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Epidemiology of HIV and selected blood-borne infections in East-Africa
Hladik, W.
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Hladik, W. (2013). Epidemiology of HIV and selected blood-borne infections in East-Africa
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Download date: 16 Jun 2017
1
Introduction
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Chapter 1
Africa, more than any other continent, is still plagued with the
burden of infectious disease. The human immunodeficiency virus
(HIV), a newly emerging disease dramatically altered population
health in sub-Saharan Africa in recent decades and changed
the epidemiology of ancient infectious diseases such as human
herpesvirus 8 (Kaposi’s sarcoma associated herpesvirus), and
tuberculosis. The separate emergence of two separate HIV species
(HIV-1 and HIV-2) reflects the continued exposure of humans to
pathogens emerging from Africa’s forests.
Prevailing stigma, both old (tuberculosis) and new (HIV), as
well as poor health care and health information systems are met
by new and sophisticated prevention, treatment, and surveillance
techniques. Surveillance is defined as the ongoing, systematic
collection of data on the occurrence or distribution of diseases
and other conditions or attributes in a population. HIV and
related infectious disease surveillance – the monitoring or prompt
reporting of every new case – is a key strategy in industrialised
settings. In low resource settings, such as East-Africa, HIV and
related infectious disease case surveillance is still in its infancy,
reflecting the generally poor state of health information systems
in the region. To fill the resulting information gaps, observational
epidemiological research and surveys examine and estimate key
aspects of HIV-related population health.
1.1 Epidemiology of HIV infection
1.1.1 Origin of the HIV epidemic
HIV, part of the lentivirus sub-family of retroviruses, consists of
two major types, HIV-1 and HIV-2 [1]. HIV-1, comprising two main
groups, M (“major”) and O (“outlier”) , is the predominant HIV type
in Africa and the rest of the world, while HIV-2 is prevalent mostly
in West-Africa [2]. Case reports and serological evidence suggests
that the HIV-1 group M epidemic may have its origin in the area of
Congo-Kinshasa (today’s Democratic Republic of Congo), Rwanda,
10
1.indd 10
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Introduction
and Burundi [3]. The daily river-ferry from Kinshasa to Brazzaville
may have been a route of spread to Congo-Brazzaville and the war
between 1971-81 in Tanzania and Uganda may have facilitated its
spread to these two countries, and on to other countries in EastAfrica [3]. In East-Africa today, HIV-1 group M subtypes A and D
predominate, apart from Ethiopia where subtype C is dominant.
1.1.2 HIV transmission
Sexual HIV transmission
Sexual transmission accounts for the bulk of new HIV infections
in sub-Saharan Africa, including East-Africa. The transmission
probability per sex act is mainly a function of HIV viral load
(reflecting levels of HIV in the genital tract [4]), presence or
absence of genital ulcers, and mode of sexual intercourse. Vaginal
sex is estimated to carry a per act transmission probability of
0.0011 [5]. In the presence of sexually transmitted infections (STIs),
this risk may increase eight-fold [6], whereas anal sex multiplies
the base risk 2.6 fold [7]. HIV transmission through oro-genital
contact likely is inefficient. Further, compared to the asymptomatic
stage of HIV infection, which accounts for most of the infection’s
duration, where HIV viral load is lowest, the primary HIV infection
stage is estimated to be associated with an 9-40 fold increased HIV
transmission probability [4, 8-11]. The transmission risk during the
symptomatic HIV infection stage (lasting approximately 2 years
prior to death) increases the asymptomatic stage base risk 7-fold
[8]. Mathematical modelling suggests that although infectivity in
the acute stage of HIV is very high and transmission probability
is also increased during late-stage infection, no stage may be
dominant in driving the HIV epidemic on a population level [12].
Vertical HIV transmission
Vertical HIV transmission from mother-to-child (MTCT) constitutes
the second most frequent transmission mode in generalised
epidemics. Without intervention, the MTCT risk is estimated at 20%
11
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24.05.13 00:13
Chapter 1
perinatally [13]. HIV transmission continues during breastfeeding
with an estimated monthly risk ranging from 0.75% (exclusive
breastfeeding) to 1.5% (mixed breastfeeding) during the first 6
months, and a further monthly transmission risk of 0.75% after 6
months [14-16].
Parenteral HIV transmission
Parenteral HIV transmission includes the most efficient modes of
transmission. Transfusion of HIV-positive blood carries an estimated
transmission risk of 95%-100% [17], whereas the risk of infection
through the use of a HIV contaminated syringe is estimated at 0.8%
(median) [18].
1.1.3 Current epidemiology and burden of HIV disease in EastAfrica
General population
The HIV/acquired immunodeficiency syndrome (AIDS) epidemic
in East-Africa likely is the second most severe worldwide after
southern Africa. Uganda was among the first countries to declare
its HIV epidemic in the mid-1980s [19-22] and reports followed
about the likely heterosexual transmission of HIV in Uganda [23], in
contrast to the western industrialised nations where men who have
sex with men (MSM), intravenous drug use and blood transfusions
accounted for the vast majority of HIV infections. Reports of HIV
sero-positivity in various populations groups across East-Africa soon
followed: a) 1984: in patients meeting the clinical AIDS definitions
in Rwanda [24]; b) 1985: across different population groups, with
wide variations, in Kenya, [25]; c) 1986: in healthy individuals and
patients in Rwanda [26] d) 1987: in apparently healthy subjects
and patients in Tanzania [27] and e) 1988: in pregnant women in
Bujumbura, Burundi [28]. Since the late 1980s or early 1990s all
eastern African countries experience generalised HIV epidemics,
often exceeding 5% in prevalence. Although exact reasons remain
unknown, low levels of male circumcision, high prevalence of genital
12
1.indd 12
24.05.13 00:13
Introduction
"#$%&'(!)!
herpes simplex virus type 2 (HSV-2), and partner concurrency (i.e.,
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as
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biological
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Table
1.1 HIV-related indicators in select eastern African countries
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1.indd 13
!
24.05.13 00:13
Chapter 1
High-risk populations
Within epidemics in Africa, there are population groups subject to
markedly higher HIV infection risks. Such groups include female sex
workers (FSWs) and their clients, MSM and injection drug users
(IDUs).
In Kampala, Uganda, surveys among FSWs estimated an HIV
prevalence of 33%, and among clients and partners of FSWs as
18% [40]. Given an estimated HIV prevalence of 10% among adult
women in the general population in Kampala [37], and a selfreported median duration of sex work in Kampala of 3 years at the
time of survey participation, this would suggest a substantial HIV
incidence in FSW. UNAIDS-commissioned studies estimate that
in Kenya 14% of incident HIV infections are due to commercial
sex [38], whereas in Uganda, this proportion is estimated at 10%
[39]. These proportions are likely higher if restricted to the urban
populations of East-Africa.
MSM also show high levels of HIV infection due to the
increased risk of HIV transmission by anal sex and severe stigma
and criminalisation, leading to a lack of tailored prevention
services. HIV prevalence among MSM in Kampala, Uganda, was
estimated at 13.7% [40], similar to an estimate in Zanzibar (12.3%)
[41], but substantially higher among “high-risk” MSM in Mombasa,
Kenya, with an estimated 43% [42]. Estimates of the proportions
of all new HIV infections in a given country that are due to MSM
contacts vary between 0.9% in Uganda [39], and 15% in Kenya [38]
and Rwanda [43]. However these proportions are very sensitive
to the estimated national population sizes of MSM, which are
difficult to estimate and politically delicate. MSM in East-Africa
also demonstrate substantial sexual mixing. In Malawi for example,
a third of MSM were married or cohabiting with a woman [44],
whereas in Uganda 31% of Kampala MSM were ever married, and
78% ever had sex with a woman [40].
14
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Introduction
In contrast, there is a paucity of data on IDUs in East-Africa. In
Nairobi, Kenya, HIV prevalence among IDUs was estimated at 36%
[45], somewhat similar to an estimated 26% HIV prevalence among
IDU in Zanzibar, Tanzania [46].
1.1.4 HIV surveillance
General principles
The World Health Organisation (WHO), UNAIDS, and the US Centers
for Disease Control and Prevention (CDC) issue key surveillance
guidelines, such as those for 2nd Generation HIV Surveillance
[47]. These guidelines prescribe an HIV surveillance approach
depending on the epidemic setting (low-level, concentrated,
generalised HIV epidemics). Countries where the HIV prevalence
is estimated at below 1% in the general population and does not
exceed 5% in “key populations” (high-risk groups) are defined as
“low-level” epidemics. Concentrated epidemics are found where
HIV prevalence exceeds 5% in at least one high-risk group (such
as FSWs, MSM, or IDUs). Countries with generalised epidemics
are defined as countries where the estimated HIV prevalence in
pregnant women exceeds 1%. In generalised epidemics, as found
throughout East-Africa, countries are supposed to regularly
conduct surveys among ante-natal clinic (ANC) attendees.
The purported strengths of an ANC-based surveillance
system, using “unlinked anonymous testing” (UAT) on left-over
blood, were (and are) that pregnant women are healthy, that
HIV testing may be done without informed consent (minimising
selection bias), and that ANC attendees may be a proxy of the
general adult population, including men and non-pregnant
women. ANC-based HIV surveillance using UAT proved to be the
cornerstone for the monitoring of all generalised HIV epidemics
and to date provides the majority of African HIV surveillance data
points used to estimate the burden of disease. Traditionally, the
median ANC site HIV prevalences were reported and used for trend
observations over time. Stratifications by urban/rural setting and
15
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Chapter 1
by age group provide additional important information about the
broad distribution of HIV. In addition, HIV prevalence among 1519 or 15-24 year-old ANC attendees may serve as a crude proxy
for HIV incidence as the median duration of HIV infection in these
young age groups presumably is low. In recent years the concept
of UAT has come under criticism as the HIV test result cannot be
returned to the patient hence theoretically impeding HIV treatment
and control efforts [48]. At the same time, “Prevention of Mother
To Child Transmission” (PMTCT) programs have undergone rapid
expansion in most countries with generalised epidemics, and many
more pregnant women are tested for HIV through PMTCT than in
UAT-based surveillance rounds. Efforts are underway to evaluate
the utility of PMTCT data for HIV surveillance and its potential to
replace the UAT-based ANC surveillance systems [49, 50].
In addition, periodic national household-based surveys (e.g.
AIDS Indicator Surveys or Demographic Household Surveys with
HIV testing) are recommended. The great advantage of such
surveys is the high precision of HIV estimates, the inclusion of both
men and women (and at times children), and the often detailed
HIV-related data collection. The key limitations of these surveys are
their huge costs and the resulting donor dependency.
HIV surveillance in East-Africa
Reflecting the early start of the HIV epidemic in East-Africa, HIV
surveillance started in the late 1980s. In Uganda, surveillance
was first passive and based on a WHO recommended clinical
case definition for AIDS in Africa [51]. Data collection began in
1987 and was primarily hospital-based. Serological HIV tests
for surveillance were introduced shortly thereafter. Following
WHO recommendations, surveillance was anchored among ANC
attendees; the first data were reported in 1987 [52]. All countries
in East-Africa comply with the WHO recommendations.
16
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Introduction
HIV surveillance among high-risk populations
Household surveys among the general population suffer the
potential of severe social desirability bias, leading to under-reporting
of high-risk behaviours, such as drug use, multiple sex partners,
anal sex, commercial sex, or even condom use. Many general
population based surveys do not include data measures related to
anal sex [53]. Further, unless very large sample sizes are achieved,
general population surveys also likely cannot sample many enough
high-risk individuals to warrant a meaningful analysis of such
sub-groups, prompting the conduct of separate data collection
activities aimed specifically at high-risk individuals. Such high-risk
groups, also termed “hidden populations” due to their low social
visibility, typically include FSWs, clients of FSWs, MSM, and IDUs.
Non-commercial sex partners and spouses of these groups are also
viewed at high-risk for HIV infection and serve as important bridging
populations between these core groups and the lower risk general
population. Other “high-risk groups”, defined on demographic,
rather than behavioural, characteristics, can include long distance
truck drivers, fishing communities, migrant workers, all of which are
characterised by their mobility, or impoverished populations such
as homeless populations or slum dwellers. However, generalising
these demographic groups as “high-risk” can overestimate the
number of persons at high-risk and divert resources otherwise
available for behaviour-based high-risk populations. A separate
high-risk group may be regarded as persons engaging in multiple
concurrent partnerships (partner concurrency) [54]. In generalised
epidemics, this sub-set of the general population may account for a
significant proportion of incident and prevalent HIV-infections but
is difficult to survey as demonstrated by the lack of specific survey
data on such individuals.
Measuring and monitoring HIV disease in high-risk groups
faces additional challenges and data requirements. Challenges
include the identification of high-risk individuals and their
17
1.indd 17
24.05.13 00:13
Chapter 1
reluctance to participate in surveys. Additional data requirements
include the geographic distribution of high-risk individuals and the
population size of these groups.
Another challenge is that traditional sampling designs such as
random or cluster sampling are usually infeasible as no complete
sampling frame is generally available. Alternatives for sampling
high-risk individuals include time-location sampling (TLS), and
respondent driven sampling (RDS) [55]. TLS is a suitable sampling
strategy when most members of a given high-risk group, such
as FSWs in brothels, IDUs attending treatment centres, street
children categorised by geographic location, or MSM frequenting
bars or other social venues, are present at distinct venues at any
one time [56-60]. RDS, a peer-referral sampling strategy, has been
proposed recently [61-63] and represents an advanced form of
snowball sampling [56, 64]. RDS surveys are increasingly being
used worldwide, including in Africa [65], despite limitations [66].
In East-Africa, HIV surveys among high-risk groups are
usually anecdotal, often limited to national capitals or few major
urban centres, and of varying quality, in particular with regard to
the sampling design which often amounted to little more than
convenience sampling. Surveys among FSWs and, less often, clients
of FSWs are among the oldest high-risk group surveillance efforts.
Surveys among IDUs are rare and limited to major coastal urban
settings such as Dar es Salaam, Tanzania, or Mombasa, Kenya.
Surveys among MSM are still the exception rather than the rule in
East-Africa.
The reasons why high-risk group surveys are less prominent
than surveillance efforts in the general population may be
an inadvertent consequence of epidemic classification, as
“generalised” epidemics may falsely suggest that everyone is at
equal (high) risk for HIV infection or that surveillance and control
of HIV in high-risk populations is less important. Other reasons
for the relative negligence of high-risk group surveillance may be
donor-driven, as organisations such as PEPFAR (the US President’s
18
1.indd 18
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Introduction
Emergency Plan for AIDS Relief, the largest HIV-related donor in
sub-Saharan Africa), the Global Fund for AIDS, TB, and Malaria,
and UNAIDS are focused on numerical target settings such as the
number of people in HIV care and treatment, or the number of
HIV-positive pregnant women taking ARVs, to which the much
smaller high-risk populations can “contribute” relatively little.
Finally, prevailing stigma against high-risk behaviours (sex work,
injection drug use, and especially homosexuality) is rampant in
much of Africa which hinders access not only to HIV services but
likely also contributes to reluctance to regularly collect survey and
surveillance data in these groups.
A range of methods are available to estimate the population
size of high-risk groups, including capture-recapture [67, 68] the
multiplier method [69], census and enumeration, as well as network
scale-up [70-72], all of which suffer from various limitations. Due
to the low social visibility of high-risk groups, such as MSM, IDU
and FSWs, methods that are implemented within the general
population (such as network scale-up) may need to be adjusted for
[73].
1.1.5 Modelling and projections
Surveys and surveillance usually report the burden of disease
through proportions, rates, and ratios. For HIV control efforts
though, donors, policy makers, and programme planners need to
also consider the absolute burden of disease and the population
sizes in need of interventions or services. Such indicators include
the number of persons that need to be tested for HIV, or admitted
to care or treatment. The absolute size of the HIV epidemic and
number of persons accessing services determines the resources
needed, including staff, infrastructure, and commodities. Countries
with generalised epidemics, including eastern African countries,
also often have significant population growth, which adds to the
growing absolute burden of HIV disease even in stable epidemic
scenarios.
19
1.indd 19
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Chapter 1
For the general population, HIV-related size estimates are
often obtained through modelling and projections, using tailored
software packages such as Spectrum [74]. These techniques
allow the estimation of new HIV infections, vertical infections and
AIDS deaths, and facilitate projections into the immediate future
years. ANC surveillance data play a key role as input data for such
modelling and projections exercises [75] as their trend data allow
to forecast the epidemic’s likely course into the future [74, 76]. In
the absence of near-complete health information systems, such
model and projection-based estimates provide critical information
to describe the estimated burden of HIV disease.
1.1.6 HIV control efforts
General principles
HIV control efforts have undergone remarkable change both
qualitatively and quantitatively. Early in the epidemic, in the 1980s,
control efforts largely consisted of collecting anecdotal data on the
scale of the epidemic, establishing nascent HIV monitoring systems,
beginning of screening programmes for blood donors, and calls for
a reduction in the number of sexual partners (“zero grazing” in
Uganda) [21, 77]. In the 1990s, eastern African nations witnessed
a continuation of substantial AIDS-related mortality without having
the means to emulate the triple ARV-based treatment programmes
industrialised countries began to establish. Hence, behaviour
change programmes (ABC – Abstinence, Being faithful, Condoms)
continued to be the only substantive tools available to Ministries of
Health in the region [78, 79], supported by donor funds that often
emphasized abstinence and “faithfulness”, de-emphasised the role
of condoms, and provided funds to faith-based organisations. Only
in the last decade, when massive donor funding began to pour
into sub-Saharan Africa, began the era of substantial decline in
mortality along with the rise of biomedical control programmes.
20
1.indd 20
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Introduction
Biomedical interventions
Theoretical models suggest a potential to minimise or even
eradicate HIV epidemics through a “Test & Treat” approach, i.e.,
identifying and placing all HIV-infected individuals on ART, either
alone or in combination with other interventions [80, 81]. However,
the global economic setting in recent years makes it unlikely that
the necessary funding will be made available, and concerns about
the ethics of such an approach as well as behavioural dis-inhibition
and ARV resistance question the validity of this theoretical
approach [82, 83]. Recent study findings suggest a large potential
of select biomedical interventions to curb the HIV epidemics in
Africa, including male medical circumcision (MMC), ART, PMTCT,
including family planning, microbicides and ARV-based preexposure prophylaxis (PrEP).
Effect of biomedical interventions
- ART can reduce HIV transmission among HIV-infected people
by 92% [84], to 96% [85]
- ARV-based PrEP can reduce HIV acquisition in uninfected
individuals in HIV-discordant relationships by 62%-73% [86]
- ARV-based PrEP may reduce HIV acquisition in MSM by an
estimated 44% [87]
- ARVs can reduce the risk of MTCT, to an estimated 11% for
single dose nevirapine [88, 89], 4% using dual ARV regimens
[90, 91], and 2% when using triple ARV regimens [13]
- MMC can reduce HIV acquisition risk by at least 60% [92-94]
- Latex condoms are estimated to have a 80% effectiveness in
preventing HIV transmission [95, 96]
- Microbicides can reduce HIV acquisition depending on the
level of adherence [97]
21
1.indd 21
24.05.13 00:13
Chapter 1
1.2 Epidemiology of selected blood-borne infections
HIV-related opportunistic infections (OIs) are defined as
infections that occur more frequently or in more severe form in
immunosuppressed HIV-infected individuals than in uninfected
individuals. OIs comprise a wide spectrum of viruses, bacteria,
protozoa, as well as fungal infections, and account for the bulk of
the HIV-related morbidity and mortality. Despite large-scale ART
programmes and the accompanying decline of OI-related morbidity
and mortality [98, 99], OIs continue to occur mostly because of late
HIV diagnosis, poor adherence to, or lack of ART uptake [100].
Several OIs are caused by blood-borne pathogens, including
hepatitis B and C virus, plasmodia spp., and human herpes virus
8. The high prevalence of HIV in East-Africa is reflected by even
higher HIV prevalences in hospitalised patients. At the same time,
the need for blood transfusions in East-Africa is substantial, due
in part to malarial anaemia, sickle cell anaemia, and obstetrical
complications. Screening of donated blood for blood-borne
pathogens has evolved dramatically in recent decades due to
increased funding and assays suitable for mass screening. Prior to
the recognition of the HIV pandemic, screening often was anecdotal
or non-existent and donors usually were recruited among relatives
of candidate transfusion recipients or were commercial donors –
both of which are more likely to carry blood-borne pathogens than
volunteer non-remunerated donors. Screening for syphilis and HIV
(antibodies) were among the first routine measures employed
in the 1980s, followed by testing for hepatitis B surface antigen.
Recently, screening for hepatitis C is increasingly common such as
at the Uganda Blood Transfusion Services. The short refrigeration
time of donated blood due to high demand and the non-removal of
the buffy coat may increase the transmissibility of (cell-associated)
pathogens.
22
1.indd 22
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Introduction
1.2.1 Human herpesvirus 8
Human herpesvirus 8
Human herpesvirus 8 (HHV-8), also known as Kaposi’s sarcoma (KS)associated herpesvirus, (KSHV) is a novel human gamma herpes
virus. HHV-8 was first identified in 1994 in KS lesions [101] and it is
now accepted that HHV-8 is the causative agent for KS [102-104]. In
KS specimens, HHV-8 DNA could be isolated in 83% to 100% of cases
regardless of the patient’s HIV status, or type of KS [105-107]. It is
also considered a candidate etiologic agent for B-cell lymphoma,
multicentric Castleman’s disease and potentially for other tumours
[108]. Although HHV-8 can be differentiated into several subtypes,
the importance of subtypes for transmission or pathogenesis is
unknown [109-111]. HHV-8 represents a classic OI in HIV-infected
individuals [112, 113] and HHV-8 sero-prevalences in East-Africa
are the highest in the world, with many estimates originating from
Uganda [114-116]. The widely discrepant prevalence estimates
within and across geographic regions likely also reflect the state of
development of HHV-8 testing technologies and current lack of a
gold standard.
Kaposi’s sarcoma
KS is a vascular neoplasm primarily affecting the skin, subcutaneous
tissue, and occasionally internal organs. KS is classified in four
epidemiological types [117-119]: Classical KS is seen mostly in
elderly men of Mediterranean origin or of Jewish descent. Endemic
KS was first described in Uganda and occurs mainly in eastern and
Central Africa, affecting men, women, and children, and tending
to have a more aggressive clinical course than classical KS. A third
form is known as immunosuppression-associated KS, found among
immunosuppressed patients such as organ transplant recipients.
The fourth type, KS among AIDS patients, termed epidemic KS, is
often the most frequent malignancy in patients with AIDS. Rates
of (AIDS-associated) KS are very high where both HIV and HHV-8
prevalences reach high levels, such as in Uganda where in the early
23
1.indd 23
24.05.13 00:13
Chapter 1
1990s KS accounted for approximately half of all cancers reported
to the National Cancer Registry [120]. The incidence of KS then
declined along with the decrease in HIV prevalence and expansion
of ART [120-123]. Similar trends have also been observed in other
parts of Africa, such as Zimbabwe [124, 125] and Zambia [126].
Seroprevalence of HHV-8 in East-Africa
In Africa, HHV-8 is primarily or at least partially acquired during
childhood, presumably by non-sexual routes [127-130]. In Uganda,
one study’s finding suggested an HHV-8 incidence of approximately
4% among children less than ten years of age [131]. Another study
found that seroprevalence reached high levels in young adults in
Uganda (35.5% by age 21 years), with little increase thereafter [132].
This suggest that HHV-8 seroprevalence in East-Africa rises sharply
during childhood and more slowly during adulthood [133] HHV-8
testing of stored plasma samples from a nationally representative
survey in Uganda estimated the HHV-8 seroprevalence among
adults aged 51-59 years as 56.2% [136].
Transmission of HHV-8
The modes of HHV-8 transmission are not yet fully understood. In
the U.S. and Europe, HIV-infected MSM are at the highest risk of
developing KS [103, 134, 135], significantly higher compared to AIDS
patients who acquired HIV by contaminated blood products, IDU or
through heterosexual contact [134]. KS has also been observed in
HIV-negative MSM and heterosexual men and women [136-138].
Evidence is accumulating that HHV-8 may also be transmitted via
organ transplantation, such as in kidney transplant recipients [139141]. Serological evidence indicates that HHV-8 may be vertically
transmitted [142, 143], although disputed by other studies [130].
A history of IDU was found to be a risk factor for HHV-8 infection,
raising concern that HHV-8 may be transmitted parentally, although
an examination of a historical cohort of US transfusion recipients
found no evidence of transfusion-related HHV-8 transmission
24
1.indd 24
24.05.13 00:13
Introduction
[144]. Studies have documented that horizontal, and perhaps
sexual transmission, are likely to be the primary modes of HHV-8
transmission in Africa [145].
HHV-8 transmission by transfusion
The question of blood-borne transmission of HHV-8 and mass
screening of donated blood for HHV-8 continues to be a research
issue awaiting further clarification [146, 147]. Although evidence
of HHV-8 infection has been found both among blood donors
[146] and transfusion recipients [115], to date, laboratory
and epidemiological studies have shown that risk of HHV-8
transmission by blood products either does not occur, or at most,
occurs infrequently [146-150]. According to epidemiologic studies,
persons with haemophilia in the United States who were infected
with HIV by blood products rarely develop KS and have a similar
prevalence of HHV-8 antibodies as the general population [148,
151]. Similarly, persons with AIDS who acquired HIV infection
through receipt of contaminated blood products have a low
incidence of KS [134, 138]. In a retrospective cross-sectional study
among Ugandan sickle-cell anaemia patients, a history of blood
transfusion was associated with small HHV-8 infection risk [152].
Several factors may have contributed to the fact that no
studies to date have been able to document HHV-8 transmission
by blood transfusion:
- Blood donors at risk for HHV-8 infection in the U.S. and
Europe, such as MSM, IDU, or persons infected with HIV or
hepatitis C, are routinely deferred from donating blood.
- HHV-8 transmission by blood may require a certain level of
viraemia that is generally not present in antibody-positive
individuals.
- The viability of HHV-8 in stored blood is unknown, but may be
diminished after refrigeration and storage.
- Routine virus inactivation and sterilisation procedures for
plasma derivatives may inactivate HHV-8.
25
1.indd 25
24.05.13 00:13
Chapter 1
In sub-Saharan Africa, the risk of HHV-8 transmission by blood
transfusion has barely been evaluated. Two major conditions are
different in the African setting. First, blood transfusions are often
given as whole blood units. As HHV-8 is a cell-associated virus [153]
and can be detected in peripheral blood mononuclear cells (PBMC)
[154], the risk for HHV-8 transmission is possibly higher if whole
blood is transfused. Second, HHV-8 seroprevalence, as well as
rates of endemic and AIDS-associated KS are much higher in Africa
than in North-America or Europe, suggesting an amplified risk of
transfusion-associated HHV-8 transmission in unscreened blood
[155]. The risk of HHV-8 transmission by blood transfusion may
further be higher in countries like Uganda than in industrialised
countries as the refrigerated storage time of blood units after
donation tends to be short due to high demand.
1.2.2 Plasmodium falciparum and other Plasmodia spp.
Human malaria is caused by four species of plasmodia, sporozoan
parasites: Plasmodium falciparum, Plasmodium vivax, Plasmodium
ovale, and Plasmodium malariae. Humans are the only reservoir
for these Plasmodia spp, all of which are transmitted by Anopheles
mosquitoes. Transmission of Plasmodia is infrequent in areas
where the altitude exceeds 2000 meters [156].
The burden of malarial disease in East-Africa is substantial.
The number of deaths per 100,000 population/year varies from
10 (Ethiopia), to 12 (Kenya), 15 (Rwanda), 87 (Tanzania), to 103
(Uganda) [157]. The vast majority of malaria-related deaths are
caused by P. falciparum; deaths mostly occur due to severe anaemia
or cerebral malaria. In highly endemic countries such as Tanzania
and Uganda, malaria is often the most frequent reason for blood
transfusions, mostly in children under five years of age.
HIV-infected persons appear to be at greater risk to develop
clinical malaria and are more likely to experience treatment failure
[158]. Although the magnitude of these interactions are modest
on the individual level, the large numbers of persons infected with
26
1.indd 26
24.05.13 00:13
Introduction
HIV and Plasmodia spp. in Africa suggests that even small levels
of such interactions may have a substantial impact on population
health [158], although contested by others for countries with low
HIV prevalence [159].
1.2.3 Hepatitis C virus
With the expansion of HIV treatment programmes in East-Africa,
patients’ life expectancies increased and the effects of hepatitis B
and C virus (HBV, HCV) co-infections become increasingly apparent
[160].
WHO estimates that some 170 million people are chronic
carriers of HCV [161] – far more than the number of HIV-infected
persons globally. Africa appears to have the highest HCV prevalence,
estimated at approximately 5% [162], but with significant variation:
highest in Central Africa (6%) and lowest in East-Africa (1.6%).
Many of the estimates do not stem from nationally representative
samples hence the true picture of HCV infection in sub-Saharan
Africa remains unclear. Within East-Africa, estimates range from
0.9% in Kenya to 6.6% in Uganda [162]. HCV prevalence among
hospitalised patients in Uganda was estimated to be 2.3% with
no difference between HIV-positive and HIV-negative patients
and no association with IDU [163]. Transmission of HCV centres
towards exposure to infected blood and blood products, including
unscreened transfused blood, IDU, and medical, dental, or cosmetic
procedures that involve exposure to HCV-infected blood products
[164]. Exposure to HCV among IDUs may be high, reaching 51.4% in
Kenya, and 22.2% in Tanzania [165]. Transmission from mother to
child or by sexual intercourse appears to be far less frequent as is
exposure to HCV-infected household items, such as shaving razors
or toothbrushes [164]. The lack of a good understanding of the
predominant mode of HCV transmission in Africa is of particular
significance as no effective HCV vaccine is available and treatment
is difficult to access.
27
1.indd 27
24.05.13 00:13
Chapter 1
Data on HIV/HCV co-infection in Africa are scarce but generally
assumed to be low [160]. In Cameroon, the rate of HIV/HCV coinfection in pregnant women was estimated at 0.001% [166].
Among HIV-infected individuals, the prevalence of HCV infection
varies widely by population group and setting: in Kenya, 3.7%
among HIV-infected in-patients [167] and 0.7% among HIV-infected
blood donors [168]. No signs of HCV infection were detected
Tanzanian blood donors [169, 170]. IDUs in Tanzania however do
show increased risk for HCV and HIV/HCV co-infection [171]. A
study in southern Ethiopia observed an anti-HCV positivity rate of
10.5% among HIV-infected voluntary counselling and testing (VCT)
clients [172]. Taken together, these data contrast industrialised
settings where rates of HIV/HCV co-infections generally are much
higher, which in turn suggests different transmission routes for HCV
and/or HIV in Africa.
Similar to HBV, HIV and HCV co-infected persons experience
less often a spontaneous clearance of their HCV infection [173] and
carry a higher risk of developing cirrhosis than HCV mono-infected
persons [174, 175], leading to a higher risk of decompensated liver
disease and related death [176]. Little is known about the effect
of HCV infection on HIV disease progression, and the few available
studies provide inconsistent observations [177-179].
HCV prevention
While almost all prevention programmes focus on preventing
HIV infection, the similarities in transmission may be of benefit
for the prevention of HCV. Efforts to prevent HCV infection
include screening of blood products, steps to reduce nosocomial
transmission through needles and syringes, making ARVs more
widely available, and condom promotion. These prevention efforts
will become increasingly important as the expansion of HIV-related
ART programmes likely will lead to more frequent in liver disease in
HIV and HCV co-infected persons. Few programmes in East-Africa
28
1.indd 28
24.05.13 00:13
Introduction
target IDUs for HIV/HCV prevention, reflecting the facts that most
HIV transmission occurs sexually, the paucity of data on IDU, and
the low social visibility of IDUs.
@2&(187.&-12!
!,<,""O/0'2&:.8+*".&'4+1/"'4"-:;%?@4&+*:"
1.3. Demographic profile of East-Africa
1.3.1 East-Africa: definition and boundaries
!,<,!""-:;%?@4&+*:P"(/4+$+%+'$":$(">')$(:&+/;!"
N$4&C+,(-.$! >b-67('! );)B! 0$3! :'! 8',-2'8! -2!
"""""Q+2)&/"!,!""N$4&C+,(-.$"
Figure 1.1 East-Africa
4'='($5! 9$34! ('475&-26! -2! &#'! -2.574-12! 1,!
8-,,'('2&! 6(17%4! 1,! .172&(-'4! $28! =$(3-26!
6'1%15-&-.$5! :1728$(-'4;! J15-&-.$553/! &#'!
N$4&C+,(-.$2! "10072-&3! >N+"B! .10%(-4'4!
^6$28$/! F'23$/! ^2-&'8! X'%7:5-.! 1,!
<$2[$2-$/! X9$28$/! $28! Y7(728-! P)E*Q;! <#'!
^2-&'8! h$&-124! >^hB! 8',-2'4! &#'! N$4&'(2!
+,(-.$2! X'6-12! $4! -2.578-26! $! &1&$5! 1,! )\!
2$&-124! >.10%(-4-26! &#'! N+"! 0'0:'(4! $4!
9'55!$4!"101(14/!WO-:17&-/!N(-&('$/!N&#-1%-$/!
R$8$6$4.$(/! R$5$9-/! R$7(-&-74/! R$31&&'/!
R1[$0:-K7'/!
Xo72-12/!
D'3.#'55'4/!
D10$5-$/! l$0:-$/! $28! l-0:$:9'! P)E)QB;!
N&#-1%-$/! N(-&('$/! WO-:17&-/! $28! D10$5-$! $('!
$541! 1,&'2! (','(('8! &1! $4! &#'! S?1(2! 1,!
+,(-.$T;! j'16($%#-.$553/! &#'! X-,&! A$55'3!
.124&-&7&'4! &#'! 8',-2-26! .#$($.&'(-4&-.! 1,!
N$4&C+,(-.$/! 'I&'28-26! ,(10! N&#-1%-$G4! +,$(!
!
8'%('44-12! &1! .'2&($5! R1[$0:-K7'! P)EHQ;!
b1(! &#'! %7(%14'! 1,! &#-4! &#'4-4/! &#'!
8'4.(-%&-12!1,!N$4&C+,(-.$!4#$55!,1.74!12!&#'!
East-Africa (Figure 1.1) may be defined in several ways resulting
N$4&C+,(-.$2! "10072-&3! $28! in
&#'!the
?1(2!
1,!
inclusion
of different groups of countries and varying
+,(-.$/! 9-&#! 4%'.-$5! $&&'2&-12!geopolitical
&1! ^6$28$/!boundaries. Politically, the East-African Community
F'23$/!$28!N&#-1%-$;!!
(EAC) comprises Uganda, Kenya, United Republic of Tanzania,
Rwanda, and Burundi [180]. The United Nations (UN) defines
!,<,9""=1+0:%/"
the Eastern African Region as including a total of 19 nations
N$4&C+,(-.$G4!.5-0$&'!-4!47(%(-4-2653!.115!$28d1(!8(3!6-='2!-&4!5$&-&78'!P)EHQ;!Y'.$74'!
(comprising the EAC members as well as Comoros, Djibouti, Eritrea,
5$(6'! $('$4! $('! 1,! #-6#! $5&-&78'/! &'0%'($&7('4! ('0$-2! 018'($&'! 8'4%-&'! N$4&C
29
+,(-.$G4! 51.$&-12! -2! &#'! &(1%-.$5! :'5&! 4&($885-26! &#'! 'K7$&1(;! b7(&#'(/! 47:4&$2&-$5!
$('$4! $('! 8(3! 1(! 'I&('0'53! 8(3/! %$(&53! 87'! &1! 0172&$-2! ($26'4! 47.#! $4! &#'!
X9'2[1(-! $28! N&#-1%-$2! #-6#5$284! 9#-.#! .('$&'! $! S($-2! 4#$819T! 1,! &#'! 9'4&'(53!
0124112!9-284!P)EZQ;!!
!,<,<""5+;%'&3"
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&1! ]***! Y;";/! :7&! 4%('$8! &1! &#'! 5195$284! 1253! .124-8'($:53! 5$&'(! P)E`Q;! <#'! 014&!
9-8'53! 4%1M'2! 5$267$6'4! -2! N$4&C+,(-.$! $('! &#'! U(101! $28! +0#$(-.! 8-$5'.&4! -2!
N&#-1%-$/!D10$5-!>D10$5-$B/!D9$#-5-!><$2[$2-$B!$28!+($:-.!4%1M'2!-2!410'!1,!N$4&C
+,(-.$G4!.1$4&$5!('6-124/!$28!,7(&#'(01('!270'(174!1&#'(!8-$5'.&4;!<#'!J1(&767'4'!
!1.indd
29
HZ!
24.05.13 00:13
Chapter 1
Ethiopia, Madagascar, Malawi, Mauritius, Mayotte, Mozambique,
Réunion, Seychelles, Somalia, Zambia, and Zimbabwe [181]).
Ethiopia, Eritrea, Djibouti, and Somalia are also often referred to
as the “Horn of Africa”. Geographically, the Rift Valley constitutes
the defining characteristic of East-Africa, extending from Ethiopia’s
Afar depression to central Mozambique [182]. For the purpose of
this thesis, the description of East-Africa shall focus on the EastAfrican Community and the Horn of Africa, with special attention
to Uganda, Kenya, and Ethiopia.
1.3.2 Climate
East-Africa’s climate is surprisingly cool and/or dry given its latitude
[182]. Because large areas are of high altitude, temperatures
remain moderate despite East-Africa’s location in the tropical
belt straddling the equator. Further, substantial areas are dry or
extremely dry, partly due to mountain ranges such as the Rwenzori
and Ethiopian highlands which create a “rain shadow” of the
westerly monsoon winds [183].
1.3.3 History
Home of modern humans [184], agriculture in the (Ethiopian)
highlands dates back to 7000 B.C., but spread to the lowlands only
considerably later [185]. The most widely spoken languages in
East-Africa are the Oromo and Amharic dialects in Ethiopia, Somali
(Somalia), Swahili (Tanzania) and Arabic spoken in some of EastAfrica’s coastal regions, and furthermore numerous other dialects.
The Portuguese were the first Europeans to establish a presence
in East-Africa, dating back to 1505 [186]. Their control was later
replaced by Omani Arabs, thus regaining control of the Indian
Ocean trade, including slaves and spices. In the 19th century, the
British Empire took a foothold in today’s Uganda, Kenya and coastal
Somalia, part of Europe’s “Scramble for Africa” that saw Germany
establishing German East-Africa (in today’s Tanzania), Portugal’s
control of Mozambique, and France’s seizure of island territories
in the Indian Ocean. Independence for East-African nations came
30
1.indd 30
24.05.13 00:13
"#$%&'(!)!
9'('!&#'!,-(4&!N7(1%'$24!&1!'4&$:5-4#!$!%('4'2.'!-2!N$4&C+,(-.$/!8$&-26!:$.M!&1!)`*`!
P)EaQ;!<#'-(!.12&(15!9$4!5$&'(!('%5$.'8!:3!U0$2-!+($:4/!&#74!('6$-2-26!.12&(15!1,!
&#
&#'!@28-$2!U.'$2!&($8'/!-2.578-26!45$='4!$28!4%-.'4;!@2!&#'!)\ !.'2&7(3/!&#'!Y(-&-4#!
Introduction
N0%-('! &11M! $! ,11&#158! -2! &18$3G4! ^6$28$/! F'23$! $28! .1$4&$5! D10$5-$/! %$(&! 1,!
N7(1%'G4!SD.($0:5'!,1(!+,(-.$T!&#$&!4$9!j'(0$23!'4&$:5-4#-26!j'(0$2!N$4&C+,(-.$!
in
the late 20th century, starting with Somalia (1960) and Tanzania
>-2! &18$3G4!
<$2[$2-$B/!
J1(&76$5G4! .12&(15!
1,! R1[$0:-K7'/!
$28!Burundi,
b($2.'G4! 4'-[7('!
1,!
(1961
in then
Tanganyika),
followed
by Rwanda,
Uganda
-45$28!&'((-&1(-'4!-2!&#'!@28-$2!U.'$2;!@28'%'28'2.'!,1(!N$4&C+,(-.$2!2$&-124!.$0'!
(1962),
Kenya
(1963),
Djibouti
(1977),
and
lastly
Eritrea
(1993).
&#
-2!&#'!5$&'!H*
Ethiopia
is an!.'2&7(3/!4&$(&-26!9-&#!D10$5-$!>)\a*B!$28!<$2[$2-$!>)\a)!-2!&#'2!
independent nation since the 4th century BC [187].
<$26$23-M$B/!,15519'8!:3!X9$28$/!Y7(728-/!^6$28$!>)\aHB/!F'23$!>)\aZB/!WO-:17&-!
&#
>)\]]B/! $28! 5$4&53! N(-&('$! >)\\ZB;! N&#-1%-$! -4! $2! -28'%'28'2&! 2$&-12! 4-2.'! &#'! _ !
1.3.4
Demography
.'2&7(3!Y"!P)E]Q;!
!,<,H""O/0'2&:.83"
East-Africa
experiences rapid population growth despite a decline
in
women’s
total fertility
rate (TFR)
over8'4%-&'!
the last
decades
(Table
N$4&C+,(-.$!
'I%'(-'2.'4!
($%-8! %1%75$&-12!
6(19&#!
$! 8'.5-2'!
-2! 910'2G4!
1.2).
Uganda’s
TFR
of
6.4
[188]
suggests
that
this
nation
is
growing
&1&$5!,'(&-5-&3!($&'!><bXB!1='(!&#'!5$4&!8'.$8'4!><$:5'!Z;)B;!^6$28$G4!<bX!1,!a;_!P)EEQ!
at
East-Africa’s
leading
to a population
doubling
4766'4&4!
&#$&! &#-4! fastest
2$&-12! -4!rate
6(19-26!
$&! N$4&C+,(-.$G4!
,$4&'4&! ($&'!
5'$8-26! time
&1! $!
of
approximately
21 1,!
years.
The HIVH)!epidemic
region
has
%1%75$&-12!
817:5-26! &-0'!
$%%(1I-0$&'53!
3'$(4;! <#'!in
?@A!this
'%-8'0-.!
-2! &#-4!
noticeably
slowed (but not halted) both the rise in life expectancy
('6-12!#$4!21&-.'$:53!4519'8!>:7&!21&!#$5&'8B!:1&#!&#'!(-4'!-2!5-,'!'I%'.&$2.3!$4!
9'55!$4!%1%75$&-12!6(19&#!P)E\Q;!
as
well as population growth [189].
!
A:>1/"!,<""W'016($%#-.!.#$($.&'(-4&-.4!,1(!4'5'.&!N$4&C+,(-.$2!.172&(-'4"
Table
1.2 Demographic characteristics for select East-African countries
!
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_;aa!
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_;\a!
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a;ZE!
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R-B",FC06"'/1,+%&0+N'
JN'."#:'
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)Z)!
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E/`)\!
E_/\]a!
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)*/H]]! ZZ/]\a!
ZH]/)Ea!
315$&%+01-'
7+?1$.%-B.9::'
*) 2005-2010
pB!H**`CH*)*!
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index.asp?panel=1, accessed 2nd Jan. 2011.
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1.indd 31
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31
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Chapter 1
1.4 Outline of this thesis
In Part 1 Chapter 2 examines the burden of HIV disease in
Uganda and the potential effects of selected HIV/AIDS control
programmes to mitigate it. Chapter 3 reports on the burden of and
risk factors for HIV disease among men who have sex with men in
Kampala, Uganda. Chapter 4 assessed the accessibility and quality
of Prevention of Mother-To-Child HIV Transmission (PMTCT)
programme data, as well as the utility for HIV surveillance, in
Kenya. Chapter 5 compares the effects of antiretroviral prophylaxis
for the prevention of PMTCT to that of existing family planning
use and estimates the burden of paediatric HIV disease due to
unwanted fertility in Uganda. In Chapter 6 we estimated the effect
of CD4+ levels and antiretroviral treatment on the specificity of a
widely used HIV recency assay, the BED enzyme immune assay,
and evaluated a HIV avidity assay to detect BED-based false-recent
results.
Part 2 focuses on HIV-related opportunistic infections and
blood transfusion. In Chapter 7 we evaluated the risk of human
herpesvirus 8 (HHV-8) transmission by blood transfusion in Uganda
where HHV-8 is endemic, through a prospective observational
cohort study of HHV-8-seronegative transfusion recipients receiving
HHV-8-seropositive or seronegative blood. HHV-8 is etiologically
linked to Kaposi’s sarcoma, representing up to half of all reported
cancers in Uganda. In Chapter 8 we assessed HHV-8 seroprevalence,
risk factors for infection, and HHV-8 serologic assays in a crosssectional study of candidate Ugandan blood donors. In Chapter
9 we evaluated the risk of mortality associated with transfusion
of HHV-8-antibody positive blood among transfusion recipients
in Kampala, Uganda. In Chapter 10 we examine the prevalence
of hepatitis C virus in candidate Ugandan blood donors and
associated screening costs. In Chapter 11 we assessed the effect
of HIV infection on morbidity and mortality in children receiving
32
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Introduction
blood transfusions due to severe malarial anaemia in Kampala,
Uganda. In the General Discussion in Chapter 12 the main findings
of this thesis are discussed. A summary is provided as well.
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