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Occasional paper no 7









THE CALM BEFORE

THE STORM (2)

The impact of HIV/AIDS on the South African

population, and constitutional and legal

issues surrounding the epidemic’s victims







Epicentre AIDS Management Services









July 2002









Commissioned by the Home Loan Guarantee Company









An URB AN INSTITUTE programme funded by US AID

Published in July 2002 by the



Housing Finance Resource Programme



The Isle of Houghton



Old Trafford 3, Level 3



11 Boundary Road, Houghton



Johannesburg, South Africa



P O Box 3350, Houghton



Johannesburg 2041



Tel +27 11 484-5278



Fax +27 11 484-1299



info@hfrp.org.za



www.hfrp.org.za







All rights reserved. This paper may not be reproduced, stored or transmitted without the

prior permission of the Housing Finance Resource Programme. Short extracts may be

quoted, provided the source is fully acknowledged.







Edited and produced by Riaan de Villiers







ISBN 0-9584476-7-5







This report was written by Karen Michael of Epicentre AIDS Management Services.







This publication was made possible through support provided by the Office of Housing and

Urban Environment, South Africa, US Agency for International Development, under the

terms of contract no LAG-I-00-99-00036-00, delivery order 800. The opinions expressed

herein do not necessarily reflect the views of the US Agency for International Development.

CONTENTS





Foreword 5



Research objectives 7



PART 1: EPIDEMIOLOGICAL ISSUES 9



Introduction 11



HIV/AIDS in Southern Africa 11



Completed and continuing research on HIV/AIDS in South Africa 14



Epidemiological surveillance 14

Demographic projections 17

Econometric projections 22

Weakness and strengths 22

Evaluation of the impact and projection models 23



Limitations of epi-data (antenatal clinic data) as an indicator of

general prevalence 24

The impact of HIV/AIDS on low income groups in South Africa 28



The progression and profile of HIV in South Africa 29



The natural history of HIV infection 29

The effects of HIV/AIDS on the capacity of various populations to

hold down jobs 33

The impact of the disease on the ability of people to repay loans 34



THE TREATMENT OF HIV/AIDS 38



Background on anti-retroviral therapy 38

Nucleoside analog reverse transcriptase inhibitors (‘nukes’) 39

How are antiviral drugs used? 41

Do antiviral drugs cure AIDS? 41

The cost-effectiveness of anti-retroviral treatment 42

Conclusions 46

PART 2: CONSTITUTIONAL AND LEGAL ISSUES 47



Research method 49



The legislative framework 49



The constitution 49

The Promotion of Equality and Prevention of Unfair Discrimination

Act (no 4 of 2000) 51

The Medical Schemes Act 54

The Life Offices Association Code of Good Practice 54

CONTENTS









Academic research 56



Case law 59



Conclusion 60



APPENDICES 61



Appendix 1: Modellling 63



Appendix 2: The Doyle and ASSA models 65



Appendix 3: Is HIV infection a disincentive to loan repayments? 69



Appendix 4: Persons interviewed 71



REFERENCES 72









4

FOREWORD



This publication is the second of two reflecting the results of a major research

project aimed at developing an understanding of the impact of HIV/AIDS on the

low-income housing finance sector. The project has been co-ordinated by the

Home Loan Guarantee Company (HLGC). The Housing Finance Resource Pro-

gramme has acted as a major funder of the research performed, and is pub-

lishing the edited reports as two volumes in its occasional paper series.



Two sets of consultants – Quindiem Consulting and Epicentre AIDS Manage-

ment Services – were contracted to perform different parts of the research.



Volume 1 contains the results of a survey – conducted by Quindiem Consult-

ing – aimed at establishing how lenders operating in different segments of the

low-income housing market are perceiving, and actually experiencing, the

manifestation of HIV/AIDS in their borrower populations.



Volume II contains the results of a comprehensive literature review – per-

formed by Epicentre AIDS Management Services – focusing on:



1. the epidemiological impact of HIV/AIDS on South Africa’s population by

identifying how it manifests (and will continue to manifest) across age,

gender, income groups, residential circumstances, and geography; and



2. the constitutional and legal implications arising from being an HIV/AIDS

patient/borrower.





Epidemiological impact



The Epicentre team approached this aspect of its task by:



1. identifying the work of health economists operating in research units and

consultancies across South Africa pertinent to this project;



2. describing the impact of HIV/AIDS on the South African population, with

particular emphasis on those earning less than R6 000 a month (strati-

fied as closely as possible into R1000–R2000, R2000–R3 500, and R3

500–R6000) income groups;



3. describing the stages of HIV/AIDS, ie mapping out morbidity through to

death, and its likely effect on the capacity of various population groups

(gender, income, age and so on) to hold down jobs;



4. projecting the future impact of the epidemic on the capacity of people to

repay loans, ie reflecting the effect of morbidity and death, as well as the

fact that families and communities must also bear the costs of the epi









5

FOREWORD









demic, eg the cost of anti-retrovirals, other increases in health care or op-

portunity costs and funeral costs; and



5. examining the issue of the potential for treatment to intervene in the epi-

demic, as well as the cost of this intervention (possibly indefinitely) and its

impact on the ability of the households to pay back loans.





Constitutional and legal issues



The researchers approached this aspects of their task by:



1. describing the rights as set out in the Constitution that apply to HIV/AIDS

victims;



2. interpreting the Equality Clause with respect to the specific rights to bor-

rowers;



3. describing the protocol on HIV/AIDS adopted by the Life Office’s Associa-

tion; and



4. describing all other legislation, e.g. insurance, pensions and so on that

may have implications for borrowers with HIV/AIDS.



It is hoped this volume – and the one preceding it – will help all the role play-

ers in the field of housing finance to improve their understanding of the issues

surrounding the tragic incidence of HIV/AIDS.









6

RESEARCH OBJECTIVES



This study forms part of a project aimed at assessing the impact of HIV/AIDS on

the low-income housing finance sector. It reviews the literature on the epide-

miological impact of HIV/AIDS on South Africa’s population, ad well as the con-

stitutional and legal implications arising from being an HIV/AIDS pa-

tient/borrower.





Method



The research has involved a comprehensive review of electronic databases; a

search of on-line databases and websites; a search of the titles and abstracts of

conference presentations; and a search of the bibliographies and lists of refer-

ences of articles collected. The literature review has been supplemented by

interviews or e-mail correspondence with key researchers.

‘I suppose in housing the issue hasn’t been out squarely on the table;

people aren’t dealing with it head-on … there are lots of loopholes and

problems we will be sitting on later on. It is partly because communities

have other problems … for a lot of communities we work with, aids has

not yet become a reality in daily life. And because people are dealing

with realities in a reactive way, it’s housing and job creation that they

put on the table.’





– Director of a development NGO, quoted in Lawson (1997: 34)









Standard Bank’s eviction of AIDS orphans ‘inhuman’,

says SACP





‘As the South African Communist Party (SACP) launches its Red Octo-

ber Campaign to make banks serve the people, Sowetan reports that

Standard Bank, one of the largest four banks in South Africa, is taking

action to evict orphans from their parent’s house in the Ekuhuleni town-

ship of Daveyton because they cannot pay and service the home loan

taken with the bank by their late parents. The parents of the four chil-

dren passed away last year due to HIV/AIDS-related illnesses. Given the

HIV/AIDS pandemic in our country and its particular impact on employed

workers, all financial institutions need to take measures to ensure that

credit, finance and credit insurance are available to all people living

with HIV/AIDS. Instead we have banks, insurance companies and other

financial institutions either omitting such cover or willy-nilly discriminat-

ing against people living with HIV/AIDS.’





-- http://www.woza.co.za/evictions8.htm

PART 1:



EPIDEMIOLOGICAL

ISSUES

INTRODUCTION





Housing the nation is one of the greatest challenges facing the Government

of National Unity. The extent of the challenge derives not only from the enor-

mous size of the housing backlog and the desperation and impatience of the

homeless, but stems also from the extremely complicated bureaucratic, ad-

ministrative, financial, and institutional framework inherited from the previous

government. – Department of housing (1995: 1)





South Africa faces a significant developmental challenge. Housing delivery is

a key element in the wider development framework. The 1995 white paper on

housing estimated the urban housing backlog at about 1,5 million units. The

consequences of this backlog are overcrowding, squatter settlements, land

invasions in urban areas, and poor access to services in rural areas. It adds to

the insecurities and frustrations of individuals and communities, and contrib-

utes to high levels of crime and other forms of instability. Due to the high rates

of population growth, and low rates of housing provision, the housing backlog

is estimated to increase by about 178 000 units a year (Department of hous-

ing 1995).



In addition, South Africa is currently experiencing one of the worst HIV/AIDS



epidemics in the world. General prevalence is estimated at 20 per cent, and

infections rates among the sentinel antenatal population groups continue to

rise year on year (UNAIDS 2001). Treatment options are limited due to the ex-

orbitant costs of anti-retroviral medication, as well as inadequate health de-

livery infrastructure. The prognosis is bleak, particularly for the poorest sec-

tors of the population.



South Africa’s HIV/AIDS epidemic has exacerbated its development challenges,

and presents a specific challenge to housing delivery. However, research thus

far has failed to illuminate and quantify the impact of the epidemic on housing

delivery. Furthermore, idt is not yet understood whether HIV infection adds to

the risks of lending in the low-income market.



This section of the report surveys completed and continuing research on the

epidemiological and demographic impact of HIV/AIDS on the South African

population. It also assesses the quality of the research and the data they util-

ise, and evaluates whether current data is adequate to quantify risk to lenders.







HIV/AIDS IN SOUTHERN AFRICA



HIV prevalence rates have risen to alarming levels in parts of southern Africa,

with the most recent antenatal clinic data revealing levels of more than 30 per

HOUSING FINANCE RESOURCE PROGRAMME









cent in several areas. In Swaziland, HIV prevalence among pregnant women

attending antenatal clinics in 2000 ranged from 32,2 per cent in urban areas

The high prevalence to 34,5 per cent in rural areas; in Botswana, the corresponding figures were

rates mean that even 43,9 per cent and 35,5 per cent. In the South African province of KwaZulu-

exceptional successes Natal, the figure stood at 36,2 per cent.



on the prevention front Adult prevalence is estimated at 10 per cent in 16 African countries; in sev-

will only gradually eral countries in southern Africa, at least 20 per cent are infected. Countries

reduce the human toll across the region are expanding and upgrading their responses; however, the

high prevalence rates mean that even exceptional successes on the prevention

front will only gradually reduce the human toll. It is estimated that 2,3 million

Africans died of AIDS in 2001.



UNAIDS has estimated that that one in nine South Africans (ie adults and chil-

dren) are infected, amounting to about 12 per cent of the population. How-

ever, it estimates that about 20 per cent of the adult population (people aged

15-49) are infected. Crude death rates in 2001 were also twice as high (14,7

per thousand population) than they would have been without AIDS (7,4 per

thousand population; UNAIDS 2001).



According to the US Census Bureau (2000), by the year 2010 Botswana,

South Africa, and Zimbabwe will experience population growths of –1,3 per

cent, -1,3 per cent, and -0,9 per cent respectively, instead of the 2,0, 1,0, and

1,9 per cent they would have without AIDS. This is the first time that negative

population growth has been projected for developing countries. This will be

due to high levels of HIV/AIDS coupled with relatively low fertility. In other

countries, populations will still grow despite high levels of mortality, due to

very high levels of fertility. The impact of the pandemic on child mortality is

highest in those countries that have significantly reduced child mortality due

to other causes, and where HIV prevalence is high. Many HIV-infected children

survive their first birthdays, only to die before age five. In Zimbabwe, 70 per

cent of all deaths among children younger than five are due to AIDS. In South

Africa, this percentage is 45.









12

THE CALM BEFORE THE STORM (2)









Figure 1: Predicted loss of life expectancy due to HIV/AIDS of children

born in 2000









Predicted loss in life expectancy

due to HIV/AIDS in children born in 2000



Predicted life expectancy Loss in life expectancy due to HIV/AIDS



Botswana



Zimbabwe



South Africa



Kenya



Zambia



Côte d'Ivoire



Rwanda



Mozambique



Haiti



Cambodia



0 10 20 30 40 50 60 70

Life expectancy at birth (years)





Source: U.S. Census Bureau, 2000









Since the epidemic began 20 years ago, more than 60 million people have

been infected with the virus. Sub-Saharan Africa remains the most severely

affected region. About 3,4 million new infections occurred in 2001, bringing

to 28,1 million the total number of people living with HIV/AIDS in this region.

HIV/AIDS is now the leading cause of death in sub-Saharan Africa. Worldwide,

it is the fourth biggest killer(UNAIDS 2001).



At the end of 2001 an estimated 40 million people globally were living with

HIV. Most of them do not know they carry the virus. Many millions more know



nothing about HIV, or too little to protect themselves against it. AIDS killed 2,3

million African people in 2001 alone. There were an estimated 3,4 million

new HIV infections in sub-Saharan Africa in the past year (UNAIDS 2001: 1).



Progress is being made on the treatment and care front. Botswana is begin-

ning to provide anti-retroviral drugs through its public health system, thanks

to a bigger health budget and drug price reductions negotiated with pharma-

ceutical companies (UNAIDS 2001: 16). South Africa has also taken the first

steps towards providing anti-retrovirals by offering Nevirapene to HIV-

positive pregnant women at state hospitals and clinics.









13

HOUSING FINANCE RESOURCE PROGRAMME









In the context of a public–private partnership between five research and de-

velopment pharmaceutical companies and five United Nations agencies, ac-

cess to anti-retroviral therapy in Africa is improving. At the end of 2001 more

than 10 African countries were providing anti-retroviral therapy to people

living with HIV/AIDS.





Serological COMPLETED AND CONTINUING RESEARCH ON HIV/AIDS

surveillance rests on IN SOUTH AFRICA

certain basic

The impact of HIV/AIDS is being researched by means of epidemiological sur-

requirements, such

veillances, demographic projections, and econometric projections.

as the absolute

protection of Epidemiological surveillance

confidentiality and

Background

privacy, and the

repeatability of the Since 1990, HIV prevalence data have been collected via an unlinked anony-

mous survey, conducted by the department of health, of women attending

sampling frame

state antenatal clinics (ANCs). This survey has provided the best measure of

changes in prevalence. The data are used to estimate the number of South

Africans infected with HIV.



HIV serosurveillance data are used to estimate HIV prevalence rates and the

geographic distribution of infection, monitor trends over time in specific

population groups, and identify subpopulations at increased risk of infection.



The seroprevalence survey is administered to 16 000 women at randomly

selected antenatal clinics. Blood samples are tested for both HIV and syphilis.

Data is disaggregated on the basis of age and geographical distribution.



Serological surveillance rests on certain basic requirements, such as the ab-

solute protection of confidentiality and privacy, and the repeatability of the

sampling frame. No survey system will produce a truly representative sample,

but should aim to broadly cover all sections of the population, including rural

and urban. The appropriate choice of populations will differ from country to

country, and should be guided by an assessment of scientific needs as well as

available resources and cultural and political factors. Serological surveillance

should be aimed at generating the regular analysis and dissemination of re-

sults, focusing on prevalence in young age groups as a surrogate measure of

HIV incidence, and producing data specific to each sex. Data are generally ana-

lysed by site, age, and – if applicable – sex, in an attempt to detect differentials.



Organisations such as UNAIDS and the World Health Organisation (WHO) con-

sistently praise South Africa for the quality of its surveillance data (Williams et

al 2000). However, this has a serological focus. While it is adequate for sero







14

THE CALM BEFORE THE STORM (2)









logical surveillance, it is questionable whether it can be used for reliable

demographic and econometric analysis.









35



30



25

1996

20 1997

1998

%









15 1999

2000

10



5



0

59 years), and spreads through the

the remainder. The 14–59 year age group is then further divided into four population at risk by

‘risk’ groups depending on the ease with which its members are expected to assumed infection of

contract and transmit the HIV.

non-infected individuals

Each year the new uninfected 14-year-olds are allocated to the four risk within and among

groups. Infection is introduced into the PRO risk group via 300 male and 450 groups

female infected ‘imports’ which are not added to the population but merely

used when calculating the ‘sexual activity weighted HIV prevalence’, and

hence the partners' force of transmission of HIV. The epidemic then spreads

through the population at risk by assumed infection of non-infected individu-

als within and among groups. The rate at which the infection spreads is con-

trolled by the following assumptions:



4. Those contained in the ‘contagions’ matrix, which gives the force of

transmission by an infected individual in a given risk group to members of

the other groups. This force of transmission is a function of the number of

sexual contacts a year, the number of new partners a year, and the ease of

transmission.



5. The sexual activity curve (to be found on the sex activity sheet), which is

simply an assumption of relative sexual activity according to age (sepa-

rately for males and females).



The following changes were made to the ASSA600 model.



A new starting population: The hypothetical population was replaced with

an estimate of the South African population in 1985 derived from the popula-

tion in 1970.



Fertility: The model was adjusted to allow for:



• The falling fertility of HIV-negative women over time, in line with past

trends



• the fact that HIV-positive women experience lower fertility than HIV-



negative women (except at younger ages), and that this effect increases

with age



Mortality: The base mortality table was replaced with one reflecting national

mortality circa 1985 (Dorrington 1998), and the model adapted to allow for

improving (falling) mortality over time. In addition, the mortality of HIV-



positive infants was changed from 30 per cent a year to that corresponding to

a survival curve with a median term to death of two years.





67

HOUSING FINANCE RESOURCE PROGRAMME









Migration: The model was changed to allow for net migration with specified

proportions in the risk groups (although, in the absence of any evidence, these

proportions were chosen to be the same as those of the whole).



Unfortunately, In this regard, the model reproduced fairly successfully both the pattern of

behavioural and reported AIDS cases in 1995 and the age distribution of ANC HIV prevalence for



social research is 1994–7. However, the model appears to be far less successful in tracking the

path of the epidemic in the PRO and STD risk groups, in particular with the

scant, and very

long-term prevalence being far higher than any of the surveys for other coun-

little national

tries seems to suggest. A possible explanation for this, apart from the suspect

behavioural

nature of much of the data, the very specific definition of the PRO risk group in

prevention data particular so as to comprise only 1 per cent of the population. In other words,

are available it is quite likely that the survey data represents a mixture of the risk groups as

defined in the model.



In the end, the model reproduces the estimates of the prevalence of pregnant

women fairly closely, and deviations are as likely to be due to errors and

shortcomings in the ANC surveillance estimates as to problems with the model.



As the epidemic progresses, and as behaviour change begins to be a more sig-

nificant epidemiological factor, there will be an even greater need to build

these changes into modelling efforts. Behavioural surveillance particularly

helps to explain trends within and among data sets, and data derived from

behavioural surveillance would be an important supplement to the existing

data derived from surveillance at antenatal clinics. Unfortunately, behav-

ioural and social research is scant, and very little national behavioural pre-

vention data are available. The need for such data is particularly acute in the

mature stages of the epidemic, when vectors of infection are more diffuse and

the boundaries between high and low transmission populations become less

distinct.





CONCLUSION



Given the questionable bases of these models in terms of the accuracy and re-

liability of data, their internal and external validity, and their sensitivity, the

results generated seem adequate for advocacy but inappropriate for research,

as the assumptions and the data they rely on are not empirical and not accu-

rate enough.









68

THE CALM BEFORE THE STORM (2)









APPENDIX 3: IS HIV INFECTION A DISINCENTIVE TO LOAN

REPAYMENTS?



In order to quantify the risk of HIV infection among low-income earners to

lenders, a basic question has to be asked: is HIV infection a disincentive to loan

repayment? This question cannot be answered by asking lenders or by mining

existing financial databases, which do not indicate HIV infection as a variable

for risk. This report has attempted to ascertain whether it can be answered by

using existing research and modelling practices. The answer appears to be

negative. Thus the question becomes whether existing models can be refined

to answer the research question.



ASSA is currently trying to plug existing income data into its model, without

much success. The reasons are familiar:



1. The models as they are currently calibrated cannot accommodate income

data.



2. There is a paucity of income data at a household level. There is no income

data for households affected by HIV/AIDS in South Africa



3. Income groups in South Africa are transitional and turbulent. There is a

great deal of mobility within and between income groups. No data exists

that captures the dynamic nature of income groups in South Africa, and

models which treat income as a fixed variable would invariably be inade-

quate.



4. Researchers and modellers have very little idea of the distribution of HIV



across ‘income groups’ in South Africa. Prevalence data are not corre-

lated with income, and any modelling of income as an independent vari-

able would necessarily be an educated guess (a macro simulation)



Ground zero is that there is a correlation between high rates of HIV prevalence

and poverty. Research from other countries has shown a high level of correla-

tion between poverty and HIV/AIDS. However, this research only illuminates as

much as it conceals. It is unknown for example, whether HIV infection consti-

tutes an added risk for loan default, To answer this question, we need to an-

swer a number of other questions:



1. What is the average payback period for a low-income housing loan, and is

this period shorter than the median time between infection and the onset

of severe HIV-related disease?



2. What is the profile of the progression of HIV disease among low-income

earners in South Africa?









69

HOUSING FINANCE RESOURCE PROGRAMME









3. What is the median time from infection to the onset of severe HIV-related

infection?



Such data would 4. Does the onset of AIDS-related complex (ARC) lead to loan default?

allow one to 5. What is the effect of various treatment regimes on disease progression and

accurately establish repayment?

whether HIV

6. How much risk variance is explained by HIV? There are other factors that

infection poses a contribute to the risk of loan default among low-income earners that have

significant risk of to be ‘weighted’ against HIV.

loan default among

The research void that exists cannot be spanned by creating a bricolage of

low-income earners results generated by existing models. Rather, in order to adequately answer

the research question, some fundamental groundwork needs to be done.



A significant step forward would be to collect primary detailed, time series

data, and construct a purpose-built model which could analyse changing

household structure, changing expenditure and consumption patterns, gen-

eral disease burden, employment issues, effects of treatment and behaviour

change interventions, social capital effects, and so on. Significant data sets

would include:



1. Prevalence and incidence – prevalence survey among a sample popula-

tion of low-income earners as defined by the HFRP’s definition of low-

income earners.



2. Establishing disease progression in sample population.



3. Establishing where significant increments of risk are located along this

progression.



4. Establishing variables that increase or decrease risk along this progres-

sion, such as behaviour and treatment interventions, or loss of employ-

ment.



5. Model should include appropriate disaggregators such as race, gender,

income, age, geographical distribution, household structure, etc.



Such data would allow one to accurately establish whether HIV infection poses

a significant risk of loan default among low-income earners, as well as the

significant increments of risk along the continuum of disease progression

among low-income earners. Advocacy work on the design of financial prod-

ucts appropriate to HIV-infected individuals in the low-income market would

then stand on a solid foundation.









70

THE CALM BEFORE THE STORM (2)









APPENDIX 4: PERSONS INTERVIEWED



Liesl Gerntlholtz, AIDS Law Project, University of the Witwatersrand.

011 717 8600



Cathy Albertyn, Centre for Applied Legal Studies, University of the Witwa-

tersrand. 011 403 2341



Robyn Solomon, Human Rights Commission. 011 484 8300



Dominic Liber, actuary. 011 489 5826



Prof Alan Rycroft , University of Natal, Durban. 031 260 2605



Richard Elliot, Canadian HIV/AIDS Legal Network.



Brendan Christian, Law Clinic, University of Natal, Durban. 031 260 9111



Anton Kok, Centre for Human Rights, University of Pretoria. 012 420 2878









71

HOUSING FINANCE RESOURCE PROGRAMME









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