This age breakdown of malaria cases closely corresponds to the demographic data for the province detailed in Table 3, which gives a age breakdown of the total populations of the three malaria provinces based on the 1996 census. Of the three provinces, approximately 40% of total residents were below the age of 15 and approximately 4.5% of residents were over the age of 65. About 55% of the provinces' residents were between the ages of 15 and 65. This demonstrates how closely the ages of malaria patients correspond to the general age profile of the provinces. It is important to note that the malarial areas form only a part of the total provinces, however there is no reason to believe that the general age breakdown of the malarial areas will differ significantly from the age profile of the provinces as wholes.

Table 3: Summary breakdown of malaria cases age groups, South Africa, 1996, 1997 and 1998

Age Group

Percentage within each group

 

1996

1997

1998

0 - 14

35.21

39.50

40.51

15 - 64

62.75

58.02

56.93

65 and older

2.05

2.49

2.56

Total

100

100

100

Source: Medical Research Council

Table 4: Total population age distribution in five-year intervals by malaria province, 1996

Age Group

Northern Province

Kwazulu-Natal

Mpumalanga

0 to 4 years

646 880

964 546

326 049

4 to 9 years

725 137

1 002 945

338 304

10 to 14 years

708 069

1 018 217

336 576

15 to 19 years

598 061

914 304

298 126

20 to 24 years

452 966

851 952

278 970

25 to 29 years

327 048

684 674

236 320

30 to 34 years

276 249

590 584

210 960

35 to 39 years

230 799

504 757

174 232

40 to 44 years

185 605

408 925

143 256

45 to 49 years

147 688

337 932

105 393

50 to 54 years

110 393

248 877

75 219

55 to 59 years

105 909

212 752

62 586

60 to 64 years

95 180

178 471

48 205

65 to 69 years

100 441

158 207

45 260

70 to 74 years

56 409

95 372

26 875

75 to 79 years

55 466

68 571

24 500

> 80 years

43 888

54 423

18 654

Unspecified

63 181

118 512

49 227

Total

4 929 368

8 417 021

2 800 711

Source: Census 1996, Statistics South Africa.

 

From the census data presented in table 4, it is possible to estimate the relative risks faced by residents in each of the three malarial provinces. By dividing the number of malaria cases in each province by the population (as measured in 1996) an incidence risk for each province is arrived at.

 

Table 5: Risk ratios for the malaria provinces*

Province

1996

1997

1998

Northern Province

0.0011

0.0009

0.0009

Kwazulu-Natal

0.0010

0.0012

0.0014

Mpumalanga

0.0036

0.0021

0.0023

*Each ratio is multiplied by 100.

 

From table 5 it is clear that the risk of infection in Mpumalanga is between 2.6 and 3.4 times higher than in the Northern Province and between 1.6 and 3.4 times higher than Kwazulu-Natal. The higher risk in Mpumalanga could be due to a number of factors, such as climatic differences, or perhaps because of different approaches in the malaria control programme adopted in each of the provinces.

Malaria has never been known to affect either gender more severely and therefore it is assumed that the parasite attacks males and females equally. (pers. comm. Dr. Frank Hansford, Northern Province Dept. of Health) Data from Mpumalanga province shows that the number of cases in males and females is fairly evenly divided, with 44% of cases occurring in females and 55% in males in 1997. The breakdown is more equal in 1998, with 52% female cases and 48% male cases. Traditionally, the role of women in rural areas would have been to care for children and to produce agricultural produce from small household plots or tribal land. With general economic changes and particularly the increased importance of the tourism industry in the malarial areas, women are now playing a more active role in the formal economy. Because of this, no distinction is made between the genders of malaria patients with regard to lost productivity.

Active and Passive Malaria Cases

The provincial departments of health record two broad types of malaria cases, namely active cases and passive cases. Malaria control personnel, who regularly visit households in malarial areas in order to detect cases, record active cases. This active detection of cases involves inquiring about residents with illnesses resembling malaria and taking blood smears from them. Active detection is essential in identifying uncomplicated or mild malaria, particularly in areas where curative health services are not available. Those suffering from uncomplicated malaria are often treated immediately and if someone is found to be suffering from severe or complicated malaria, arrangements are made to transport them to clinics or hospitals.

Passive detection involves the diagnosis and reporting of malaria cases by health personnel at prevention and curative facilities. Again blood smears are taken and laboratories confirm the diagnosis. It is important to note that the reported number of malaria cases is made up only of those cases that are confirmed by taking blood smears. It is highly likely therefore that the true number of malaria cases is higher than reported by the Department of Health. (pers. comm. Danette Lombard, National Dept. of Health)

Because of the nature of active and passive cases of malaria, it would be reasonable to assume that in general, active cases are made up of mild or uncomplicated malaria, as the sufferer has not found it necessary to go directly to a curative facility. Those passive cases, where the sufferer has gone directly to the curative facility can be assumed to be severe or complicated cases. There will obviously be cases where a person suffering from severe malaria and is unable to get to a clinic, but these cases are assumed to be minimal. (pers. comm. Dr. Frank Hansford, Northern Province Dept. of Health)

The proportion of active to passive cases appears to vary between the three malaria provinces. In the Northern Province, for 1996 and 1997, passive cases made up approximately 80% of the total number of cases, while in Kwazulu-Natal, the number of passive cases appear to be of the order of 30%. In Mpumalanga, passive cases made up 65% of the total number of cases in 1995/96, however were much lower (approximately 30% for previous years.) This difference could be due to different levels of effort on behalf of malaria control personnel in the different provinces in finding active cases, or it could be due to different levels of tolerance to the disease in different areas.

Table 6: Active and Passive Malaria Cases

Province

Year

Active

Passive

Total

Mpumalanga

1996

3 560

6 477

10 037

 

1997

1 398

4 516

5 914

 

1998

444

5 894

6 338

Northern Prov.

1996

1 052

4 159

5 211

 

1997

864

3 807

4 671

 

1998

675

3 738

4 413

Kwazulu Natal

1996

5 617

3 076

8 693

 

1997

7 127

2 801

9 928

 

1998

8 460

3 479

11 939

Source: Medical Research Council

 

The data presented in Table 6 includes data for Mpumalanga, Northern Province and only northern Kwazulu-Natal. The data does not include those cases found outside the three malaria provinces or in other areas of Kwazulu-Natal because of data inconsistencies (Medical Research Council).

South Africa's malaria control programme requires that all malaria cases within the three malaria provinces are confirmed and logged. The number of cases is monitored at both a local and national level. There is no requirement however for malaria cases outside these areas to be logged or tracked. A significant number of cases are recorded outside the malaria areas and can be attributed to migrant workers, who are infected in one of the malarial areas and then return to work in a non-malarial area, such as Gauteng. Tourists who visit the malarial areas would also contribute the number of cases outside the three malaria provinces. The total number of reported malaria cases outside the three malaria provinces were 1 097 in 1996, 1 259 in 1997 and 902 in 1998. These cases range between 3% and 5% of the total number of reported cases. It is likely that cases are among the economically active in the major industrial centres of South Africa. It can therefore be assumed that the economic impact, through lost productivity of these cases will be significant and should therefore be taken into account.

4. Malaria Prevention and Control in South Africa

The first malaria control programmes in South Africa began in the 1920s with larval control. Antimalarial committees were set up in Kwazulu-Natal and in the then Transvaal in order to co-ordinate preventative measures. The identification of larval sites was a vital part of this programme, which also encouraged the use of house screens and bed nets.

A report by Professor Swellengrebel, who visited the Kwazulu-Natal in 1930, recommended intensive anti-malarial measures and the principles of species sanitation contained in his report have been followed ever since. (Sharp B, et al. 1998). Certain areas, such as the Ingwavuma, Ubombo and Hlabisa districts of northern Kwazulu-Natal were not considered suitable for anti-malaria programmes because it was feared the natural immunity of the local population would decrease. Oil and Paris Green were used in larval control in the 1930s and continued to be the main method of control until 1946. During this period, many larval sites were drained and frequently eucalyptus trees were planted in order to remove permanently any malaria breeding sites. The South African Railways was extremely pro-active in malaria control, particularly through larval control near its stations. Between 1932 and 1938, the number of malaria infections among railway personnel fell from 1 021 to 57.

Pyrethrum insecticides were introduced for malaria control in 1934 and were sprayed within dwellings during the main transmission periods. The spraying of these insecticides had to be repeated weekly. The use of insecticides proved far more successful in the control of the malaria vector and despite the need for weekly spraying, cost about a third of the larval control programme. (Sharp, B et al. 1998)

The spraying of households with pyrethrums was extended to "native" areas (original wording) in the 1930s whereas before this it was restricted to white rural populations. Where larvicides and pyrethrums were used together, such as in the Springbok flats, which now fall in the Northern Province, the incidence of malaria was greatly reduced.

Malaria continued to be a severe problem while larval control was practised and while pyrethrum house spraying was implemented. It was not until DDT replaced pyrethroids that the vector control programme led to the radical and long-term reduction of malaria cases. In Kwazulu-Natal, the use of DDT began in 1946 and during the next five years, the number of adult vectors caught annually during routine check sprays decreased from 4 621 to 322 (Nethercott, 1974, reported in Dept. of Health, 1997).

DDT is widely acknowledged as the most successful insecticide in malaria control and its use allowed for the economic development of many areas that previously had been restricted because of malaria. After the introduction of DDT in the vector control programme in 1946, the number of cases of malaria in the then Transvaal declined to about one tenth of those reported in 1942/43. In some areas, DDT spraying was reduced and sometimes stopped because of the success it had in vector control. It was only required again after periods of heavy rains when malaria cases tended to rise.

DDT is highly specific and is still considered to be one of the most effective insecticides for several reasons. (Kemm, K. 1999) First, it is affordable and therefore available to many of the poorly developed and under-funded rural areas of South Africa. Second it is easy to mix and apply and therefore relatively little supervision and quality control is needed. When DDT is sprayed onto walls, it leaves a white powdery residue that allows the sprayer to check easily the parts that have been left out. Lastly no immunity of mosquitoes to DDT has been found in South Africa.

5. Local Economies in Malarial Areas

Data from the Development Bank of Southern Africa (DBSA) for 1994 gives a breakdown of the economic activities in the various malarial areas of South Africa. The economies of the three areas where malaria is prevalent are somewhat different. In Kwazulu-Natal and Mpumalanga, agriculture, manufacture, trade and catering and community services are the most important sectors of the economy. In the Northern Province, the mining sector contributes the most in terms of gross geographic product (GGP) with almost a 50% contribution, followed by community services, trade and catering and finance and real estate.

Tourism plays an important part of the economies of most of the malarial areas. The Kruger National Park and the private game reserves that border it comprise the majority of the land area within the malarial areas of the Northern Province and Mpumalanga. There are a number of smaller game reserves and private lodges in northern Kwazulu-Natal, both inland and along the coast. In recent years many cattle ranches in this area have moved over to game farming, either for hunting or game viewing. The Lubombo Spatial Development Initiative (SDI), which is fundamentally a development plan for eastern Swaziland, southern Mozambique and north-eastern Kwazulu-Natal has tourism as its main focus and the basis for future development in the area. The trend towards tourism is therefore likely to continue and to become an even more important sector of the local economy.

Table 7: Gross Geographic Product at factor cost and current prices by kind of economic activity for malarial areas in South Africa. 1994 (R1000)

Province

District

Primary Sector

Secondary Sector

Tertiary Sector

 

Total

 

 

Agriculture Forestry & Fishing

Mining & Quarry

Manufact-uring

Electricity & Water

Constr-uction

Trade Catering

Transport &Comm-unication

Finance & Real Estate

Community Services

 

Kwazulu-Natal

Hlabisa

75 497

442

44 092

0

4 496

68 693

6 344

16 990

21 587

238 141

Ingwavuma

20 839

18 182

690

43

833

216

393

542

11 893

53 633

Mahlabatini

3 306

24 286

2 070

169

1 815

517

1 272

2 954

29 928

66 317

Mtunzini

137 818

4 127

222 970

0

6 645

30 530

20 986

16 547

38322

477 945

Nongoma

6 390

10 264

1 759

132

1 226

509

1 099

1 047

16 875

39 300

Ubombo

4 283

0

670

0

349

5 095

289

1 273

10 109

22 068

Total Kwazulu-Natal 

248 133

57 301

272 251

344

15 364

105 560

30 383

39 353

128 714

897 404

% contribution 

27.6

6.3

30

0.03

1.7

11

3.3

4.4

14

100

Mpumalanga

Nelspruit

247 582

107 507

136 351

6 086

17 983

94 686

79 590

32 278

119 659

841 722

Barbertn

140 731

2 304

750 681

74 359

50 049

330 047

148 982

280 954

179 308

1 957 415

Total Mpumalanga 

388 313

109 811

887 032

80 445

68 032

424 733

228 572

313 232

298 967

2 799 137

% contrib

 

13.8

3.9

31.6

2.8

2.4

15.2

8.2

11.2

10.7

100

Northern Province

Giyani

28 132

1 654

13 354

851

14 477

8 674

3 664

13 273

231 462

315 540

Lulekani

6 335

1 474

7 497

229

8 725

3 802

2 413

5 451

56 534

92 460

Messina

40 593

18 277

8 480

585

1 757

24 404

13 710

18 839

38 668

165 313

Phalaborwa

10 111

1 362 024

14 945

10 248

11 626

74 008

13 537

41 581

119 800

1 657 880

Thohoyandou

35 360

22 313

31 772

22 960

18 845

115 449

9 729

52 861

370 816

680 103

Total Northern Province

120 531

1 405 742

76 048

34 873

55 430

226 337

43 053

132 005

817 280

2 911 296

% contribution

4.1

48.3

2.6

1.2

1.9

7.8

1.5

4.5

28.1

100

Total All Malarial Areas

756 977

1 572 854

1 235 331

115 662

138 826

756 630

302 008

484 590

1 244 961

6 607 837

% contribution

11.5

23.8

18.7

1.8

2.1

11.4

4.6

7.3

18.8

100

Source: DBSA, Kwazulu-Natal Development Profile, 1998. Mpumalanga Development Profile, 1998, Northern Province Development Profile, 1998.

 

Table 8: Sectoral composition of the labour force - magisterial districts in malarial areas, SA, 1994

Province 

District

Total Labour Force

Formally Employed

Unemployed

Active in Informal Employment

Total Labour Force (%)

Formally Employed (%)

Unemployed (%)

Active in Informal Sector (%)

Kwazulu-Natal

 

 

 

 

 

Hlabisa

33 447

16 009

12 286

5 152

100

47.9

36.7

15.4

Ingwavuma

17 903

6 440

8 741

2 722

100

36.0

48.8

15.2

Mahlabatini

24 667

7 963

12 968

3 736

100

32.3

52.6

15.1

Mtunzini

13 185

8 903

2 208

2 074

100

67.5

16.7

15.7

Nongoma

15 777

4 719

8 674

2 384

100

29.9

55.0

15.1

Ubombo

15 889

8 325

6 522

1 042

100

52.4

41.0

6.6

Total Kwazulu-Natal

120 868

52 359

51 399

17 110

100

43.3

42.5

14.2

Mpumalanga

 

Nelspruit

33 019

20 371

8 222

4 426

100

61.7

24.9

13.4

Barberton

38 303

23 403

9 782

5 118

100

60.1

25.5

13.4

Total Mpumalanga

71 322

43 774

18 004

9 544

100

61.4

25.2

13.4

Northern Province

 

 

 

 

Giyani

47 115

16 323

25 969

4 823

100

34.6

55.1

10.2

Lulekani

14 086

4 783

7 663

1 640

100

34.0

54.4

11.6

Messina

16 266

9 455

4 697

2 114

100

58.1

28.9

13.0

Phalaborwa

26 468

16 946

5 990

3 532

100

64.0

22.6

13.3

Thohoyandou

63 292

25 847

31 575

5 870

100

40.8

49.9

9.3

Total Northern Province

167 227

73 354

75 894

17 979

100

43.8

45.4

10.8

Total Malarial areas

359 417

169 487

145 297

44 633

100

47.2

40.4

12.4

Source: DBSA, Kwazulu-Natal Development Profile, 1998. Mpumalanga Development Profile, 1998, Northern Province Development Profile, 1998

 

Table 9: Formal employment by kind of economic activity, malarial areas, 1994

Province

District

Primary Sector

Secondary Sector

Tertiary Sector

Total

 

 

Agriculture Forestry & Fishing

Mining, Quarry

Manufacturing

Electricity, Water

Construc-tion

Trade, Catering

Transport, Communica-tion

Finance,

Real estate

Commun-ity services

 

Kwazulu-Natal

Hlabisa

4 141

302

1 484

89

726

1 419

555

225

7 066

16 009

 

Ingwavuma

1 562

1 048

292

11

266

274

90

57

2 840

6 440

 

Mahlabatini

171

965

604

31

399

452

201

213

4 928

7 963

 

Mtunzini

3 944

6

2 280

23

356

455

181

190

1 469

8 903

 

Nongoma

311

384

483

22

253

418

164

71

2 614

4 719

 

Ubombo

2 522

384

347

42

301

706

189

163

3 671

3 671

Total Kwazulu-Natal

12 651

3 090

5 490

218

2 301

3 724

1 380

918

22 587

52 359

% contribution

24.16

5.90

10.49

0.42

4.39

7.11

2.63

1.75

43.14

100

Mpumalanga

Nelspruit

6 907

571

3 771

308

666

2 264

592

1 157

4 135

20 371

 

Barberton

9 612

5 735

2 480

51

543

1 248

249

271

3 214

23 403

Total Mpumalanga

16 519

6 306

6 251

359

1 209

3 511

841

1 429

7 348

43 774

% contribution

37.74

14.41

14.28

0.82

2.76

8.02

1.92

3.26

16.79

100

Northern Province

Giyani

1 684

714

396

69

697

1 157

236

293

11 077

16 323

 

Lulekani

351

589

206

17

389

469

144

112

2 505

4 783

 

Messina

3 117

1 465

238

8

532

642

149

166

3 136

9 455

 

Phalaborwa

3 111

3 663

564

68

273

1 114

217

407

7 530

16 946

 

Thohoyandou

1 742

590

2 249

190

1 423

2 170

777

702

16 004

25 847

Total Northern Province

10 006

7 021

3 653

353

3 315

5 552

1 523

1 680

40 252

73 354

% contribution

13.64

9.57

4.98

0.48

4.52

7.57

2.08

2.29

54.87

100

Total malarial areas

39 176

16 417

15 394

929

6 825

12 788

3 744

4 027

70 188

169 487

% contribution

23.11

9.69

9.08

0.55

4.03

7.54

2.21

2.38

41.41

100

Source: DBSA, Kwazulu-Natal Development Profile, 1998. Mpumalanga Development Profile, 1998, Northern Province Development Profile, 1998

 

In most of the malarial areas, unemployment is very high and frequently is above 40%. Malaria occurs in many areas that lie in the previous homeland areas, which are generally economically depressed and reliant on small-scale agriculture. Industrial and urban centres such as Gauteng and Durban draw much of its labour from many of these areas and there has been an historic and ongoing pattern of migration from rural areas to urban centres. There are however a number of industries in or surrounding these old homeland areas which provide employment opportunities. Examples of these are Nelspruit in Mpumalanga and Richards Bay in Kwazulu-Natal, which are within malarial areas of intermediate risk.

The informal sector plays an important part in the local economies in the malarial areas, with on average 12% of the total labour force active in this sector. Small scale agriculture and the production of arts and crafts for the tourist market are important sources of income for many households. Because of the nature of this sector, it is however impossible to know what it contributes to the GGP of the area or what the value of lost earnings through illness might be.

Tables 7, 8 and 9 give economic data based on 1994 figures and it is assumed that the basic structure of the economies is unchanged. A number of economic and social changes have taken place in South Africa since 1994, however current data at magisterial district level is unavailable. The figures presented in tables 7, 8 and 9 do not purport to give a complete picture of the local economies. They should however give broad indications of the kinds of economic activities and the employment situation so that a more accurate assessment of the losses in productivity through malaria can be made.

Wage data

The National Productivity Institute (NPI) produces productivity statistics for a number of different sectors of the South African economy. Wage data for the main economic sectors in the malarial areas are summarised below in table 10. In order to determine an accurate average wage rate for the malarial areas, a weighted average, based on the levels of employment in the various sectors within the malarial areas is calculated.

 

Table 10: Annual Earnings per employee, South Africa, 1997

Sector

Year

Earnings per employee (R/yr)

Daily earnings per employee (R/day)

% employment in each sector

Agriculture, forestry and fishing

1996

5 873

25.5

23.11

1997

6 419

27.9

 

1998*

7 015

30.5

 

Mining and quarrying

1996

35 121

152.7

9.69

1997

40 315

175.3

 

1998*

46 277

201.2

 

Manufacturing

1996

40 518

176.2

9.08

1997

46 126

200.5

 

1998*

52 510

228.3

 

Trade, catering and accommodation

1996

51 353

223.3

7.54

1997

55 683

242.1

 

1998*

60 378

262.5

 

Finance, real estate and business services

1996

58 144

252.8

2.38

1997

59 791

259.9

 

1998*

61 484

267.3

 

Services

1996

55 201

240.0

41.41

1997

59 630

259.3

 

1998*

64 414

280.1

 

* estimated, based on % change between 1996 and 1997. Source: NPI, 1998

As the NPI data is based on annual wages, a daily wage is calculated by dividing the annual wage by the number of annual working days. This assumes an average of 20 days leave a year, 11 public holidays and that employees do not work on weekends (104 days) resulting in 230 working days per annum

Based on the above wage data and the percentages of the labour force in the malarial areas, weighted average wages have been calculated for 1996, 1997 and 1998. An 8 hour working day has been assumed in order to calculate the hourly wage rate.

Table 11: Weighted average wages, malarial areas, 1996, 1997 & 1998*

Year

Annual weighted wage rate (R/yr)

Daily weighted wage rate (R/day)

Hourly weighted wage rate (R/hour)

1996

39 626

172.29

21.54

1997

40 466

175.94

21.99

1998*

44 313

192.67

24.08

* estimated, based on % increases between 1996 and 1997.

6. The Economic Costs of Malaria

The economic costs of malaria can be divided into two broad groups, direct costs and indirect costs. Direct costs include the costs to individuals and to the health services of treating and preventing malaria. Indirect costs are the costs to the economy of lost productivity due to malaria, the costs of lost future earnings in the case of death from malaria and costs incurred through days lost in education.

Types of Malaria Cases

In general, two types of malaria cases are treated in South Africa, complicated (or severe) malaria and uncomplicated (or mild) malaria. As their names would suggest, complicated malaria requires more intensive treatment and usually hospitalisation. Uncomplicated malaria symptoms are similar to flu symptoms, with fevers, sweats, body pains and headaches. The symptoms of complicated or severe malaria can include convulsions, severe anaemia, hypoglycaemia, renal failure, sepsis, pneumonia, adult respiratory distress, hyperparasitaemia, hypothermia or circulatory shock. Cerebral malaria can also develop in complicated cases and as with the other symptoms, is life threatening.

Uncomplicated malaria cases are usually treated with drugs in tablet form and more often than not are sent home. All pregnant mothers and children under the age of five are treated in hospital whether they have complicated or uncomplicated malaria. There is a far higher risk of complications developing in these two categories of patients.

Neither the Department of Health, nor regional hospitals and clinics keep accurate data on the number of complicated and uncomplicated cases. The regional malaria control programme offices however do have data on the number of active and passive cases within their regions. As explained above, an active case is one where the malaria control personnel have actively gone into the community and have sought out malaria cases. Active cases usually do not exhibit any severe symptoms of malaria and have not chosen to seek medical attention. Passive cases are those which have actively sought medical attention by coming into clinics or hospitals. These cases are likely to be severe or complicated malaria and are treated with fansidar and chloroquine. Not all passive cases are admitted to hospitals and in fact many are usually sent home to complete the course of treatment.

In order to estimate the economic costs of malaria, it is assumed that all the active cases are treated at home and do not receive any hospital treatment save the drugs given to them by the malaria control personnel. Of the passive cases, 55 percent are assumed to be treated as outpatients and 45 percent are assumed to be admitted to hospital. Of those admitted to hospital, some of the cases will be treated orally with chloroquine and fancidar and some more severe cases will be treated with IV quinine. Those less severe cases will generally be in hospital for 4 days, while the IV quinine patients will be hospitalised for 7 days. (pers. comm. Dr. Ian Cooper, Medical Superintendent, Manguzi Hospital) No accurate data exists on the number of orally treated patients and those IV treated patients, therefore it is assumed that of the total number of cases, 40 percent are treated orally and 5 percent are IV quinine treated.

Direct Costs

Direct costs are made up of the time of medical personnel, cost of drugs to treat malaria victims and the cost of testing for malaria. Every malaria case is different and will require different amounts of attention from medical personnel and different types and quantities of drugs to treat the disease. It has not been possible to collect primary data on the costs incurred in treating malaria cases. The data used are largely estimates from medical practitioners and medical researchers in the field and should be seen as averages and are based on their estimates.

Medical personnel time

In clinics within malarial areas, it is unusual to find medical personnel who are solely dedicated to the treatment of malaria, however in many cases, malaria takes up a significant amount of time. This imposes a direct cost on the health service, as these personnel are no longer available to perform other duties.

Of those passive cases that are treated as outpatients, nursing staff would on average spend 15 minutes with the patient and then a further 15 minutes is spent by medical staff. Of the passive cases admitted to hospital who are able to take quinine treatment orally, nursing staff are likely to spend around 60 minutes in every 24 hours with the patient and 20 minutes on admission. Medical staff are likely to spend 10 minutes in every 24 hours with the patient and 25 minutes on admission. For complicated cases where the patient is unable to take quinine orally and need IV quinine treatment, nursing staff are likely to spend 180 minutes per 24 hours with the patient and medical staff are likely to spend 25 minutes per 24 hours and a further 30 minutes on admission. (pers comm. Justin Wilkins, Dept. of Pharmacology, UCT; Dr. Ian Cooper, Medical Superintended, Manguzi Hospital)

Table 12: Time spent by Health Workers on Malaria Cases

Type of Malaria Case

Time spent receiving treatment

Nursing Care

Medical Care

Uncomplicated

Treated by malaria control personnel

Complicated (treated as outpatient)

30 minutes

15 minutes

15 minutes

Complicated (hospitalised)

4 days

(96 hours)

260 minutes

(4.3 hours)

60 minutes

(1 hour)

Complicated (IV treatment)

7 days

1 290 minutes

(21.5 hours)

205 minutes

(3.4 hours)

 

The uncomplicated malaria cases are treated by malaria control staff, who have a separate budget and the costs for this treatment are included separately.

The time costs are based on the average wages of medical personnel for Shongwe Hospital in Mpumalanga for 1997. (pers. comm. Justin Wilkins, Dept. of Pharmacology, UCT ) It is assumed that these wage costs are applicable in all parts of the country as this hospital is a fair example of the hospitals and treatment centres in all the malarial areas. The average annual cost of employment for medical personnel includes annual fringe benefits and is based on a full range of personnel. The average nursing wages for example take into account the cost of employment of nursing assistants, staff nurses, professional nurses, senior professional nurses and assistant directors. The medical cost of employment is averaged between the cost of employing medical officers and superintendents.

Table 13: Medical and Nursing Costs of Employment

Position

Annual Salary

Daily Salary

Hourly rate

Nursing

46 367

201.60

25.20

Medical

177 591

772.13

96.52

Source: Justin Wilkins

As with the average wage rates for the malarial areas, these medical and nursing costs assume 230 working days per annum and an 8-hour working day.

Drug and Testing Costs

All active and passive malaria cases are given rapid malaria tests, which take approximately five minutes to complete. These rapid tests or parasite F tests only test for Plasmodium falciparum malaria, which makes up approximately 90% of the malaria cases in South Africa. Rapid tests cannot be used to confirm whether or not a malaria patient is free of the parasite after treatment, as the rapid test can remain falsely positive for up to two weeks after treatment. Rapid tests on average cost R10 per test and can normally be completed in five minutes.

Malaria cases are usually tested after treatment, using a smear test, which has to be performed in a laboratory. While the equipment for smear tests is cheaper than the rapid tests, they are far more time consuming and on average take approximately forty minutes to complete. The smears need to be dried and stained - a process that can take up to two hours to complete. The smears are however done in large batches so as to save time. It takes approximately five minutes to view the smear and confirm the results, however the process per slide can take approximately forty minutes to completion. Time is the greatest expense with smear tests, however there are costs of consumables, which are estimated to be R3 per test.

As with the cost of medical personnel, the cost of laboratory technologists is taken from Shongwe Hospital in Mpumalanga for 1997. It is again assumed that the cost of laboratory personnel is equivalent in all malarial areas. The daily and hourly rates are calculated in the same way as with the medical and nursing costs.

 

Table 14: Laboratory Technologist Cost of Employment

Position

Annual Salary

Daily Salary

Hourly rate

Laboratory Technologist

62 319

270.95

33.87

Source: Justin Wilkins

Hospitalisation costs

The costs involved in keeping a patient in hospital are often very significant. Costs are incurred in feeding patients, changing and cleaning bed linen, cleaning and disinfecting floors and walls, swabs and in the use of needles and drips. It is estimated that for the 1997/98 financial year it cost on average R300 per day to keep a patient in Manguzi hospital in Kwazulu-Natal of which R70.32 per day is attributed to medical personnel. The cost of accommodating a patient in hospital, not including medical personnel is therefore R229.77 (pers. comm. Dr. Ian Cooper, Medical Superintedent, Manguzi Hospital). The cost of keeping a patient in hospital per day in most rural hospitals is very similar and it is therefore assumed that it costs R230 per hospitalised patient per day throughout South Africa.

Certain costs are not included in this estimate, such as the cost of transporting emergency malaria cases to larger and more sophisticated hospitals. Anecdotal evidence from Manguzi hospital suggests that a number of malaria patients are transported from this hospital in northern Kwazulu-Natal to larger hospitals in Durban or Richards Bay either by ambulance or helicopter. (pers. comm. Dr. Ian Cooper, Medical Superintendent, Manguzi Hospital) These costs are borne by the hospital (in the case of ambulances) or by the provincial department of health (in the case of helicopters). Due to a lack of data on these costs, they have been omitted from the analysis.

Malaria Control Programme Costs

A large proportion of the costs incurred in detecting and treating malaria cases is in the active malaria control programmes. Malaria control personnel actively locate and treat malaria cases and take rapid tests and smear tests. The budget for the malaria control programme also includes the costs of spraying households with insecticides as part of the vector control programme. Estimates of the expenditure on the national malaria control programme are given below. It must be stated that these figures are estimates of the programme costs done at the beginning of the financial year. No figures are available from the three malaria provinces of the actual amounts spent, which could well be in excess of the figures given here.

Because of changes to the malaria control programme budgeting system, no details of expenditure are available for the 1995/96 and 1996/97 financial years. The expenditure on the programme during these years is however estimated to be lower than the 1997/98 financial year (pers. comm. Danette Lombard, National Dept. of Health). For the purposes of this analysis it is assumed that the expenditure in 1995/96 was R 55 million and in 1996/97 was R60 million.

Table 15: Annual Budget for the Malaria Control Programme, 1997/98 Financial Year

Standard Item

Northern Province

Mpumalanga

Kwazulu-Natal

TOTAL

Personnel

24 532 000

9 010 861

14 761 246

48 304 107

Administration Total

2 341 000

1 881 040

2 287 529

6 509 569

Transport

660 000

1 093 500

1 623 120

3 376 620

Subsistence

1 165 000

666 340

298 883

2 130 223

Other

516 000

121 200

365 526

1 002 726

Stores - Total

5 448 000

1 597 000

5 106 545

12 151 545

Insecticides

3 700 000

1 200 000

700 000

5 600 000

Drugs

500 000

40 000

1 500 000

2 040 000

Rapid tests

50 000

 

2 000 000

2 050 000

Protective clothing

376 000

80 000

521 645

977 645

Other

822 000

277 000

384 900

1 483 900

Equipment - Total

345 000

661 943

147 000

1 153 943

Spraying pumps and spares

n/a

30 000

30 000

60 000

Microscopes

n/a

40 000

60 000

100 000

Other

n/a

n/a

57 000

57 000

Professional Services

196 000

15 000

94 000

305 000

Grand Total (Rand)

32 862 000

13 165 844

22 396 300

68 424 164

 

Indirect Costs

Indirect economic costs of malaria are those that do not entail an immediate cash cost to an organisation, such as the Department of Health. Indirect costs are those costs incurred on the wider economy through, for example, productivity losses through the inability to work. Indirect costs are more difficult to estimate than direct costs, as assumptions have to be made about productivity of malaria victims. Estimates have to be made of mortality costs as well as morbidity costs, which involves estimating the present cost of lost future earnings.

Productivity losses

Wages have been determined according to the published average wages per sector and then weighted according to the levels of employment in those sectors within the malarial areas. The unemployment rate in the areas will have to be taken into account, however it cannot be assumed that those malaria patients that are unemployed will not cause productivity losses. In most rural areas, most household members are involved in some productive activity, be it herding cattle or goats, or working on communal or private land in order to produce agricultural products that are either consumed by the household or sold at market.

Many women are involved in caring for children other than their own (grandchildren, nieces, nephews etc.) which allows women to leave the home and seek employment elsewhere. The illness or death of a child carer can therefore have devastating effects on the employment of such a mother.

As has been shown by the breakdown of the ages of malaria cases and the gender breakdown, malaria is not selective, as the cases closely resemble the demographic pattern of the malarial areas. The age breakdown of malaria cases for 1996, 1997 and 1998 (given in table 6 above) is applied to both active and passive malaria cases. This gives at the number of cases below the age of 15, the number of cases between the age of 15 and 65 and the number of cases over 65.

The malaria cases within the economically active age range (15 to 64) are further divided into those employed, those unemployed and those active the informal sector based on DBSA data (table 8 above). It is assumed that those in formal employment earn the weighted average wage rate as detailed above. It is further assumed that the unemployed earn a basic agricultural wage as they produce agricultural goods on household land and herd cattle and goats. As it is difficult accurately to determine appropriate wage levels for the informal sector, it is assumed that those active in this sector also earn a basic agricultural wage.

Because of the nature of active malaria cases it is assumed that they lose 1 day of productive work. Passive cases that are treated as out patients will usually lose about 4 days of work, as will passive cases that are treated with chloroquine and fancidar in hospital. IV quinine patients who suffer from more severe malaria will lose approximately 7 days work.

It is usual for a member of a household to take time off to care for children with malaria. (pers. comm. Dr. Ian Cooper, Medical Superintendent, Manguzi Hospital) As mentioned above, all children under the age of 5 are automatically hospitalised and it is assumed that on average the length of stay in hospital will again be 4 days. During this time, it is further assumed that one adult will lose an equivalent amount of productive time. For those children between the ages of 6 and 15 that are treated as outpatients, it is likely that an adult will be able to perform some of the usual productive activities, therefore 2 days of lost productivity are assumed. Because of the supportive extended family in most rural areas of South Africa, it is assumed that carers are not formally employed, but are members of the immediate or extended family who are able to afford the time to care. The productivity losses are therefore estimated at agricultural wages.

Anecdotal evidence from residents in the Jozini area of Kwazulu-Natal suggests that in certain clinics and hospitals, family members are required to care for malaria patients of all ages due to a shortage of nursing staff. (pers. comm. Mr. J. Gumede, Jozini resident) As this has not been officially confirmed, these potential lost productive days have not been included.

Educational costs

A number of studies have associated malaria with poor cognitive development, anaemia, epileptic convulsions and faltering growth in the first three years of life (Chima et al, 1999). Schiff et al. (1996) (reported in Chima et al. 1999) showed that children who were not protected by impregnated bed nets grew less in a 5 month period and were twice as likely to be anaemic as protected children. Strong evidence has been shown between iron deficiency anaemia and poor performance in infant development scales, IQ and learning tasks in pre-school children and educational achievement among school-age children. (Pollitt 1993; Pollitt 1997; Soewondo et al. 1989 - reported in Chima et al. 1999).

Malaria is reported to be the single most important cause of epileptic seizures in early childhood, with 31.3% of seizures attributed to malaria in Kenya while in Zimbabwe the figure is lower, at 16% (Chima et al, 1999). The impact of epileptic seizures on the cognitive ability of children is serious and can cause serious learning disabilities and reduced school attendance. (Chima et al. 1999).

Cerebral malaria can result in approximately 10% of children having residual neurological sequelae that can produce intellectual impairment. Cerebral malaria has also been found to be responsible for cerebral palsy and blindness in children (Brewster et al, 1990 - reported in Chima et al. 1999)

The losses in school days, impaired cognitive abilities and the ability to reason could affect future productivity and earnings. No direct evidence is however available to support this assertion (Chima et al, 1999) and more research is necessary before any estimate of these costs can be estimated.

Mortality costs

For every malaria patient that dies, costs are incurred to the economy due to lost future productivity. An estimate of these mortality cost will entail calculating the present value of future earnings. A real discount rate of approximately 10% is used in this calculation, based on real interest rates of 20% and an inflation rate of 9%.

No data is available on a national basis of the ages of malaria deaths, however limited data for the province of Mpumalanga is available for 1997 and 1998. This data (contained in table 16 below) gives the number of deaths from malaria in the province for these 2 years, within 5 yearly intervals.

It is assumed that each death occurs in the median year of each age group and on this basis, the average age of death for 1997 was 30.3 years and for 1998 was 35.6 years. It is assumed that the retirement age is 65, which results in 34.7 years of lost productivity for 1997 and 29.4 years of lost productivity for 1998. As no data for the country as a whole is available, the estimated average age of death for Mpumalanga is used for both years for the whole country. In addition, in order to estimate mortality costs for 1996, the 1997 average age of death is assumed for this year.

Table 16: Age breakdown of malaria cases and deaths, Mpumalanga, 1997 and 1998

Age Group

1997

1998

 

Number of Cases

Deaths

% cases of total

Number of Cases

Deaths

% cases of total

0 to 4 years

442

3

7.4

616

1

9.7

4 to 9 years

684

2

11.5

719

1

11.3

10 to 14 years

737

0

12.5

857

1

13.5

15 to 19 years

1 001

0

16.9

884

2

13.9

20 to 24 years

769

2

13

758

1

11.9

25 to 29 years

617

0

10.4

618

2

9.7

30 to 34 years

428

2

7.2

476

5

7.5

35 to 39 years

376

2

6.3

413

1

6.5

40 to 44 years

261

0

4.4

307

3

4.8

45 to 49 years

182

0

3.0

194

1

3.0

50 to 54 years

122

0

2.0

144

2

2.2

55 to 59 years

109

0

1.8

106

1

1.6

60 to 64 years

82

0

1.3

107

0

1.6

65 to 69 years

61

0

1.0

74

1

1.1

70 to 74 years

28

0

0.47

26

1

0.4

75 to 79 years

10

0

0.16

13

1

0.2

> 80 years

5

0

0.08

8

0

0.12

Total

5 914

11

100

6320

24

100

Source: Mpumalanga Department of Health

For every death however there are costs, which could be borne by the government that are saved. These costs could include future health costs, pension costs and general welfare payments. No estimate is made of these cost savings, which could be considerable, however they should be borne in mind.

Malaria Patients outside the Malaria Provinces

Frequently visitors to malarial areas return home, or in the case of migrant workers, to their place of work, and only then do they show the symptoms of malaria. As pointed out above, because the non-malaria provinces are outside the malaria control programme, the reporting on these cases is less systematic. For the purposes of this study, it is assumed that all the cases of malaria outside the malaria provinces are treated in hospital for 4 days, using chloroquine and fancidar treatment. The costs of treatment are assumed to be the same as in the malaria provinces, however this could be an underestimation as usually the costs of treatment in urban centres is higher than in rural areas.

In order to estimate lost productivity, the same average wage rate as in the malaria provinces is used. As there is no data giving the location of the malaria patients outside the malarial areas, it is not possible to adjust the wage rate accordingly. It is also assumed that no family care is necessary for those patients outside the malaria provinces.

Additional Economic Costs

A number of additional economic costs are incurred by malaria that have not been quantified in this analysis. One cost for example is the lost productivity incurred through the attendance of funerals of malaria victims. In South Africa funerals are usually attended by most or all of the extended family and by large numbers of neighbours and friends. While funerals are usually held on weekends, costs will be incurred by family members travelling from urban centres to rural areas and will frequently be required to take time off work. In many farms and factories, the whole workforce will take time off to attend funerals, which can disrupt production and therefore incur costs.

Malaria could have an impact on the tourism industry, especially as tourists have recently become more aware of the high levels of malaria and the danger that it poses. Tourists are usually required to take antimalarial drugs, such as chloroquine (trade names: Anoclor, Daramal, Nivaquine, Plasmoquine or Promal) and proguanil (trade name: Paludrine). An alternative drug is mefloquine (trade name Lariam) which should be prescribed by a doctor. Some of these drugs can cause serious side effects, such as nausea, vomiting and diarrhoea in the case of chloroquine and proguanil. Lariam can cause more serious side effects to the nervous system and has been known to cause hallucinations and trembling of the body. It is because of these serious side effects to the nervous system that Lariam can only be prescribed by a doctor. The danger of contracting malaria and the side effects from the antimalarial drugs are likely to deter a number of tourists from visiting malarial areas. It is interesting to note that many of the non-malarial tourist areas in South Africa, such as the Waterberg nature areas in the Northern Province prominently promote the fact that they are non-malarial.

These economic costs have not been quantified, however they should be borne in mind, particularly as tourism is growing in importance for the South African economy and in areas such as northern Kwazulu-Natal is the main focus of economic development. Tourism accounts for between 7% and 8% of South Africa's GDP and wildlife tourism is thought to constitute a significant portion of this. (pers. comm. Lee Ann Bac, Grant Thornton Kessel Feinstein.)

Households living in malarial areas could incur certain costs through expenses on preventative measures. These measures could be purchasing of mosquito repellents, insecticides, door and window screens and bed nets. While some wealthier residents in malarial areas could purchase some of these items, preventative measures are not widely taken and therefore this cost has not been estimated. (pers. comm. Jotham Mthembu, Kwazulu-Natal Dept. of Health)

Summary of Economic Costs

Appendix A contains detailed workings of the estimated economic costs of malaria in South Africa. A summary of the direct and indirect costs is given in table 17 below.

The estimated economic cost of malaria, which take into consideration only part of the economic costs, are considerable. In 1998 malaria cost approximately R124 million (US$ 20.3 million) in direct and indirect costs. The figures for 1997 and 1996 are lower at R 95 million (US$ 15 million) and R102 million (US$ 16 million) respectively. A large portion of the economic costs is incurred in the national malaria control programme, which actively treats and seeks to prevent malaria and in the lost future earnings brought about by malaria deaths.

Table 17: Summary of Economic Costs of Malaria

Type of Cost

1996 (Rand)

1997 (Rand)

1998 (Rand)

Number of malaria cases

23 907

20 513

22 690

Direct Costs

 

 

 

Malaria Control Programme

55 000 000

60 000 000

68 424 164

Cost of treating and hospitalising patients

7 171 599

5 653 828

5 902 062

Indirect Costs

 

 

 

Malaria patient lost productivity

6 640 120

6 166 245

6 016 356

Carer - lost productivity

138 803

157 737

190 689

Mortality costs

31 993 131

20 845 528

42 438 360

Cases outside malarial areas

2 006 771

2 321 515

1 663 230

TOTALS

102 950 427

95 144 855

124 634 863

Cost per case

4 304

4 638

5 492

 

While these economic costs have been calculated in order to reflect the local economic conditions as closely as possible, a number of assumptions (as detailed above) have had to be made. The economic costs are only estimates that rely on secondary data and information and do not purport to be the full economic costs of the disease. Because of time constraints no primary data collection from malaria patients has been done in order to verify the results. No attempt has been made to quantify the social costs of malaria in terms of inconvenience, pain and the reduction in quality of life of malaria patients and their families. These costs should therefore be viewed cautiously, as conservative estimates of the partial economic cost of malaria in South Africa.

Economic Costs of Malaria in other parts of Africa

The World Health Organisation has estimated that malaria causes over a million deaths a year mainly in African children and is responsible for between 300 and 500 million cases of acute illness globally, including Asia and the Americas. Accurate data on the actual number of cases and deaths specifically resulting from malaria are however not available.

Between countries, there are differences in the methods of defining malaria cases and therefore it is difficult to interpret the number of cases from other African countries with those from South Africa.

In most Southern African countries, malaria cases are only confirmed with blood smear tests once patients are admitted to hospital. The total number of cases reported includes all cases that are classified as malaria based on the symptoms of the patient. Because of this, the number of cases could be exaggerated because of the fact that other diseases with malaria-like symptoms could be classified as malaria. By the same token, the number of cases in South Africa could be underestimated, as only cases that are confirmed by quick F tests or blood smear tests are included.

Table 18 gives the number of estimated malaria cases for certain Southern African countries for 1998, based on data held by malaria control personnel in those countries. This data must be viewed with caution for the reasons given above and should only be seen as estimates. No data is available from Botswana and no clinical reports of malaria cases are available for Mozambique.

Table 18: Malaria cases in selected Southern African countries

Country

Population

% exposed to malaria (%)

Population exposed to malaria

Estimated number of malaria cases

Mozambique

15 000 000

100

15 000 000

N/a

Namibia

1 700 000

60

1 020 000

400 000

Swaziland

900 000

33

300 000

30 000

Tanzania

30 000 000

95

28 500 000

12 000 000

Zambia

10 000 000

100

10 000 000

2 000 000

Zimbabwe

12 500 000

33

4 160 000

880 000

TOTAL

70 100 000

 

58 980 000

15 310 000

Source: Pers. comm. Danette Lombard, National Department of Health

 No data are available on the wage levels in malarial areas of the other Southern African countries. South African wage levels are generally higher than those in most other Southern African countries, therefore the wage level used is half that of the average South African wage. While there are more accurate ways of determining the wage levels, the constraints of this paper preclude any more accurate wage analysis.

Certain other African countries, such as Zambia, do not have malaria control programmes as in South Africa. A strategy of increasing the resistance to malaria in endemic areas is rather pursued and a programme that eradicates the malaria vector could disrupt this process. Because of this, no malaria control programme costs are included. Costs of treatment are assumed to be similar to South Africa as are the number of days spent incapacitated.

No age breakdown of the above cases is available and it is likely that a large proportion of the cases comprise children under the age of 15. As in South Africa, family members will be required to care for malaria patients, particularly children. Due to financial limitations, the health services in Southern African countries (other than South Africa) are likely to be highly dependent on family members to care for malaria patients that are admitted to hospital. Because of this, for every malaria case it is assumed that one adult days work is lost. Not all malaria cases in Southern Africa will be treated with Fancidar and Chloroquine, while others will receive no medical attention at all. Due to a lack of accurate data, the cost of treating patients will be restricted to the cost of a treatment of Chloroquine (R 0.98/treatment). No cost data on hospital costs are available, therefore these costs are omitted.

On this basis, the total economic cost of malaria in other Southern African countries is estimated to be approximately R 5 900 million, or US$ 967 million. These figures should be viewed with caution because of inaccuracies in the reported number of cases and because of the assumptions wages and medical costs. While the figures presented here could exaggerate the real economic cost of malaria in Southern Africa, they are within reasonably close limits to the estimate of US$ 791 million estimated by Shepard et al (reported in Chima et al, 1999) for the whole of Africa in 1987.

Table 19: Estimates of the Economic Cost of Malaria for Selected Southern African Countries

Country

Number of Cases

Lost productivity Costs

(million R)

Medical treatment costs (fancidar & chloroquine)

(million R)

TOTAL

(million R)

Namibia

400 000

154.14

9.50

163.62

Swaziland

30 000

11.56

0.70

12.27

Tanzania

12 000 000

4 624.07

284.00

4 908.58

Zambia

2 000 000

770.67

47.40

818.09

Zimbabwe

880 000

339.09

20.86

359.96

TOTAL

15 310 000

5 899.54

363.00

6 262.54

 

The economic cost of malaria to Southern Africa is extremely high and while there are likely to be inconsistencies and inaccuracies in the way in which costs have been calculated, the costs are high and could be as much as 4 % of the region's combined GDP. Given that most of the Southern African countries featured are heavily reliant on agriculture and other relatively labour intensive economic activities, the impact of malaria on the economy is likely to be very severe.

7. The Impacts of DDT and Alternatives for Malaria Control

As mentioned above, DDT is widely recognised as being the most effective insecticide in malaria vector control. To date no studies have been performed in South Africa that analyse the relationship between the incidence of malaria and the use of DDT. Anecdotal evidence however from a number of specialist researchers, health workers and malaria control personnel confirm that DDT has been the single most important and effective factor in controlling malaria in the past.

Conclusive evidence has however emerged in a study on the use of DDT in South America which shows a statistically significant negative relationship between the rate of house-spraying with DDT and annual parasite indices (API). (Roberts, D et al.) In modelling the relationship between house-spray rates (HSR) and the API for 28 years of data from Brazil, a regression model produced an excellent fit (F = 354; df = (2.26); p<0.0001). The same regression analysis was performed in Ecuador which again produced an excellent fit (F= 45.6; df = (2,30); p < 0.0001) showing the powerful relationship between DDT-sprayed houses and malaria rates. The analysis also shows that when large numbers of houses are sprayed with DDT, malaria rates decline and when fewer houses are sprayed, malaria rates increase. Many countries in South America have recently discontinued house spraying with DDT and have reported large increases in malaria cases. The only country that has increased the use of DDT since 1993 has been Ecuador which has reported a very substantial decrease (61%) in malaria rates since 1993. (Roberts, D et al)

While DDT may be a highly effective weapon against malaria in Africa, South America and Asia, evidence does exist showing certain negative biophysical impacts and certain negative implications for human health. These potential impacts are discussed in turn.

Biophysical impacts of DDT

A number of recent studies have been performed in South Africa, mainly in the Kwazulu-Natal region which have attempted to assess the impact of DDT on plant and animal life. The area in which the studies were performed is very rich in biodiversity and has unique topographic, geologic and climatic features. It is also an area that has extremely high incidences of malaria and that has been the focus of DDT vector control for approximately 50 years.

In a study (Bouwmann et al. 1990) on the health implications on fish in the Pongola Flood plain in northern Kwazulu-Natal, the levels of p,p'-DDT and its metabolites, p,p'DDE and p,p'DDD were tested in three species piscivorous fish, the tigerfish (Hydrocynus vittatus), the blue kurper (Oreochromis mossamibicus) and the butter catfish (Eutropius depressirostris). The tigerfish is the major piscivorous fish in the system, while the other two species are more omnivorous, eating plant matter, diatoms and algae, insects, young fish and shrimp. Importantly all three species are utilised by the local populations and in many cases represent the major form of protein.

At the time, DDT was applied in house spraying between January and March every year as part of the malaria control programme. DDT was used as an agricultural pesticide in the area, however this use was ceased when the pesticide was banned as an agricultural pesticide in 1974. Tests were performed on the fish species before and after the use of DDT in the area.

The results of this study show that the levels of DDT contamination in the major piscivorous fish are approximately three times higher than the level of contamination in other fish species. This would seem to support the theory of bioaccumulation, in other words that DDT accumulates in higher concentrations in higher order species. Caution however must be exercised with this result as the low number of tigerfish tested prevents meaningful statistical analysis. It is important to note that the levels of DDT found in the study on tigerfish and the other fish species do not pose any threat to human health.

The highest concentrations of DDT and its metabolites DDE and DDD were found in pan closest to the malaria control camp, where DDT was stored and mixed. It is likely that DDT containers were washed out in this pan, leading to higher than normal levels. Simple changes to the way the camp is managed would however prevent future contamination.

As mentioned above, tigerfish are used by local populations and are also preyed upon by the African fish eagle and possibly the Nile crocodile. The implications of the higher levels of DDT in higher order species can only be inferred. No studies have been performed in South Africa that has looked at the effect of species population as a result of DDT use. Some studies in Zimbabwe have shown that levels of DDT in crocodile eggs are at levels that would point to bioaccumulation at levels higher than the tigerfish.

Many of the studies into the effects of DDT in South Africa have been piecemeal and so the potential impacts on higher order species can only be inferred from other studies, in South Africa and abroad. Levels of DDT have been found an egg of the African fish eagle from Kariba Island in Zimbabwe (Tannock et al, 1983 reported in Bouwman et al, 1990) which affect the reproductive ability of the raptor (this conclusion is however based on the study of only one egg). The African fish eagle is however known to be a strong reproducer and in actuality no direct impact on its population has been found. (pers. comm. Dr. Henk. Bouwman, Head, Unit for Pesticide Impact, ARC ).

Unlike the United States and Europe, the highest levels of DDT have not been found in predatory birds, rather in insectivorous birds. The reason for this is most probably because many insectivorous birds feed and nest near human habitation, where there are higher insect populations. With household DDT spraying, the levels of DDT are therefore likely to accumulate in insectivorous birds via insects.

More research is necessary to determine the impact that DDT and its metabolites DDE and DDD are likely to have on actual animal populations. The conclusions that are made in studies on DDT levels only make inferences on the potential impacts of animal populations based on other studies performed internationally. While DDT may have certain negative biophysical impacts, the actual effect that these impacts will have on actual animal populations is uncertain. It is however important to point out that in the approximately 50 years of DDT use in South Africa, no-DDT induced change in bird populations or breeding cycles, nor-DDT induced egg shell thinning has been recorded. (Kemm, K. 1999)

Human health impacts of DDT

Because of the variety of applications of DDT and its widespread use, almost everyone born since the mid 1940s has had some exposure to the insecticide. Humans can be exposed to DDT in a number of ways, however perhaps the most common way in the areas where malaria vector control spraying occurs is through the air. DDT can also be accumulated in the body by eating contaminated fish, food, milk and water. DDT is poorly absorbed through the skin, making it a relatively safe insecticide to handle. (Smit et al, 1992)

DDT tends to accumulate in the adipose tissue of humans, mainly because of the high fat:water partition coefficients of DDT and DDE. When DDT was extensively used in the United States, the average storage level of DDT in human fat was about 5 parts per million (ppm). This level however was reduced sharply to between 1 and 2 ppm by the late 1960s when the use of DDT was greatly reduced.

A study was undertaken examining the serum levels of DDT and liver function of malaria control personnel in Kwazulu-Natal. (Bouwman et al, 1991) It was revealed that the levels of DDT among the malaria control personnel were far higher than that of an aged match sample of the general population in the province who were exposed to DDT through the malaria vector control programme. The study showed that despite the higher levels of DDT in the malaria control personnel, the levels were still within the laboratory normal range and therefore do not represent significant health risks. Reports on the exposure of factory formulators of DDT, who are normally exposed to far higher concentrations of DDT show the lack of risk from the pesticide, even at very high body burdens. (Bouwman et al, 1991)

The impact of DDT and its metabolites on infants has been the focus of a number of studies in South Africa. Infants ingest DDT through breast milk, and because most mothers breast-feed for up to two years in rural communities, the total transfer of DDT can reach levels that theoretically could have damaging side effects. Infants for whom the intake of DDT exceeds 0.0037 mg/kg per day could be exposed to neurotoxic effects. Because of the immaturity of the kidneys and liver functions and the underdeveloped protective barrier of the central nervous system, the safety factor for infants appears to be smaller than for adults. (Smit et al. 1992)

A study done in Kwazulu-Natal has shown that for infants, the mean intake of DDT was between 20 and 75 times higher than the allowable daily intake for adults. (Bouwman et al.1992). The impacts of this have not been adequately researched, however the dosages may result in detrimental effects, such as hypo-reflexia.

Many studies have been performed examining the possible carcinogenic impact of DDT on humans, however there is no evidence that elevated levels of DDT in body fat either caused cancer, or were caused by cancer. A study by Tomatis (reported in Smit et al. 1992) on the carcinogenic risk of chemicals to humans listed 17 chemicals as having carcinogenicity, however not one of these was a pesticide.

In assessing the potential negative human health impacts of DDT and its' metabolites, it is important to stress again that in all the years of use of DDT in malaria vector control, no negative side effects from malaria control personnel or from residents within malaria control areas have been reported. (pers. comm. Dr. Frank Hansford, Northern Province Dept. of Health; Mr Jotham Mthembu, Kwazulu-Natal Dept. of Health)

The Move Away from DDT

Currently in South Africa, DDT is used only in vector control only in the Northern Province and there only existing stocks are being run down with no plans to replace them. DDT has been withdrawn from the vector control programme for a number of reasons.

Firstly, environmental pressure, both nationally and internationally has forced the Department of Health to reassess the use of DDT. Environmental pressure against DDT began in earnest in the 1960s in the United States and led to the banning of DDT in agricultural use in 1974. Although many of the arguments put forward by environmentalist groups were not based on fact, the ban was upheld. (Kemm K., 1999) The US has continued to put pressure on other countries to ban the substance by threatening not to import agricultural produce and related goods if DDT was not banned.

In South Africa, it has been reported that a major consideration for ceasing to use DDT in malaria vector control is so as not to deter foreign tourists. (pers. comm. Jotham Mthembu, Kwazulu-Natal Dept. of Health) As has been explained above, most of the malarial areas in South Africa fall within the major tourist destinations where there are game and nature reserves. The knowledge that DDT is used in this environment could potentially turn tourists away who had preconceived ideas of a pristine natural environment. (pers. comm. Jotham Mthembu, Kwazulu-Natal Dept. of Health) This is despite the fact that malaria itself poses a serious danger to tourists who have no immunity to the disease and who are required to take prophylactic drugs which frequently have unpleasant side effects.

Secondly, DDT is said to irritate and increase the activities of bed bugs in households that are sprayed. This increase in bed bug activity has led to certain household members refusing access to malaria control personnel who are then unable to spray. Insecticides, such as Fenitrothrion have been used very successfully against bed bugs and should be used to mitigate this negative impact.(Sharp B. et al. 1988)

Thirdly, DDT is only effective on porous walls, such as the mud-plastered walls. As rural areas become more developed, more and more people are building cement and brick houses with plastered and painted walls which are unsuitable for DDT. More and more rural households have furniture on which, it is suspected, mosquitoes rest. Spraying furniture with DDT could damage it and therefore would be very unpopular. (pers. comm. Danette Lombard, National Dept. of Health, Dr. Frank Hansford, Northern Province Department of Health)

Lastly, DDT stains walls white and although this makes quality control of spraying extremely easy, some householders find the staining unacceptable and tend to re-plaster after the malaria control personnel have left. The re-plastering covers over the DDT residue and therefore leaves it ineffective.

After taking the above factors into consideration, the South African Department of Health has sought alternatives to DDT, which, as explained below, may have some advantages, however their unqualified superiority over DDT is questionable.

Botswana has used DDT in its malaria control programme for many years, however recently has been forced to use synthetic pyrethroids because DDT is now produced in such small quantities that it has had difficulty obtaining it. (pers. comm. Dr. Themba Moeti, Head of Communicable Diseases, Ministry of Health, Gabarone)

Alternatives to DDT

DDT is not the only pesticide that can be used in vector control, indeed deltamethryn, a synthetic pyrethroid, is currently being used in vector control in South Africa. Like DDT, deltamethryn is highly toxic to insects and has a low toxicity to humans, however it is biodegradable and should not bioaccumulate as does DDT. Deltamethryn does not leave any stains on walls and therefore should be more acceptable to householders who found the DDT staining unacceptable.

Deltamethryn does not appear to irritate bed bugs and therefore increase their activity and it can also be used on modern painted walls, were DDT cannot. There are however a number of drawbacks to the use of deltamethryn.

Deltamethryn and all the other synthetic pyrethroids cost significantly more than DDT. The Department of Health quotes a cost of 5.35 cents/m2 for DDT between 1 April 1995 and 31 March 1997, while deltamethryn during the same period is quoted as cost between 6.06 cents/m2 and 7.23 cents/m2. According to Kwazulu-Natal regional department of health, the cost of deltamethryn is now 11.28 cents/m2 (pers. comm. Jotham Mthembu, Kwazulu-Natal Dept. of Health). The published prices of other synthetic pyrethroids vary between 10.18 cents/m2 and 20.59 cents/m2. While the price of DDT may have increased since this period, it is still widely recognised as being one of the most cost-effective insecticides.

As mentioned above deltamethryn has advantages over DDT in that it does not stain walls, however this can result in a serious quality control problem. Once sprayed, deltamethryn cannot be seen and therefore it is difficult to know how consistently walls have been sprayed, or indeed if they have been sprayed at all. In some instances, houses have been sprayed twice because of this uncertainty which adds greatly to the expense of the malaria control programme. (pers. comm Jotham Mthembu, Kwazulu-Natal, Dept. of Health)

While a number of international studies have been performed to assess the potential biophysical and human health impacts of synthetic pyrethroids, no studies have been performed in South Africa. Because of the different climatic conditions in South Africa, neither the rate of breakdown, nor the impact on the environment of the insecticides is known. Evidence has shown that synthetic pyrethroids have an effect on the neuro-transmitters of animals and there is potential for synergism between DDT and pyrethroids.(pers. comm. Dr. Henk Bouwman, Head, Unit for Pesticide Impact, ARC). Synergism occurs when two agents react and produce an effect that is greater than the additive effect of the two agents. For example, if the effect of agent A is 1 and the effect of agent B is 1, the additive effect is 2. The synergistic effect on the other hand would, for example, be 3. Synergism has been found between DDT and synthetic pyrethroids, however the clinical significance of this synergism has not been studied. (pers. comm. Dr. Henk Bouwman Head, Unit for Pesticide Impact, ARC).

Synthetic pyrethroids are currently used in agriculture, particularly on cotton and in small scale farming. It is possible that Anopheles mosquitoes will develop resistance to the insecticide. If this occurs, there could be a return to the use of DDT in vector control, however there is a danger that resistance to synthetic pyrethroids could instigate cross-resistance to DDT, depending on the genes that are affected.

8. Current Malaria Control Policy

South Africa's Malaria Control Policy

South Africa's malaria control policy aims to maintain a malaria case fatality rate below 0.5% and to reduce the incidence of indigenous malaria to below 100 cases per 100 000 people per year. In order to achieve this, the basic elements of the strategy are:

  1. To provide early diagnosis and prompt treatment
  2. To plan and implement selective and sustainable preventive measures, including vector control, on the basis of the malaria surveillance information.
  3. To detect epidemics early and to prevent or contain them.
  4. To strengthen capacity in evaluation, basic and applied research in order to

(i) promote the regular assessment of the malaria situation, in particular the ecological, social and economic determinants of the disease, and

(ii) encourage improvements in the control of malaria.

  1. To develop human resource capacity at all levels in the malaria control programme by appropriate training, motivation and other means.

(Department of Health, 1995)

The two main focuses of this strategy are in disease management, which entails detecting, diagnosing and treating malaria cases and disease prevention, which includes vector control, parasite control and the protection of individuals. The vector control programme concentrates on identifying high risk areas and spraying structures with residual insecticides. Parasite control involves identifying and treating people that are infected with the parasite in order to disrupt the parasite's lifecycle and reduce the rate of transmission. Protecting individuals by preventing malaria bites is recommended and various trials testing the feasibility of insecticide impregnated bed nets are underway in South Africa. Chemoprophylaxis is an option available for the protection of individuals, however due to their high cost and the fact that they are not 100% effective, they should only be used after considering the risk benefit ratio.

The National Department of Health is no longer promoting the use of DDT for the reasons given above, but rather promotes synthetic pryrethroids such as deltamethrin and cyfluthrin for vector control.

Table 20 below gives the quantities of insecticide used for indoor spraying for the three provinces during the 1997/98 season. The table also shows the expenditure on each insecticide, based on the published prices at the time of spraying. It is interesting to note that the only province to still use DDT, the Northern Province, managed to spray 3.6 times the number of dwellings as Kwazulu-Natal and almost 7 times the number of dwellings as Mpumalanga. Not only did it spray more dwellings, but it managed to do so at a lower cost per household. These costs do not take into account the fact that synthetic pyrethroids could require more quality control than DDT and thereby increasing the cost of application still further.

Table 20: Amounts and Costs of Insecticides for Indoor Spraying during 1997/98 season.*

Insecticide

Northern Province

Mpumalanga

Kwazulu-Natal

DDT

Amount sprayed (kg)

82 791

0

0

Cost (Rand)

 

1 661 615

0

0

Deltamethrin

Amount sprayed (kg)

68

1 861

6 641

Cost (Rand)

 

12 291

336 375

1 200 360

Cyfluthrin

Amount sprayed (kg)

1 350

356

0

Cost (Rand)

 

1 389 501

366 416

0

Total number of structures sprayed

Total number of structures sprayed

900 024

131 870

244 271

Total cost

Total cost

3 063 407

702 791

1 200 360

Cost per structure (Rand/structure)

Cost per structure (Rand/structure)

3.4

5.3

4.9

Source: Department of Health

* Costs calculated as follows: 1Kg DDT = R20.07, 1Kg Deltamethrin = R180.75, 1Kg Cyfluthrin = R1 029.26. Source: Department of Health, 1996a

During this season, the number of malaria cases in the Northern Province was well below that of either of the other provinces and was in fact consistently lower than the other provinces for the two preceding seasons.

Table 21: Provincial comparison of malaria cases, 1995/96, 1996/97 & 1997/98 seasons

Season

Northern Province

Mpumalanga

Kwazulu-Natal

1995/96

3 536

9 434

10 266

1996/97

5 942

6 778

10 012

1997/98

3 171

6 122

13 972

Source: Department of Health

It is impossible to say how important DDT has been in ensuring that the Northern Province maintains the lowest levels of malaria as numerous factors contribute to malaria incidence. The fact however that over 900 000 structures were sprayed (not only with DDT) would tend to suggest that it does play an important role.

International malaria initiatives

The recent rise in the number of malaria cases, particularly in Africa, has prompted the World Health Organisation to initiate its Roll Back Malaria (RBM) programme. The RBM programme is designed to act as an umbrella under which the various malaria programmes, such as the Multilateral Research Initiative on Malaria can operate and builds on the Global Malaria Control Strategy (GMCS). The GMCS is made up of four technical elements:

(WHO, 1998)

The RBM strategies will be based on regional, epidemiological and health systems needs and objectives and will focus on community and district level action.

Case management has for many years been the mainstay of most malaria control programmes in the majority of high-risk malarial areas. (pers. comm. Brian Sharp, South African Medical Research Centre) The current main focus of vector control is in the use of insecticide-treated mosquito nets (ITMNs) which have been shown in various studies to be effective in controlling malaria. (pers. comm. Brian Sharp, South African Medical Research Centre) The ITMN programme has been successfully introduced in Tanzania and as all the nets are locally produced, it has generated additional economic activity. The ITMN programme has only recently been initiated in South Africa and the early perceptions are that the success is limited and that they are not being widely used (pers. comm. Jotham Mthembu, Kwazulu-Natal Department of Health)

Insecticide spraying only occurs in those malarial countries where malaria is unstable and highly seasonal, such as South Africa, Namibia, Swaziland and Zimbabwe. The use of insecticide spraying does not feature prominently in the RBM vector control policy, despite the success of the insecticide use in the past.

The RBM programme commits itself to international research and development mechanisms in order to develop new and more cost effective tools for malaria control and to establish the schemes which will encourage investment in these products. It appears that the main focus on this R & D is in the development of anti-malarial drugs and the RBM conceptual framework identifies the following objectives and timetable for R & D:

Immediate term,

Medium term,

Longer term

It is vital that the development of affordable and effective chemoprophylaxes and vaccines in the long term is a vital part of the anti malaria programme, caution should be exercised in promoting anti-malarial measure that are not appropriate to developing countries. R & D of new insecticides that specifically target mosquitoes and that are not adapted from agricultural insecticides could also be an important part of the anti-malaria programme.

9. The Impact of a Ban on DDT

The United Nations Environment Programme Governing Council at its 19th session in February 1997 concluded that action was needed to develop legally binding international agreements to reduce the risks to human health and the environment resulting from the release of DDT and 11 other persistent organic pollutants (POPs). The impact of the effective ban could have far reaching implications for many developing countries.

The current UNEP programme is to achieve an internationally legally binding instrument for implementing international action against the POPs by the year 2000. The next meeting of the International Negotiating Committee will be between the 6th and 11th of September 1999 in Geneva.

While there are undoubtedly sound reasons for the banning of a number of the POPs, the valuable role that DDT plays in saving lives and reducing economic costs in many developing countries should be taken into account. While it is not possible to put an accurate figure on the potential economic cost to developing countries of a banning of DDT, it will undoubtedly have very significant negative economic impacts.

South Africa is moving away from the use of DDT in its vector control programmes for a number of reasons of which local and international environmental pressures are only one. The ban however will limit the number of 'weapons' in South Africa's anti-malaria arsenal if the use of synthetic pyrethroids do not have the desired effects. What is of even more importance is the fact that DDT is currently used by a number of Southern African (Namibia, Botswana and Swaziland) countries against malaria and is saving lives and economic costs.

The banning of DDT is perhaps part of a wider debate in which the pressure put on many developing countries in the South to conform to the environmental and health standards of developed countries in the North. Frequently institutions and individuals that do not encounter the life threatening diseases and health problems faced by many millions in the developing world, bring about these economically costly pressures. Not only do many developing countries have to contend with serious environmental and health problems, but they are striving to create jobs and improve the standards of living for their citizens. Legally binding international agreements will frequently hamper their ability to do this and ensure that they will never attain the standards of living of developed countries that benefited from substances such as DDT in the past.

It has been reported that the use of DDT in Mexico could be responsible for DDT contamination in areas of the Arctic Circle. (pers. comm Dr. Henk Bouwman Head, Unit for Pesticide Impact, ARC) Where there is clear evidence of this and it can be demonstrated that actual harm is being done, the intervention of international bodies such as the UNEP could be justified. The possibility that DDT use in vector control in Southern Africa affecting those outside the region is remote. In the case of Southern Africa, the decision of whether or not to use DDT are best based on local conditions and considerations and not on imposed and inappropriate environmental and health standards of the developed world.

Should alternatives to DDT, such as a malaria vaccine, become available to developing countries at affordable costs, DDT will no longer be necessary. A long-standing problem though is that the development of anti-malaria drugs, insecticides and vaccines is not as commercially profitable as research and development into the prevention of other diseases. Malaria control programmes are normally required to use insecticides that have been developed for the agricultural sector and not to fight malaria.

No research has been done which determines the relationship between the number of malaria cases and the use of DDT in malaria vector control and therefore it is difficult to determine accurately the economic cost of a ban of DDT. However, based on the efficiency of the insecticide in malaria control in the past, the removal of DDT from vector control programmes is however likely to impose costs on Southern African countries. If DDT is used and can reduce the number of malaria cases in Southern Africa by only 10%, it could result in a saving of around US$ 96 million. The success of DDT in the past could mean that a ban of the insecticide could result in costs of as much as US$ 480 million.

Conclusion

This study has shown that malaria imposes very significant economic costs on South Africa and most other Southern African countries, both directly through health costs and indirectly through losses in productivity.

The use of DDT in South Africa pushed the area affected by malaria back to one fifth of its original size. This allowed for the development of land and the economic advancement of many people. At the same time, DDT was being used internationally (particularly in many developed countries) for a number of uses, to great effect and economic gain. DDT became the focus of a concerted attack from many environmentalist groups, however many of the claims made by these groups are unfounded.

While most developed countries no longer need to use DDT and can afford the numerous alternative insecticides, some developing countries rely on DDT to fight malaria and to save lives. DDT is not a panacea and there are environmental and health considerations that should be taken into account. However, banning DDT will not only impose significant economic costs on developing countries, but many of the environmental and health considerations on which the ban is based are not appropriate to developing countries.

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