1. 1
Diane AMANCIC
634791
Economic Development in Africa
Assignment  1
Ramin Nassehi
What are the analytical strengths and weaknesses in the mainstream economics
approach to understanding the spread of HIV? Discuss with examples from ONE or
MORE sub-Saharan African economies.
Word count: 2490

2. 2
Microeconomics methodologies such as Rational Choice Theory (hereafter “RCT”)
constitute the basic approach to HIV research in SSA; such mainstream approaches provide
clear general insights regarding individual decision-making in terms of sexual behaviour and
HIV risk. However, criticisms have emerged as RCT assumptions with regards to “free
choice” and risk perceptions – particularly for women – ultimately lead to at best mixed
results and subsequent inadequate policy implementation. These approaches also fail to
take into account important factors deriving from cultural practices that shape sexual
behaviour. All in all, it seems clear that mainstream economics approaches alone are not
sufficient to explain the causes of HIV transmission (hereafter HIVT) and provide mixed
results in terms of HIV prevalence (hereafter HIVP). An approach mixing microeconomics
and socio-political factors would provide better results leading to more cost-effective and
efficient policy conclusions. Hence, cultural factors such as religious affiliation may show
positive or negative relationships to HIVT/P, but should be included in mainstream
methodologies as religion is a central part of many people’s lives and define to a great extent
the way in which they behave. Using a study conducted in 38 Sub-Saharan African countries
by Peter B. Gray (2003) and recent data collected from UNAIDS, GooglePublicData and the
CIA World Factbook, this essay will demonstrate through the case study of Burkina Faso
and Zimbabwe that modelling of religion is possible and that there is a continuous, clear
negative relationship between Islamic practices and HIVP in comparison to other religious
groups in SSA. Further study will be required to determine the incidence of the independent
variable religion on HIVT. This essay will comprise 3 sections: (1) assessment of the
weaknesses of mainstream economics approaches and the subsequent necessity to include
cultural variables to microeconomics analysis; (2) macroeconomics of HIV in SSA with a
focus on Zimbabwe and Burkina Faso and (3) discussion around Gray’s (2003) research on
the negative relationship between HIV prevalence and Islam.

3. 3
(1)
Mainstream economics approaches to HIVP have been so far the preferred method
of analysis for they are empirically grounded and provide clear insights regarding risk-
induced behaviour. In the 1990s, when the HIV/AIDS pandemic had just started to reveal its
destructive impact on African societies and economies, large-scale prevention campaigns
based on RCT study results were implemented with a focus on educating the largest number
of people to HIV risks as well as subsidizing condoms. The majority of these policies proved
overall inefficient as they were often met with strong cultural beliefs which dismissed the
severity of the disease, or because the policies did little to correct socio-economic
inequalities which kept most of the population away from “safe sex”. This is a result of both
the inability of mainstream economics to predict the development of the pandemic and its
mixed results due to a narrow choice of variables and unrealistic assumptions. Indeed,
mainstream economics approaches applied to the study of the HIV/AIDS pandemic in Sub-
Saharan Africa have modelled human behaviour through a rational calculus of gain and
losses (Philipson & Posner, 1995) using individual responses to surveys. Common
assumptions include the ability to demand “safe sex” as informed and rational individuals,
knowing the HIV-related risks of engaging in unsafe sex. However, economic inequality will
drive poorer people to engage in unsafe sex, while richer backgrounds will exploit class
differences and have incentives to engage in unsafe sex too. RCT studies also sometimes
lack empirical data as explained in Philipson & Posner (1995) because of poor national data
collection in SSA countries.
It has been demonstrated that HIVP does not necessarily have a positive relationship to
education and wealth (Parkhurst, 2010), so it is not possible to make assumptions regarding
HIV/AIDS as a disease of poverty or wealth exclusively. Parkhurst (2010) showed that there
was a tendency for HIVP to increase along with the wealth quintile for it is associated with a
range of behaviour which can give people incentives not to engage in safe sex; for instance,
a person located in the highest wealth quintile in Tanzania would assume that it is

4. 4
unnecessary for him/her to engage in safe sex as he/she could afford to get treatment.
Opposed to this, poorer people – especially women – would engage in commercial sex to
make up for socio-economic inequality, proving that a woman who engages in such
practices might be informed about HIV-risk but has no choice but to sell her body and can
hardly enforce the use of a condom with her male customers. This last point exemplifies the
limits of RCT in providing accurate results as it fails to encompass the diversity of factors
that influence people’s behaviour. Likewise, the class and gender variables have a more
complex relationship to HIV prevalence as Bujra (2006) demonstrated that exploitative
relationships between classes are just one more counter-argument to the “free choice”
assumption held by neo-classical researchers.
Still, cited studies seem to focus largely on predominantly Christian Sub-Saharan African
countries, where HIVP is the highest. But as Johnson points out: “We are reminded of Fine’s
(2009) argument that rather than general hypotheses linking health to growth, we need to
better understand the health conditions faced by various segments of the population, how
they are generated within society […]” (2013: 31). Indeed, cultural factors play an important
role in HIVT as they define to a great extent the way in which individuals behave, though
religion has not been included in mainstream analysis because it is thought to be difficult to
model. However, it seems possible to model practices deriving from religious affiliation and
compare religions in this light, as Gray stated: “Behaving in accordance to religious tenets
may have impacts on health and disease transmission […] if religious factors associated with
HIV […] can be identified, then this endeavor can be important in helping to understand and
predict the course of the raging HIV epidemic” (2003: 1).

5. 5
(2)
Fig. 1.: HIVP in 16 selected SSA countries for the years 2005 to 2011. This graph shows
that predominantly Christian countries show high to very high rates of HIV prevalence (from
lowest to highest: Malawi, Mozambique, Namibia, Zambia, Zimbabwe, South Africa, Lesotho
and Botswana), while predominantly Muslim countries show low or very low HIVP (from
lowest to highest: Mauritania, Senegal, Mali, Burkina Faso, Ghana, The Gambia, Chad).
Uganda acts as a median and shows a lower rate of HIV prevalence than other
predominantly Christian countries (6.5%) because of the recent success of HIV-awareness
campaigns, but still shows a prevalence rate double that of Chad (3.4%) Data source:
Google Public Data, (2015).

6. 6
Fig. 2. shows the relationship between HIV prevalence and percentage of Muslims within a
country. 7 countries where the percentage Muslims is located between 0 and 10% show low
to really high HIVP rates, ranging from around 4% to over 35% prevalence rate. As the
percentage Muslims within a country increases, HIVP never exceeds around 10% and drops
as low as 2% when Muslims percentage reaches 80%. Finally, in one country where the
percentage Muslims averages 100%, HIVP appears to be close to 0%, showing the clear
negative relationship between HIVP and Islam/Islamic practices. Source: Gray, (2003).

7. 7
Variables
Country
Life
expectancy
at birth
(total
population)
Total
population
HIV Adult
Prevalence
Rate
Religion
GDP
per
capita
(PPP)
in US$
HIV Spending
(UNAIDS Data)
Burkina Faso 55.12 years
18,931,686 0.94%
(2014 est.)
Muslim
60.5%,
Catholic
19%,
animist
15.3%,
Protestant
4.2%, other
0.6%, none
0.4%
$1,700
(2014
est.)
22 million
$ international
donors, 30
million
$ domestic
public = 52
million $ (2012)
Zimbabwe 57.05
14,229,541
16.74%
(2014 est.)
Protestant
75.9%,
Catholic
8.4%, other
Christian
8.4%, other
1.2%
(includes
traditional,
Muslim),
none 6.1%
$2,100
(2014
est.)
220 million
$ international
donors, 34
million
$ domestic
public = 254
million $ (2012)
Fig. 3.: National-level data for life expectancy at birth (total population), total population, HIV
Adult prevalence rate (of all adults aged 15-49), religion, GDP per capita (PPP) in US$ and
HIV spending for the year 2012 for Burkina Faso and Zimbabwe (in US$). We can observe
that both countries are similar in terms of life expectancy, total population and GDP per
capita (PPP); though there are significant differences in terms of religion percentages, HIVP
and particularly HIV spending. Indeed, the Burkinabè state spends more on HIV prevention
campaigns and treatment than it receives from international aid, while Zimbabwe spends
slightly more than what Burkina Faso receives in aid and receives an outstanding 220 million
US$ in aid from the international community to fight HIV, though the HIVP rate is
considerably lower in Burkina Faso. Regarding religion, Burkina Faso is predominantly
Muslim but also homes around 20% of Catholics and other animists; Zimbabwe is
overwhelmingly Protestant/Catholic with less than 1% Muslims. Source: CIA World Factbook

8. 8
(2015), with the exception of the data on HIV spending from UNAIDS (2012). Note on
Burkina Faso: Certain communities might adhere to Islamic practices without identifying as
Muslims, along with practicing an African traditional religion, so percentage of people
following Islamic dogmas might be higher.
The data collected in Gray’s (2003) study and GooglePublicData (2015), UNAIDS (2012)
and CIA World Factbook (2015) shows that the dependent variable HIVP and the
independent variable Islam result in a negative relationship throughout the course of 12
years in SSA, in comparison to Christian countries where it results in a positive relationship
as demonstrated with the comparative analysis of Zimbabwe and Burkina Faso. This
correlation advocates for the benefits of the inclusion of a religion variable into mainstream
economics analysis on HIV. As religious affiliation results in a negative relationship with
regards to HIVP, and as cultural factors greatly influence individual behaviour with regards to
health, one hypothesis could be that commitment to Islamic practices also results in a
negative relationship with HIVT.
(3)
So far only a handful of studies stressed the importance of the inclusion of religious
practices into mainstream economics approaches to HIVT and HIVP (Obbo, 1995; Gray,
2003), although these can be modelled into mainstream economics analysis. In the case of
HIVP and Islam, the assumptions then would be that individuals have free choice, as
religious practices are free from economic coercion, and that the sample population is
committed to religious dogmas [the inclusion of a confidence interval could overweight
responses bias]. Practices affiliated to Islam include the circumcision of men; ritual washing
of genitals post-sexual intercourse; the prohibition of alcohol consumption; the allowance of
a maximum of 4 wives per man; the prohibition of homosexual and anal sex and the
prohibition of extra-marital affairs (Gray, 2003: 1). If the commitment to these dogmas is true,
then the Muslim population benefits from a religiously inherent protection against HIV risk.

9. 9
Further, Islamic religious constraints – whether they are followed or not – provide a
theoretical protection against HIV risk in comparison to Christian religious affiliation. Indeed,
even though it can be expected that not all Muslims will follow these practices to the letter,
Christian dogmas do not prohibit alcohol consumption or extra-marital affairs, which
respectively decrease condom use and increase HIV risk (ibid., 3); the circumcision of men
is not encouraged, though it has been demonstrated that circumcision decreases the risk to
contract an STD or if already infected, decreases the likeliness of spreading HIV (ibid., 2;
Stillwaggon, 2006); there is no practice of post-sexual intercourse ritual washing, which
could decrease the risk of STD infection and therefore HIV risk; Christian men are allowed to
one wife, which could create incentives for men to have extra-marital affairs with unknown
women or sex workers, which are known to increase HIV risk (Morris & Kretzschmar, 1997).
The only common variables to both religions are that religious institutions discourage
condom use for the sake of procreation; and the prohibition of homosexual and anal sex
which when practiced unsafely are risk factors. Regarding condom use and extra-marital
affairs – particularly with sex workers –, Gray’s cross-study analysis found mixed results
(2003: 4), so there might be a positive relationship between the dependent variable HIVP
and the independent variables condom use and sexual intercourse with sex workers among
certain Muslim populations. However, this can be overweighed by the fact that “[…] there is
no evidence that Islamic religious affiliation increases sexual behaviors that constitute risk
factors for HIV” (ibid., 4). A last argument for the inclusion of religion into mainstream
analysis is that the commitment to religious practices, unlike safe sex, is free from economic
coercion and/or inequality, as none of the dogmas affiliated to Islam or Christianity requires
money in order to be followed. Therefore, the reason for lower HIVP in predominantly
Muslim countries in SSA seem to be found in religious practices which shape health
conditions, and if this could be proven empirically, then it could be argued that Muslim
affiliation and resulting practices have a negative relationship with both HIVP and HIVT.

10. 10
This essay has listed a few of the methodological and empirical flaws of RCT and
demonstrated the benefits of the inclusion of religion in mainstream analysis. Firstly,
assumptions used in RCT in the study of HIVP such as free and rational choice of individuals
engaging in unsafe sex are flawed for they ignore the economic reality of poorer people in
SSA. For example, women and young girls in particular are forced into commercial and/or
unsafe sex because of their low income, which makes void the knowledge they might have
about risk-induced behaviour. It also has been shown that income, education and wealth are
not sufficient variables to explain HIVP for the empirical data is flawed or missing, which
dismisses the assumption of HIV as a “disease of poverty” as it also affects wealthier
individuals. As HIV has a complex pattern of transmission, the unrealistic assumptions and
empirical flaws of RCT make the case for the inclusion of cultural factors such as religion
into mainstream analysis. In its second part, this essay has pointed out the continuous
negative relationship between HIVP and Islam in comparison to other religious groups in
SSA, and exemplified this claim through a comparative data analysis of Burkina Faso and
Zimbabwe. Hence, if there is a negative relationship between HIVP and Islam, and as health
conditions are generated to a non-negligible extent by individual behaviour, then it could be
hypothesized that Islam for instance has a negative relationship to HIVP, and HIVT. The
third part of the essay shed light on practices affiliated to Islam and why these provide
theoretical protection against HIV risk in comparison to Christian dogmas, or lack of. Further
study is required to assess the veracity of these claims, but the inclusion of a religion
variable into mainstream economics approaches is possible and valuable as we can model
religion in terms of practices that derive from it, and as religious practices are less subject to
change unlike economic data. If the negative relationship between HIVP/T and Islam can be
empirically grounded, the resulting policy conclusions could focus on involving religious
institutions in HIV prevention which would be highly beneficial as large portions of the
population in SSA rely on these institutions.

11. 11
Bibliography:
 Bujra, Janet (2006) “Class relations: AIDS & socioeconomic privilege in Africa”, in
Review of African Political Economy, 33:107, 113-129
 Gray, Peter B. (2003) “HIV and Islam: is HIV prevalence lower among Muslims?”in
Social Science & Medicine (Impact Factor: 2.89) 06/2004; 58(9): 1751-6
 Johnston, Deborah (2013) Economics and HIV: The Sickness of Economics,
London: Routledge
 Morris, Martina & Kretzschmar, Mirjam (1997) “Concurrent partnerships and the
spread of HIV” in AIDS, 11: 641–648
 Parkhurst, J. (2010) “Understanding the correlations between wealth, poverty and
human immunodeficiency virus infection in African countries” in Bulletin of the World
Health Organization, 88: 519-26
 Philipson, T. & Posner, R.A. (1995) “The Microeconomics of the AIDS epidemic in
Africa” in Population and Development Review, vol. 21, no. 4, pp. 835-848
 Stillwaggon, Eileen (2006) AIDS and the Ecology of Poverty, Oxford: Oxford
University Press
 Obbo, Christine (1995) “Gender, Age and Class: Discourses on HIV Transmission
and Control in Uganda” in Culture and Sexual Risk: Anthropological Perspectives on
AIDS, ed. Han ten Brummelhuis and Gilbert Herdt, Amsterdam: Gordon and Breach
Publishers