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Sexual violence (SV) is common during conflict. Despite reports of rape-related incidents of HIV infection, ecological analyses have found no association between SV and HIV at a population level. This has led to debate in the humanitarian, security and public health arenas about whether SV is an important HIV risk factor in conflict-affected settings. This paper uses published evidence on sexual violence in Africa and modelling to explore when SV may increase individual HIV risk and community HIV incidence. Publications on sexual violence in conflict settings were reviewed and a mathematical model describing the probability of HIV acquisition was adapted to include the potential effect of genital injury and used to estimate the relative risk of HIV acquisition in 'conflict' versus 'non-conflict' situations. An analytical equation was developed to estimate the impact of SV on HIV incidence. A rape survivor's individual HIV risk is determined by potentially compounding effects of genital injury, penetration by multiple perpetrators and the increased likelihood that SV perpetrators are HIV infected. Modelling analysis suggests risk ratios of between 2.4 and 27.1 for the scenarios considered. SV could increase HIV incidence by 10% if rape is widespread (>40%); genital injury increases HIV transmission (threefold or more); at least 10% of perpetrators are HIV infected and underlying HIV incidence is low (<0.5%). The analysis illustrates that SV is likely to be an important HIV risk factor in some conflict-affected settings. More generally, it indicates the limitations of using broad aggregate analysis to derive epidemiological conclusions. Conflict-related initiatives offer important opportunities to assist survivors and prevent future abuses through collaborative programming on reconstruction, HIV and sexual violence.
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Sexual violence and conflict in Africa: prevalence and
potential impact on HIV incidence
Charlotte H Watts,
1
Anna M Foss,
1
Mazeda Hossain,
1
Cathy Zimmerman,
1
Rachel von Simson,
1
Jennifer Klot
2
ABSTRACT
Background and aims Sexual violence (SV) is common
during conflict. Despite reports of rape-related incidents
of HIV infection, ecological analyses have found no
association between SV and HIV at a population level.
This has led to debate in the humanitarian, security and
public health arenas about whether SV is an important
HIV risk factor in conflict-affected settings. This paper
uses published evidence on sexual violence in Africa and
modelling to explore when SV may increase individual
HIV risk and community HIV incidence.
Methods Publications on sexual violence in conflict
settings were reviewed and a mathematical model
describing the probability of HIV acquisition was adapted
to include the potential effect of genital injury and used
to estimate the relative risk of HIV acquisition in ‘conflict’
versus ‘non-conflict’ situations. An analytical equation
was developed to estimate the impact of SV on HIV
incidence.
Results A rape survivor’s individual HIV risk is
determined by potentially compounding effects of genital
injury, penetration by multiple perpetrators and the
increased likelihood that SV perpetrators are HIV
infected. Modelling analysis suggests risk ratios of
between 2.4 and 27.1 for the scenarios considered. SV
could increase HIV incidence by 10% if rape is
widespread (>40%); genital injury increases HIV
transmission (threefold or more); at least 10% of
perpetrators are HIV infected and underlying HIV
incidence is low (<0.5%).
Conclusion The analysis illustrates that SV is likely to be
an important HIV risk factor in some conflict-affected
settings. More generally, it indicates the limitations of
using broad aggregate analysis to derive epidemiological
conclusions. Conflict-related initiatives offer important
opportunities to assist survivors and prevent future
abuses through collaborative programming on
reconstruction, HIV and sexual violence.
INTRODUCTION
Sexual violence (SV), including gang rape, forced
marriage and sexual slavery, is frequently part of
the cruel reality of war.
1
Although media reports
often focus on mass rape,
2
in practice, SV can take
many forms. Women may be threatened or coerced
into long-term sexual relationships by soldiers.
Women and girls may also form sexual relation-
ships with soldiers, border guards, peace keepers or
even aid workers in exchange for food, shelter,
protection or safe passage across borders. Although
less reported, men are also raped during conict.
3
Until recently, there was signicant concern that
HIV would thrive during conict periods in countries
such as Liberia, Rwanda, Democratic Republic of
Congo and Mozambique, and that widespread rape
and sexual coercion would play a central part in the
transmission of the virus.
4 5
In Rwanda, for example,
HIV infection levels as high as 70% were reported
among rape survivors after the genocide.
6
Epidemi-
ological research on HIV from several non-conict
African settings also found evidence of increased HIV
risk among women who had experienced SV,
7e9
with
a growing number of studies identifying a clustering
of STI risk behaviours among men who are violent,
suggesting that this increased risk is due to the use of
force and the associated disruption to the genital
epithelium and also to the increased likelihood that
the SV perpetrator is HIV infected.
10e12
Similarly,
other factors commonly associated with being HIV
infected have also been found to be connected to the
perpetration of SV, including alcohol use; multiple
sexual partners; unprotected casual sex; the likeli-
hood of anal sex; STIs; age difference between sexual
partners; access to and use of condoms (male and
female) and exchanging money or goods for sex.
13e16
Despite this identication of links between SV
and HIV, a review by Spiegel et al (2004) concluded
that there was limited evidence that conict
increases HIV risk, or that rape was associated with
increases in HIV at a population level.
17
Later,
Spiegel et al (2007) argued that their data showed
that conict in general had no epidemiologically
measurable impact and was not associated with
population HIV prevalence.
17
Subsequently, Anema
et al (2008) used mathematical modelling in
different conict-affected sub-Saharan Africa
settings to show that widespread rape only raises
the overall level of HIV prevalence in a country by
0.023%.
18
This evidence on conict, SV and HIV has fuelled
a heated debate within the humanitarian, security
and public health arenas about whether SV is an
important risk factor for HIV. Doubts about
potential impact have led some groups to interpret
the lack of association at a population level to
indicate that rape has no association with HIV and
to question the value of dealing with SV as part of
HIV programming.
However, the studies that fail to nd an associ-
ation between SV and HIV have compared aggre-
gated population-level data of HIV prevalence and
experiences of violence. Such ecological analyses use
several separate data sources and are inherently
exploratory. More broadly, the use of aggregate,
population data may mask the effect of competing
forces particular to conict settings, which may
lead to reductions or increases in HIV infection. For
example, although conict often fosters SV, which
<An additional appendix is
published online only. To view
this file please visit the journal
online (http://sti.bmj.com).
1
Department of Global Health
and Development, London
School of Hygiene and Tropical
Medicine (LSHTM), London, UK
2
Social Science Research
Council, New York, USA
Correspondence to
Dr Charlotte Watts, Department
of Global Health and
Development, Faculty of Public
Health and Policy, London
School of Hygiene and Tropical
Medicine (LSHTM), 15e17
Tavistock Place, London, UK;
charlotte.watts@lshtm.ac.uk
Accepted 15 September 2010
Watts CH, Foss AM, Hossain M, et al.Sex Transm Infect (2010). doi:10.1136/sti.2010.044610 1 of 7
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may lead to increases in HIV risk, conict-related factors, such as
restrictions on population movements, population curfews and
the separation of families, may also reduce opportunities for sex
and widespread HIV transmission.
19 20
Clearer insights into the ways SV affects HIV risk in different
African settings where HIV is prevalent could be obtained by
comparing the prevalence of HIV infection among women or
men who have been assaulted with those who have not. To
advance the debate, this paper presents current evidence on the
extent of SV against women and men in different conict-
affected settings in sub-Saharan Africa, and then uses mathe-
matical HIV modelling to explore the extent to which SV may
increase individual HIV risk and investigate situations where SV
may lead to substantial increases in community- or population-
level HIV incidence.
METHODS
We searched published and grey literature to compile existing
evidence on the extent of SV against women and men in six sub-
Saharan African countries that had recently experienced a period
of armed conict.
An established mathematical model of the probability of HIV
acquisition
21e23
was adapted to incorporate the potential for an
increased risk of HIV transmission if genital injury occurs during
sex and used to derive an analytical equation to describe the
increased relative risk (RR) of HIV acquisition in a conict
situation versus a comparablenon-conict scenario (online
supplementary appendix). A number of plausible scenarios were
developed to reect situations that might arise in high- and low-
conict situations. Scenarios included gang rape, anal rape and
transactional sex. Owing to lack of evidence about condom use
in conict situations, for the purposes of the modelling, we
generally assumed that condom use was negligible.
Similarly, an analytical equation was developed (supplemen-
tary appendix) to consider the extent to which rape may
increase HIV incidence at a community level. Different
assumptions were made about the underlying HIV incidence,
HIV and STI prevalence, the prevalence of rape and the effect of
genital injury on transmission risk. In contrast to previous
published analyses,
18
we assessed the extent to which SV may
contribute to HIV incidence rather than population prevalence.
Given the different underlying HIV incidence that may occur
between settings, in the analysis we consider the annual popu-
lation HIV incidence in the range 0.5e2.5%.
24
Mathematical modelling of the effect of genital injury requires
an input to describe how the use of force may affect the risk of
HIV acquisition for each sex act. There is evidence that during
forced sex, genital injury and vaginal bleeding are much more
common than in consensual sex, with the literature distin-
guishing between assaults with single versus multiple sites of
trauma.
25
Genital injury disrupts the multilayered stratied
epithelium that lines a womans reproductive tract and acts as
a natural barrier to infection. Bleeding during sexual assault may
also be associated with increased risk. For example, in a study of
seroconversion rates in HIV discordant couples, those reporting
non-menstrual bleeding during sexual intercourse were 4.9 times
more likely to have seroconverted.
26
In the absence of data on
how this may affect the probability of HIV transmission for
each sex act, in the modelling analysis we assume that genital
trauma (and/or anal trauma for anal rape) increases the per sex
act risk of HIV acquisition 1.5-, 3- or 6-fold, depending on the
extent of trauma. These values were extrapolated from the
epidemiological literature on the extent to which concurrent STI
infection increases the risk of HIV acquisition for each sex act,
with the cofactor of 3 comparable to the values commonly cited
for a range of different STIs.
27 28
These values were considered
conservative, especially in situations where severe force has been
used. In the anal rape scenario, penile-anal sex compared with
penile-vaginal sex was assumed to entail a fourfold increase in
risk of HIV transmission.
29e31
An important input was the relative prevalence of HIV and
STI infection among men who perpetrate SV compared with
other men in that setting. The parameterisation of this input is
difcult, however, as it depends on how long the perpetrator has
been sexually active; their previous patterns of sexual behaviour;
likelihood of exposure to HIV; and the extent to which they
have previously used condoms or received STI treatment (which
will reduce the likelihood that they are HIV infected). For the
purposes of this model, we drew on evidence from non-conict
settings about the increased risk of HIV among the perpetrators
of SV and assume that HIVand STI prevalence among men who
perpetrate rape is twice as high as among less violent men.
7 12 32
Other epidemiological parameter values used in the modelling
of community HIV incidence were taken from the academic
literature, and were set to the values commonly used in the
modelling of HIV in sub-Saharan Africa. These include the
probability of HIV transmission for each sex act of 0.002 for
penile-vaginal sex;
29
5% of those HIV-infected having high HIV
viral load
33e36
; and high viral load increases probability of HIV
transmission 10-fold.
37
The parameters associated with high
HIV viral load were assumed to be the same among perpetrators
of SV as among less violent men.
Sensitivity analyses, where different assumptions were
essentially turned off or varied, were used to explore the
robustness of the ndings to these different assumptions.
RESULTS
Published evidence on the prevalence of SV in conict is
presented in table 1. Among settings with recently ended
conicts, lifetime levels of sexual violenceand rape or sexual
abuseexperienced by women ranged from 42.3% in Liberia to
14%
42
in Cote dIvoire.
39
SV reported during conict ranged
from 35.3% in Liberia
42
to 0.2% in Cote dIvoire.
39
While in
a setting with a prolonged conict, service records from
Democratic Republic of Congo report over 20 000 SV cases
between 2003 and 2008.
40
Owing to methodological and
contextual differences it is difcult to compare these gures
across settings as each study used different study populations;
denitions of sexual abuse and time periods. Research on SV
against men, though sparse, generally reported lower levels than
SV against women.
39 42 45
Projections of the impact of sexual violence on individual HIV
risk
Modelling projections can be used to get a sense of the extent to
which an individuals risk of HIV may be inuenced by SV,
coercion and transactional sex. In practice, however, the absolute
levels of risk are likely to be highly context specic. For this
reason we focus here on estimating the risk ratios, comparing
conict-related scenarios with comparablenon-conict
scenarios. We consider risk ratios because these are less context
specic. For the scenarios presented they are not dependent on
underlying population prevalence of HIV, since this term cancels
in the calculation of risk ratios (supplementary appendix).
Hence, these ndings apply for any given underlying prevalence
of HIV.
2 of 7 Watts CH, Foss AM, Hossain M, et al.Sex Transm Infect (2010). doi:10.1136/sti.2010.044610
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The scenarios presented suggest that there may be large
increases in individual HIV risk associated with SV in conict-
affected settings. The ndings also illustrate how the risk ratios
of HIV infection are largely determined by a combination of
relative measures, which include the extent to which a perpe-
trator of SV may be infected with HIV or other STIs compared
with other sexual partners; the number of forced sex acts
compared with consensual sex acts; whether the sex acts are
anal or vaginal and the number of assailants compared with
other partners. The probability of HIV transmission during
a violent sex act, in turn, also depends upon the extent of genital
trauma, and the degree to which this increases the probability of
HIV transmission.
To illustrate how the results are affected by the different
factors, the right hand columns of table 2 show how the risk
ratios vary according to the different assumptions. All scenarios
show that individual risk of HIV more than doubles, even if
there is no genital trauma or if genital injury does not increase
the risk of HIV acquisition for each sex act (assuming HIV and
STI prevalence are twice as high among violent men as among
comparison men). Alternatively, individual risk of HIValso more
than doubles if we instead assume that there is an increase in the
risk of HIV acquisition for each sex act from genital trauma that
occurs during forced sex and HIV prevalence is twice as high
among violent men as among comparison men (and this holds
even if STI prevalence is no higher among violent men).
Projections of the impact of sexual violence on community HIV
incidence
A question raised in recent debates in the conict eld is whether
SV could lead to increases in HIV at a population-level.
17
Table 3
shows projections of how HIV incidence may be affected by SV.
In general, the proportion of HIV incidence that is attributable
to SV increases proportionally with the prevalence of forced sex,
the likelihood that the perpetrator is HIV infected and the
cofactor effect of genital trauma. The contribution of SV to
community HIV incidence is lower in high HIVincidence settings,
because there is a greater underlying risk of HIV acquisition.
There are a range of situations where SV might potentially
increase community HIV incidence by more than 10%
(emboldened in table 3). For example, where HIV incidence is
#0.5% in the absence of SV, community incidence would be
increased by more than a tenth if more than 20% of women had
experienced SV, genital injury increased HIV transmission
sixfold or more and at least 10% of perpetrators were HIV
infected.
If the STI prevalence is higher, an even larger increase in
community HIV incidence may occur (data not shown).
Table 1 Sexual violence in selected sub-Saharan African countries with armed conflicts
Country
Sexual violence (SV)
Type
Time
period Study population Survey/sampling type Reference
Women Men
% Total (n) %
Total
(n)
Burundi 27 339 ee Sexual Violence Conflict Women aged 12e49 years,
refugee camp in Tanzania
Cross-sectional/systematic
random sampling
Nduna and
Goodyear
1997
38
9.5 68 ee Anal rape Conflict Women aged 12e49 years
reporting SV, refugee camp
in Tanzania
Cross-sectional/systematic
random sampling
Nduna and
Goodyear
1997
38
Cote
d’Ivoire
14.0 8238 5.3 4175 Forced sex/rape Lifetime Individuals aged 10e49
in urban and rural settings,
national
Population-based household
survey/stratified random sampling
MFFAS and
UNFPA 2008
39
4.8 8238 1.7 4175 Forced sex/rape Past
12 months
Individuals aged 10e49
in urban and rural settings,
national
Population-based household
survey/stratified random sampling
MFFAS and
UNFPA 2008
39
0.2 8238 0 4175 Rape Conflict Individuals aged 10e49
in urban and rural settings,
national
Population-based household
survey/stratified random sampling
MFFAS and
UNFPA 2008
39
Democratic
Republic
of Congo
(DRC)
e20517 ee Rape, penetrative
sexual assault
Conflict Women and girls attending
medico-social support
programme
Service records Steiner 2009
40
e218 ee Sexual violence Conflict Cases reported and verified
by UN Mission in DRC
Incident records Taback 2008
41
Liberia 42.3 182 32.6 367 Sexual violence Lifetime Adult former combatants
aged 18*
Cross-sectional/systematic
random and cluster sampling
Johnson 2008
42
35.3 180 16.5 360 Sexual servant/slave Conflict Adult former combatants
aged 18*
Cross-sectional/systematic
random and cluster sampling
Johnson 2008
42
9.2 698 7.4 419 Sexual violence Lifetime Adult non-combatants
aged 18*
Cross-sectional/systematic
random and cluster sampling
Johnson 2008
42
17.6 4897 ee Sexual violence Lifetime Women aged 15e49,
national
Population-based household
survey/stratified random sampling
DHS 2007
43
10.8 3678 ee SV by recent partner Past
12 months
Women aged 15e49, national,
ever-married
Population-based household
survey/stratified random sampling
DHS 2007
43
Rwanda 11.7* 244* * * SV, experienced or
knew
close family member
Conflict Adults aged 18* living in
four communes exposed
to conflict
Household survey/multistage
cluster sampling
Pham 2004
44
Uganda,
Northern
27.7 118 3.9 108 Sexual violence Lifetime IDPs aged 15e49 Population-based household survey/
stratified random sampling
DHS 2007
45
*Figures are not disaggregated by sex.
DRC, Democratic Republic of Congo; IDP, Internally displaced person; MFFAS, Ministe
`re de la Famille, de la Femme et des Affaires Sociales; SV, Sexual violence; UN, United Nations; UNFPA,
United Nations Population Fund.
Watts CH, Foss AM, Hossain M, et al.Sex Transm Infect (2010). doi:10.1136/sti.2010.044610 3 of 7
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Table 2 Comparative model estimates of the relative increase in individual HIV risk for different illustrative conflict scenarios
Conflict
scenario
Comparison
scenario
Description
of model
assumptions
RR Sensitivity of RR to varying assumptions
Base case* Variation from base case*
Assuming
genital injury
facilitates
HIV, and HIV
and STI
prevalence among
violent
men is double
that of general
population
Assuming no
genital injury
and/or no
increased
risk through genital
injury
Assuming genital
injury increases
risk per sex
act more
extensively
(6-fold instead
of 3-fold, or 3-fold
instead of
1.5-fold)
Assuming
HIV and STI
prevalence
among violent
men same as
in general
population
Assuming HIV
prevalence among
violent men same
as in general
population
Assuming STI
prevalence among
violent men same
as in general
population (10%)
Assuming half
underlying STI
prevalence to
5% among men
and women in
general population
(10% among
violent men)
Assuming double
underlying STI
prevalence to 20%
among men and
women in general
population (40%
among violent men)
Adult female,
forced to
have sex
by any
number
of men
Same number of
consensual sex acts
with one low-risk
partner from own
community
Genital injury occurs
in all forced sex acts
and increases HIV
transmission per sex
act 3-fold, and the
number of
perpetrators in
conflict scenario is
equal to the number
of sex acts with
low-risk partner in
comparison scenario
6.8 2.3 13.6 3.0 3.4 6.0 6.5 7.1
Anal rape of
adult male
or female by
any number
of men
Same number of
consensual penile-
vaginal sex acts
with one low-risk
partner from own
community
Genital injury occurs
in all forced sex acts
and increases HIV
transmission per sex
act 3-fold (and the
transmission
probability is four
times higher
in anal sex than
penile-vaginal sex),
and number of
perpetrators in
conflict scenario is
equal to the number
of sex acts with low
risk partner in
comparison scenario
27.1 9.0 54.3 12.0 13.6 24.0 25.9 28.5
Adult female
trades sex
with several
men (injury once
in every 8
sex acts)
Same number
of consensual
sex acts with
one man from
own community
Genital injury occurs
once in every eight
sex acts in conflict
scenario and
increases HIV
transmission per
sex act 1.5-fold, and
number of partners/
perpetrators in
conflict scenario is
equal to the number
of sex acts with
low-risk partner in
comparison scenario
2.4 2.3 2.8 1.1 1.2 2.1 2.3 2.5
Continued
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Table 2 Continued
Conflict
scenario
Comparison
scenario
Description
of model
assumptions
RR Sensitivity of RR to varying assumptions
Base case* Variation from base case*
Assuming
genital injury
facilitates
HIV, and HIV
and STI
prevalence among
violent
men is double
that of general
population
Assuming no
genital injury
and/or no
increased
risk through genital
injury
Assuming genital
injury increases
risk per sex
act more
extensively
(6-fold instead
of 3-fold, or 3-fold
instead of
1.5-fold)
Assuming
HIV and STI
prevalence
among violent
men same as
in general
population
Assuming HIV
prevalence among
violent men same
as in general
population
Assuming STI
prevalence among
violent men same
as in general
population (10%)
Assuming half
underlying STI
prevalence to
5% among men
and women in
general population
(10% among
violent men)
Assuming double
underlying STI
prevalence to 20%
among men and
women in general
population (40%
among violent men)
Adult woman,
quarter of sex acts
are forced by her
highly exposed
male partner
Same number
of consensual sex
acts with male
partner who has
not been in a higher-
risk situation
Genital injury occurs
once in every four
sex acts in conflict
scenario and
increases HIV
transmission per
sex act 1.5-fold, and
number of sex acts
is the same in
conflict and
comparison
scenarios
2.5 2.3 3.4 1.1 1.3 2.3 2.4 2.7
*For all base case scenarios assume that HIV and STI prevalences are twice as high among violent men than in comparison men in general population (and 10% STI prevalence among men and women in general population), and STI increases HIV transmission per
sex act threefold.
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However, if genital injury increases HIV transmission just 1.5-
fold, a greater than 10% increase in the 0.5% community HIV
incidence would only occur if more than 40% of women were
raped and at least 20% of perpetrators were HIV infected (not
shown in table 3).
DISCUSSION
SV is an extreme violation of human rights that results in
profound and often enduring health problems. Although
signicant attention has been given recently to rape in war, there
is still confusion about whether it may be an important risk
factor for HIV in some conict settings. SV is seldom included in
epidemiological projections of HIV transmission.
Our review suggests that high levels of SV have occurred in
several African conict settings. Although the modelling
presented here is limited by the data available and the challenge
of developing comparable conict versus non-conict scenarios,
where the SV and HIV epidemics overlap it is plausible that SV
leads to substantial increases in individual HIV risk. This
increased risk is likely to be due to both the biological effect of
genital injury, and the potential clustering of behavioural risk
factors among men who perpetrate rape, which make them
more likely to be HIV- and STI-infected than non-perpetrators.
Our modelling also shows that SV may contribute to HIV
incidence, particularly when the underlying incidence of HIV
infection is low and/or the extent of sexual violence and genital
trauma is high. These ndings suggest that SV may lead to
increases in HIV incidence at a community leveldfor example,
in villages where systematic or mass rape has occurred. The
main limitation of the modelling is that it is a static model,
meaning that it cannot consider the transmission dynamics of
HIV in terms of secondary and tertiary HIV infections, some of
which may be indirectly attributable to SV. However, over
a short timeframe in which the underlying sexual behaviour and
epidemic remain fairly constant, other analyses suggest that
ndings from dynamic modelling are often still driven by the
factors contained in the static risk equation.
46
Epidemiologically, this analysis illustrates the dangers of
confusing population-level and individual-level effects, and
focusing on broad aggregate analysis to derive lessons about the
drivers of HIV infection. If rebel forces have systematically raped
certain populations or villages, for example, these individuals
and groups may be at high HIV risk, yet this effect may not be
detected at a population level if they are not considered sepa-
rately. By aggregating data from dynamic and heterogeneous
contexts such as conict-affected settings, where there are
competing inuences on transmission, there is a danger that
important risk factors will be overlooked.
Table 3 Modelled projections of the potential increase in community HIV incidence, for different assumptions about underlying HIV incidence, and the
prevalence of sexual violence, HIV, STIs and the extent of genital injury
HIV incidence
without sexual
violence (%)
Percentage of
women forced to
have sex (%)*
HIV prevalence
among violent
men (%)
HIV incidence with
sexual violence (%)*
Relative % increase
in HIV incidence due
to sexual violence*
HIV incidence with
sexual violence (%)*
Relative % increase
in HIV incidence
due to sexual violence *
If genital injury increases the probability
of HIV transmission per sex act 3-fold
If genital injury increases the probability
of HIV transmission per sex act 6-fold
0.50 20 10 0.53 5.40 0.55 10.80
1.50 20 10 1.53 1.78 1.55 3.56
2.50 20 10 2.53 1.06 2.55 2.12
0.50 40 10 0.55 10.80 0.61 21.61
1.50 40 10 1.55 3.56 1.61 7.13
2.50 40 10 2.55 2.12 2.61 4.23
0.50 60 10 0.58 16.20 0.66 32.41
1.50 60 10 1.58 5.35 1.66 10.69
2.50 60 10 2.58 3.18 2.66 6.35
0.50 20 20 0.55 10.80 0.61 21.61
1.50 20 20 1.55 3.56 1.61 7.13
2.50 20 20 2.55 2.12 2.61 4.23
0.50 40 20 0.61 21.61 0.72 43.21
1.50 40 20 1.61 7.13 1.71 14.26
2.50 40 20 2.61 4.23 2.71 8.47
0.50 60 20 0.66 32.41 0.82 64.82
1.50 60 20 1.66 10.69 1.82 21.39
2.50 60 20 2.66 6.35 2.82 12.70
*For the purposes of these calculations it is assumed that when a woman experiences sexual violence she has one perpetrator who violently forces sex once, causing multiple site genital injury
so that the per sex act risk of HIV transmission during this sexual violence is increased three- or sixfold.
The presence of an STI is assumed to increase HIV transmission per sex act threefold whereas high viral load is assumed to increase HIV transmission per sex act 10-fold (and 5% of
HIV-infected perpetrators have high viral load).
The HIV transmission probability per sex act without any cofactors is 0.002. Scenarios that led to >10% increase in annual incidence are shown in bold.
Key messages
<Sexual violence (SV) is common during conflict. Despite
reports of rape-related HIV infection, population ecological
analyses have found no association between violence and HIV.
<For a range of SV scenarios, modelling suggests that a rape
survivor’s individual risk may increase by a factor of 2.4 to
27.1.
<The contribution of SV to HIV incidence is determined by rape
prevalence, genital injury, perpetrator HIV prevalence and
underlying incidence. Situations exist where the incidence
increases by 10%.
<Conflict-related initiatives offer important opportunities to
assist survivors and prevent future abuses through collabo-
rative programming on reconstruction, HIV and sexual
violence.
6 of 7 Watts CH, Foss AM, Hossain M, et al.Sex Transm Infect (2010). doi:10.1136/sti.2010.044610
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The international community, through its various agencies,
such as the Security Council, Inter-Agency Standing Committee
and UN Action (a recent initiative that aims to prevent wartime
rape becoming a peacetime norm) have provided a clear mandate
for a strong response to sexual violence.
47
For too long, we have
had a narrow perspective of the epidemic and its drivers. We
need a more nuanced understanding of the epidemiology of
the virus and the contexts that create HIV vulnerability.
Conict-related initiatives offer important opportunities to
assist survivors and prevent future abuses through collaborative
programming that links reconstruction, HIV, sexual violence and
womens empowerment.
Acknowledgements Support for this research was provided by the AIDS, Security
and Conflict Initiative, convened by the Netherlands Institute of International
Relations ‘Clingendael’ and the Social Science Research Council. Partial funding for
this analysis also came from the Sigrid Rausing Trust. AMF and CHW are also
members of the DFID-funded Research Programme Consortium for Research and
Capacity Building in Sexual and Reproductive Health and HIV in Developing Countries
of the LSHTM.
Funding AIDS, Security and Conflict Initiative, convened by the Netherlands Institute
of International Relations ‘Clingendael’ and the Social Science Research Council. Partial
funding for this analysis also came from the Sigrid Rausing Trust.
Competing interests None.
Provenance and peer review Not commissioned; externally peer reviewed.
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... Out of every six children, one is recorded as being resident in an area of armed conflict and with such conflict occurrences, are the deaths of civilians (Rieder and Choonara, 2011). Sexual violence (SV) is a common feature during conflicts (Watts et al., 2010). SV represents an abuse of human rights with lingering lifetime health effects. ...
... The relationship between conflicts and health are varied. According to Watts et al. (2010) the SV categorized under forced marriages, gang rape (for both men and women) and sexual slavery are some of the cruelties experienced during conflict which sets the stage for many health-related challenges such as malnutrition, sexually transmitted diseases, unwanted pregnancies etc. but unfortunately, reportage on some of these focus mainly on mass rape (Wakabi, 2008;Plisik, 2009 Rieder and Choonara (2011) present in their article, Armed Conflict and Child Health, rather worrisome dimensions of effects of conflict. The lives and the economic potential lost to conflicts in Africa remain a concern, a concern that can only be understood and appreciated in the rebuilding and redevelopment stage of the countries. ...
Thesis
The Universal Health Coverage (UHC) has become a globally accepted concept and medium of providing healthcare to populations equitably and it’s a goal from the third Sustainable Development Goals (SDG), to be achieved by 2030. It has been described as one of the most progressive concepts to transform lives. Ghana in 2003 initiated its own form of the UHC through the establishment of the National Health Insurance Scheme (NHIS) and the continuation of the Community Health-Based Planning and Services (CHPS) implementation. It was a political decision which brought together different interest groups. The implementation of this decision saw healthcare expenditure shoot up to 10.6 percent as a share of Gross Domestic Product (GDP) in 2007. After more than a decade, the UHC (NHIS) has stagnated in growth. This study looks at the NHIS’ implementation from the point of view of the Social Determinants of Health (SDH) and what it could mean for growth if the Health in All Policies (HiAP) concept was applied. Through the use of Kingdon’s theoretical framework in terms of multiple-streams framework and agendas, alternatives and public policies, the policy process and environment are assessed. The research method used was qualitative case study. Some of the research outcomes were that there are undercurrents of tensions existing between a purely voluntary approach to the implementation of the UHC policy and the quasi-compulsory approach adopted by the country. In conclusion, the research finds that financially, it is not feasible to continue with the current strategy. There is the need to seek better institutional complementarities in pursuant of the UHC and adoption of the SDH.
... Besides the known risk of mother to child transmission, HIV/AIDS is also reported to have other adverse pregnancy complications [7] and is the leading cause of death among women of reproductive age [8]. In sub-Saharan Africa, the disproportionate burden of HIV/AIDS among women is attributed to lack of power, early marriages, coerced first sex, limited access to reproductive health services, extreme poverty, sexual violence, wars and conflict [9,10]. ...
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Background and aim For over 40 years of the HIV/AIDS global epidemic, no effective cure nor vaccine is yet available, making the current control strategies focused on curbing new infections through risk reduction. The study aimed to determine the prevalence of HIV risk factors and their associated socio-demographics among women of reproductive age in Sierra Leone. Methods We used weighted data from the Sierra Leone Demographic and Health Survey (SLDHS) of 2019 for 12,005 women aged 15–49 years. Multistage sampling was used to select study participants. Exposure to HIV risk factors was considered if a woman reported at least one of the following; having multiple sexual partners, transactional sex, non-condom use for the unmarried, and having other sexually transmitted infections (STIs). We, then, conducted multivariable logistic regression to explore the associated socio-demographics. All the analyses were done using SPSS (version 25). Results Of the 12,005 women, 38.1% (4577/12005) (95% confidence interval (CI) 37.3–39.0) had at least one of the four risk factors. Women of 15 to 19 years (adjusted odds ratio (AOR) = 1.34, 95% CI 1.00–1.80) and 20 to 34 years (AOR = 1.25, 95% CI 1.05–1.49) had more odds of having HIV risk factors compared to those of 35 to 49 years. Urban residents (AOR = 1.49, 95% CI 1.17–1.89) and those from the Northwestern region (AOR = 1.81, 95% CI 1.26–2.60) were also more likely to encounter HIV risk factors compared to their respective counterparts. Moreover, unmarried women (AOR = 111.17, 95% CI 87.55–141.18) and those working (AOR = 1.38, 95% CI 1.14–1.67) also had higher odds of having HIV risk factors, compared to their respective counterparts. Sex of household head and parity were also significant associates. Conclusions More than a third of women in Sierra Leone had encountered at least one HIV risk factor, and this was associated with age, place of residence, region, marital status, working status, household head and parity. There is a need for strengthening HIV/AIDS education programs, laws and policies targeting the young, working, unmarried and urban-resident women.
... Besides the known risk of mother to child transmission, HIV/AIDS is also reported to have other adverse pregnancy complications [7] and is the leading cause of death among women of reproductive age [8]. In sub-Saharan Africa, the disproportionate burden of HIV/AIDS among women is attributed to lack of power, early marriages, coerced rst sex, limited access to reproductive health services, extreme poverty, sexual violence, wars and con ict [9,10]. ...
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Background and aim: For over 40 years of the HIV/AIDS global epidemic, no effective cure nor vaccine is yet available, making the current control strategies focused on curbing new infections through risk reduction. The study aimed to determine the burden (prevalence) of HIV risk factors and their associated socio-demographics among women of reproductive age in Sierra Leone. Methods: We used weighted data from the Sierra Leone Demographic and Health Survey (SLDHS) of 2019 for 12,005 women aged 15-49 years. Multistage sampling was used to select study participants. Exposure to HIV risk factors was considered if a woman reported at least one of the following; having multiple sexual partners, transactional sex, non-condom use for the unmarried, and having other sexually transmitted infections (STIs). We, then, conducted multivariable logistic regression to explore the associated socio-demographics. All the analyses were done using SPSS (version 25). Results: Of the 12,005 women, 38.1% (4577/12005) (95% confidence interval (CI): 37.3-39.0) had at least one of the four risk factors. Women of 15 to 19 years (adjusted odds ratio (AOR)=1.34, 95% CI: 1.00-1.80) and 20 to 34 years (AOR=1.25, 95% CI: 1.05-1.49) had more odds of having HIV risk factors compared to those of 35 to 49 years. Urban residents (AOR=1.49, 95% CI: 1.17-1.89) and those from the Northwestern region (AOR=1.81, 95% CI: 1.26-2.60) were also more likely to encounter HIV risk factors compared to their respective counterparts. Moreover, unmarried women (AOR=111.17, 95% CI: 87.55-141.18) and those working (AOR=1.38, 95% CI: 1.14-1.67) also had higher odds of having HIV risk factors, compared to their respective counterparts. Sex of household head and parity were also significant associates. Conclusions: More than a third of women in Sierra Leone had encountered at least one HIV risk factor, and this was associated with age, place of residence, region, marital status, working status, household head and parity. There is a need for strengthening HIV/AIDS education programs, laws and policies targeting the young, working, unmarried and urban-resident women.
... Sexual violence against female refugees is a feature of conflict wherever it occurs in the world (UN Women, 2016), including high levels of sexual violations in countries such as DRC (Johnson et al., 2010;Peterman et al., 2011) and in west Africa (Amowitz et al., 2002;Watts et al., 2010) from where more than half of the women in our study originated. Perpetrators include armed forces, police, or militarized non-state groups (UN General Assembly, 2007), as reported by 3 women in our study. ...
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... Sexual violence against female refugees is a feature of conflict wherever it occurs in the world (UN Women, 2016), including high levels of sexual violations in countries such as DRC (Johnson et al., 2010;Peterman et al., 2011) and in west Africa (Amowitz et al., 2002;Watts et al., 2010) from where more than half of the women in our study originated. Perpetrators include armed forces, police, or militarized non-state groups (UN General Assembly, 2007), as reported by 3 women in our study. ...
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... Different kinds of evidence suggests that local history, politics and culture are important components to be considered in the design of interventions intended to reduce the frequency of risk behaviours [14][15][16][17]. Generalised interventions which do not take account of such factors are less likely to succeed. ...
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... 17 The disproportionate burden of HIV among women in sub-Saharan Africa is attributed to lack of power, coerced first sex, early marriage, limited access to reproductive health services, extreme poverty, and sexual violence. 9,18 Conflict and post-conflict contexts exacerbate these risks, 6,11,19 and war-related sexual violence in Northern Uganda has been well documented. 9,20,21 Heightened vulnerability of women and children surviving IDP settings stems primarily from elevated risk of rape and sexual violence, including by armed forces. ...
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... This would not explain why past IPV is associated with future HIV infection in women (Jewkes et al., 2010; Kouyoumdjian et al., 2013), although it would probably increase the cross-sectional IPV-HIV association. Secondly, some reviewers (Campbell et al., 2008) and modellers(Watts et al., 2010) have speculated that, due to physical trauma, there is a higher probability of HIV transmission when sex is forced, relative to consensual sex. Had this scenario been tested, one would expect the outcomes to resemble Scenario D (lower condom use). ...
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