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Sexual violence and conflict in Africa: Prevalence and potential impact on HIV incidence

October 2010
Sexually Transmitted Infections 86 Suppl 3(Suppl 3):iii93-99

DOI:10.1136/sti.2010.044610

Source
PubMed

Authors:

Charlotte Watts

London School of Hygiene and Tropical Medicine

Anna M Foss

London School of Hygiene and Tropical Medicine

Mazeda Hossain

Nottingham Trent University

Cathy Zimmerman

London School of Hygiene and Tropical Medicine

Show all 6 authorsHide

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,

Anna M Foss,

Mazeda Hossain,

Cathy Zimmerman,

Rachel von Simson,

Jennifer Klot

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.

Although media reports

often focus on mass rape,

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 conﬂict.

Until recently, there was signiﬁcant concern that

HIV would thrive during conﬂict 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.

Epidemi-

ological research on HIV from several non-conﬂict

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 identiﬁcation of links between SV

and HIV, a review by Spiegel et al (2004) concluded

that there was limited evidence that conﬂict

increases HIV risk, or that rape was associated with

increases in HIV at a population level.

Later,

Spiegel et al (2007) argued that their data showed

that conﬂict in general had no epidemiologically

measurable impact and was not associated with

population HIV prevalence.

Subsequently, Anema

et al (2008) used mathematical modelling in

different conﬂict-affected sub-Saharan Africa

settings to show that widespread rape only raises

the overall level of HIV prevalence in a country by

0.023%.

This evidence on conﬂict, 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 ﬁnd 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 conﬂict settings, which may

lead to reductions or increases in HIV infection. For

example, although conﬂict often fosters SV, which

<An additional appendix is

published online only. To view

this ﬁle please visit the journal

online (http://sti.bmj.com).

Department of Global Health

and Development, London

School of Hygiene and Tropical

Medicine (LSHTM), London, UK

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, conﬂict-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 conﬂict-

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 conﬂict.

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 conﬂict

situation versus a ‘comparable’non-conﬂict scenario (online

supplementary appendix). A number of plausible scenarios were

developed to reﬂect situations that might arise in high- and low-

conﬂict situations. Scenarios included gang rape, anal rape and

transactional sex. Owing to lack of evidence about condom use

in conﬂict 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,

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%.

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.

Genital injury disrupts the multilayered stratiﬁed

epithelium that lines a woman’s 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.

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

difﬁcult, 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-conﬂict

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;

5% of those HIV-infected having high HIV

viral load

33e36

; and high viral load increases probability of HIV

transmission 10-fold.

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 ﬁndings to these different assumptions.

RESULTS

Published evidence on the prevalence of SV in conﬂict is

presented in table 1. Among settings with recently ended

conﬂicts, lifetime levels of ‘sexual violence’and ‘rape or sexual

abuse’experienced by women ranged from 42.3% in Liberia to

14%

in Cote d’Ivoire.

SV reported during conﬂict ranged

from 35.3% in Liberia

to 0.2% in Cote d’Ivoire.

While in

a setting with a prolonged conﬂict, service records from

Democratic Republic of Congo report over 20 000 SV cases

between 2003 and 2008.

Owing to methodological and

contextual differences it is difﬁcult to compare these ﬁgures

across settings as each study used different study populations;

deﬁnitions 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 individual’s risk of HIV may be inﬂuenced by SV,

coercion and transactional sex. In practice, however, the absolute

levels of risk are likely to be highly context speciﬁc. For this

reason we focus here on estimating the risk ratios, comparing

conﬂict-related scenarios with ‘comparable’non-conﬂict

scenarios. We consider risk ratios because these are less context

speciﬁc. 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 ﬁndings apply for any given underlying prevalence

of HIV.

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The scenarios presented suggest that there may be large

increases in individual HIV risk associated with SV in conﬂict-

affected settings. The ﬁndings 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 conﬂict ﬁeld is whether

SV could lead to increases in HIV at a population-level.

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

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

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

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

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

Democratic

Republic

of Congo

(DRC)

e20517 ee Rape, penetrative

sexual assault

Conﬂict Women and girls attending

medico-social support

programme

Service records Steiner 2009

e218 ee Sexual violence Conﬂict Cases reported and veriﬁed

by UN Mission in DRC

Incident records Taback 2008

Liberia 42.3 182 32.6 367 Sexual violence Lifetime Adult former combatants

aged 18*

Cross-sectional/systematic

random and cluster sampling

Johnson 2008

35.3 180 16.5 360 Sexual servant/slave Conﬂict Adult former combatants

aged 18*

Cross-sectional/systematic

random and cluster sampling

Johnson 2008

9.2 698 7.4 419 Sexual violence Lifetime Adult non-combatants

aged 18*

Cross-sectional/systematic

random and cluster sampling

Johnson 2008

17.6 4897 ee Sexual violence Lifetime Women aged 15e49,

national

Population-based household

survey/stratiﬁed random sampling

DHS 2007

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

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

Uganda,

Northern

27.7 118 3.9 108 Sexual violence Lifetime IDPs aged 15e49 Population-based household survey/

stratiﬁed random sampling

DHS 2007

*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.

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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

signiﬁcant 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 conﬂict settings. SV is seldom included in

epidemiological projections of HIV transmission.

Our review suggests that high levels of SV have occurred in

several African conﬂict settings. Although the modelling

presented here is limited by the data available and the challenge

of developing comparable conﬂict versus non-conﬂict 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 ﬁndings 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

ﬁndings from dynamic modelling are often still driven by the

factors contained in the static risk equation.

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 conﬂict-affected settings, where there are

competing inﬂuences 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.

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.

Conﬂict-related initiatives offer important opportunities to

assist survivors and prevent future abuses through collaborative

programming that links reconstruction, HIV, sexual violence and

women’s 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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Sep 2024
AIDS BEHAV

Humanitarian crises—natural or human-made events that can threaten communities’ health, safety, security, and well-being—may affect the HIV epidemic dynamics. Common aspects of humanitarian crises such as poverty, powerlessness, disruptions to the health systems, and social instability can contribute to a person’s vulnerability to HIV infection through increased risk behaviors and limited access to health services. Guided by the Joanna Briggs Institute methodology for scoping reviews and the Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews (PRISMA-ScR) reporting guidelines, we conducted a scoping review of literature published in English between January 1990 and March 2022 to characterize the global evidence of modifiable and non-modifiable factors for HIV acquisition in the context of humanitarian crises. We systematically searched, screened, and synthesized literature from MEDLINE, Embase, Global Health (all accessed via Ovid), and Scopus, and also grey literature through websites of humanitarian agencies and relevant non-government organizations, the International AIDS Society’s abstract databases, and Google Scholar. We considered studies presenting empirical data on HIV prevalence, incidence, or risk factors in humanitarian crises-affected populations, including refugees, asylum seekers, and internally displaced persons. Forty-nine studies met the inclusion criteria. The majority of studies were quantitative (n = 43, 87.8%) and cross-sectional (n = 37, 75.5%) in design. Most were single-country studies (n = 43, 87.8%) and conducted in Sub-Saharan Africa (n = 31, 63.3%). We identified 5 non-modifiable factors for HIV acquisition (i.e., age, gender, location, place of birth or origin, and ethnicity) and 60 modifiable factors that we further classified into five categories, namely 18 policy and structural, 9 sociocultural, 11 health and mental health, 16 sexual practice, and 6 humanitarian crisis-related traumatic event factors. Within the modifiable categories, factors that were most often investigated were education level, marital status, sexually transmitted infection diagnosis, condom use, and experience of rape or sexual trauma, respectively. Informed by the findings, we applied the social-ecological model to map the identified multidimensional factors associated with HIV acquisition at the levels of individual, social and sexual networks, community, public policy, and the context of humanitarian crises. The current review provides a comprehensive, global analysis of the available evidence on HIV prevalence, incidence, and risk factors in humanitarian crises and implications for potential programs and research. Future research is warranted to further understand the directionality of the non-modifiable and modifiable factors affecting HIV acquisition, and the multilevel barriers and facilitators to the uptake of HIV prevention strategies in the context of humanitarian crises. Such research can generate actionable evidence to inform the development of ethical, trauma-informed, and culturally appropriate HIV prevention interventions in humanitarian settings.

Increase in HIV incidence in women exposed to rape: a comparative cohort study

Article

Full-text available

Dec 2020

Objective: To determine the incidence of HIV acquisition in women post-rape compared with t a cohort of women who had not been raped. Design: A prospective cohort study. Methods: The Rape Impact Cohort Evaluation (RICE) study based in Durban, South Africa, enrolled women aged 16-40 years from post-rape care services, and a control group of women from Primary Health Care services. Women who were HIV negative at baseline (441 in the rape-exposed group and 578 in the control group) were followed for 12 to 36 months with assessments every three months in the first year and every six months thereafter. Multivariable Cox regression models adjusted for baseline and time varying covariates were used to investigate the effect of rape exposure on HIV incidence over follow-up. Results: Eighty-six women acquired HIV during 1605.5 total person-years of follow-up, with an incident rate of 6.6 per 100 person-years (95% confidence interval (CI): 4.8 - 9.1) among the rape exposed group and 4.7 per 100 person-years (95% CI: 3.5 - 6.2) among control group. After controlling for confounders (age, previous trauma, social support, perceived stress, multiple partners and transactional sex with a casual partner), women exposed to rape had a 60% increased risk of acquiring HIV (adjusted hazard ratio: 1.59 (95% CI: 1.01 - 2.48) compared to those not exposed. Survival analysis showed difference in HIV incident occurred after month nine. Conclusion: Rape is a long-term risk factor for HIV acquisition. Rape survivors need both immediate and long-term HIV prevention and care.

Risk Factors and Clinical Presentation of Acute Primary HIV Infection in India

Article

Full-text available

Jan 1997

Context. —Most previous studies of clinical presentation and risk factors in early human immunodeficiency virus (HIV) infection have relied on retrospective analyses and referred seroconverters, and thus were subject to possible bias.

Intimate Partner Violence, Relationship Power Inequity, and Incidence of HIV Infection in Young Women in South Africa: A Cohort Study

Article

Full-text available

Jul 2010
LANCET

Cross-sectional studies have shown that intimate partner violence and gender inequity in relationships are associated with increased prevalence of HIV in women. Yet temporal sequence and causality have been questioned, and few HIV prevention programmes address these issues. We assessed whether intimate partner violence and relationship power inequity increase risk of incident HIV infection in South African women. We did a longitudinal analysis of data from a previously published cluster-randomised controlled trial undertaken in the Eastern Cape province of South Africa in 2002-06. 1099 women aged 15-26 years who were HIV negative at baseline and had at least one additional HIV test over 2 years of follow-up were included in the analysis. Gender power equity and intimate partner violence were measured by a sexual relationship power scale and the WHO violence against women instrument, respectively. Incidence rate ratios (IRRs) of HIV acquisition at 2 years were derived from Poisson models, adjusted for study design and herpes simplex virus type 2 infection, and used to calculate population attributable fractions. 128 women acquired HIV during 2076 person-years of follow-up (incidence 6.2 per 100 person-years). 51 of 325 women with low relationship power equity at baseline acquired HIV (8.5 per 100 person-years) compared with 73 of 704 women with medium or high relationship power equity (5.5 per 100 person-years); adjusted multivariable Poisson model IRR 1.51, 95% CI 1.05-2.17, p=0.027. 45 of 253 women who reported more than one episode of intimate partner violence at baseline acquired HIV (9.6 per 100 person-years) compared with 83 of 846 who reported one or no episodes (5.2 per 100 person-years); adjusted multivariable Poisson model IRR 1.51, 1.04-2.21, p=0.032. The population attributable fractions were 13.9% (95% CI 2.0-22.2) for relationship power equity and 11.9% (1.4-19.3) for intimate partner violence. Relationship power inequity and intimate partner violence increase risk of incident HIV infection in young South African women. Policy, interventions, and programmes for HIV prevention must address both of these risk factors and allocate appropriate resources. National Institute of Mental Health and South African Medical Research Council.

HIV Risk Behaviours and their Relationship to Intimate Partner Violence (IPV) Among Men Who Have Multiple Female Sexual Partners in Cape Town, South Africa

Article

Full-text available

Mar 2010
AIDS BEHAV

HIV/AIDS and intimate partner violence (IPV) are growing public health concerns in South Africa. Knowledge about adult men's perpetration of IPV and links between HIV risk behaviours and IPV is limited. Respondent driven sampling was used to recruit men who have multiple concurrent female sexual partners. Forty-one percent of the 428 recruited men had perpetrated IPV. Inconsistent condom use was associated with physical IPV; experiencing a symptom of a sexually transmitted infection and engaging in transactional sex were associated with physical and sexual IPV; problem alcohol use was associated with physical, and any IPV, but not sexual IPV; having five or more partners was associated with sexual IPV; perceptions of partners' infidelity were associated with physical and any IPV. HIV risk reduction interventions among men, especially those with multiple female sex partners, should incorporate strategies to change the underlying construction of masculinity that combines the anti-social and risky behaviours of IPV perpetration, inconsistent condom use, transactional sex and heavy alcohol consumption.

HIV Incidence in Sub-Saharan Africa: A Review of Available Data with Implications for Surveillance and Prevention Planning

Article

Full-text available

Jul 2009

HIV incidence estimation is increasingly being incorporated into HIV/AIDS surveillance activities in both resource-rich and developing countries. We conducted a systematic review to assess the availability of HIV incidence data from sub-Saharan Africa. We examined peer-reviewed articles, conference proceedings and technical reports published from 1987-2008. Incidence estimates were classified by country, year, population group, and estimation method (prospective study or the serologic testing algorithm for recent HIV seroconversion; STARHS). Our search yielded HIV incidence estimates for 15 of 44 sub-Saharan African countries, with 57 studies generating 264 unique estimates. Of these, 239 (91%) were obtained via prospective studies, and 25 (9%) via the STARHS method (24 using the BED-CEIA assay). Only five countries reported population-based estimates, and less than two-thirds of studies reported risk factor information. STARHS use increased over time, comprising 20% of estimates since 2006. However, studies that compared STARHS estimates with prospectively observed or modeled estimates often found substantial levels of disagreement, with STARHS often overestimating HIV incidence. Population-based HIV incidence estimates and risk factor information in sub-Saharan Africa remain scant but increasingly available. Regional STARHS data suggest a need for further validation prior to widespread use and incorporation into routine surveillance activities. In the meantime, prevalence and behavioral risk factor data remain important for HIV prevention planning.

The Association Between Sexual Aggression and HIV Risk Behavior in Heterosexual Men

Article

Full-text available

Jun 2009

Perpetrating sexual coercion and rape can be conceptualized as a form of sexual risk taking. In this study, the authors evaluated the relationship between sexual aggression and other risky sexual behaviors (e.g., intercourse without a condom) using an online convenience sample of 1,240 heterosexual men. Sexually aggressive men engaged in more sexual risk taking (i.e., sex with multiple partners, unprotected sex, and one-night stands) than nonaggressive men, and almost half of the reported incidents of sexual aggression were unprotected (i.e., no condom was worn). Thus, sexual aggression was found to be part of a larger pattern of sexual risk taking. Regression analyses revealed that sexual aggression was associated with greater alcohol use and lower sexual inhibition-two variables that have consistently been found to be related to other forms of sexual risk taking.

Heterosexual risk of HIV-1 infection per sexual act: systematic review and meta-analysis of observational studies

Article

Feb 2009
LANCET INFECT DIS

We did a systematic review and meta-analysis of observational studies of the risk of HIV-1 transmission per heterosexual contact. 43 publications comprising 25 different study populations were identified. Pooled female-to-male (0.04% per act [95% CI 0.01-0.14]) and male-to-female (0.08% per act [95% CI 0.06-0.11]) transmission estimates in high-income countries indicated a low risk of infection in the absence of antiretrovirals. Low-income country female-to-male (0.38% per act [95% CI 0.13-1.10]) and male-to-female (0.30% per act [95% CI 0.14-0.63]) estimates in the absence of commercial sex exposure (CSE) were higher. In meta-regression analysis, the infectivity across estimates in the absence of CSE was significantly associated with sex, setting, the interaction between setting and sex, and antenatal HIV prevalence. The pooled receptive anal intercourse estimate was much higher (1.7% per act [95% CI 0.3-8.9]). Estimates for the early and late phases of HIV infection were 9.2 (95% CI 4.5-18.8) and 7.3 (95% CI 4.5-11.9) times larger, respectively, than for the asymptomatic phase. After adjusting for CSE, presence or history of genital ulcers in either couple member increased per-act infectivity 5.3 (95% CI 1.4-19.5) times versus no sexually transmitted infection. Study estimates among non-circumcised men were at least twice those among circumcised men. Low-income country estimates were more heterogeneous than high-income country estimates, which indicates poorer study quality, greater heterogeneity of risk factors, or under-reporting of high-risk behaviour. Efforts are needed to better understand these differences and to quantify infectivity in low-income countries.

A population-based study on alcohol and high-risk sexual behaviors in Botswana

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