Is it worth publishing data and recommendations that could be misconstrued and may not make much of a programmatic difference in the field? Yes.
Data, if collected and analysed correctly and interpreted carefully, help to improve our understanding of complicated and nuanced situations. Even if programmes in the field do not significantly change, our understanding of what the outcomes of such interventions can achieve will be more realistic. It also helps decision-makers prioritise their funding and interventions.
Sub-Saharan Africa (SSA) is overwhelmingly affected by HIV/AIDS [1
]. It is also the region with the highest number of armed conflicts worldwide. In 2005, armed conflicts were active in 15 of SSA's 47 countries [2
], and resulted in the displacement of approximately 12.5 million people [3
]. Armed conflicts have traditionally been considered catalysts for HIV transmission due to associated sexual violence against women, lack of access to preventive and curative heath services, and increased vulnerability and risks incurred by population displacement and food insecurity [4
]. The use of sexual violence as a weapon of war has been particularly associated with concerns about heightened HIV incidence among women and girls [6
]. Widespread rape by armed combatants has been documented in Burundi [8
], Sierra Leone [9
], Rwanda [10
], the Democratic Republic of Congo (DRC) [11
], Liberia [12
], Sudan [13
] and Uganda [14
]. For the last decade, international organisations have perceived rape as a major cause of HIV transmission in conflict settings, and prioritised public health interventions to mitigate its effects [15
However, empirical research suggests that HIV incidence in armed conflicts may in fact diminish, remain constant or not increase to the same magnitude compared with those countries not in conflict. This may be due to reductions in population mobility, access, and urbanisation [19
]. A recent systematic review of the seven conflict affected countries found that existing data do not support a link between widespread rape and increased HIV prevalence at the population level [21
]. This finding has been met with some criticism from non-governmental organisations and advocacy groups [22
], partially because of the perceived HIV-risk associated with rape in these contexts.
This paper builds on Spiegel et al.'s systematic review of HIV in conflict affected countries. To further examine the assertion that widespread rape may not increase HIV prevalence at the population level, we analyse the impact of varying scenarios of widespread rape on HIV prevalence in 7 SSA countries that have undergone conflict.
We built a model to determine the potential impact of varying scenarios of widespread rape on HIV prevalence at the population level in the seven African countries listed above (Table ). Specifically, we investigated how the total population HIV prevalence would be affected if 1%, 5%, 10% and 15% of the female population aged 5–49 years were raped in each country. We looked at extreme scenarios, by assuming low, intermediate and high estimates of HIV prevalence and transmission rates among male assailants. We assumed that assailants of widespread rape were armed combatants. Given the absence of seroprevalence data for armed combatants in the countries under study, we assumed the HIV prevalence among assailants was commensurate to that of national militaries in SSA. To take into account potential higher prevalence in selected groups (e.g. HIV used as a weapon), we multiplied the baseline population prevalence by 2, 4 and 8. Primary outcomes of our analysis included absolute and relative increases in population level HIV prevalence, per different rape prevalence estimates, for each country, and for age groups 5–49 years. To be conservative in our estimates, we decided to use the 5–49 year age group compared with the 15–49 year group because rape in conflict has been reported among girls less than 15 years of age.
Estimated increase in prevalence in HIV due to different rates of sexual assault in women 5–49 yrs, by selected countries.
We obtained annual population estimates for the countries under study from United States Census Bureau's International Data Base [23
]. These population estimates are based on all residents of nations within SSA regardless of legal status or citizenship, and represent a compendium of data on population, fertility, mortality, contraceptive use, and related demographic topics provided by the US Census Bureau [24
]. High, low and mid-range estimates of national HIV prevalence estimates for women aged 5–49 years were obtained from UNAIDS/WHO's country-specific end-2006 Epidemiological Fact Sheets for HIV/AIDS and Sexually Transmitted Infections [25
We determined the number of women at risk of becoming newly infected with HIV from rape by subtracting the estimated number of HIV prevalent cases from the total adult female population. The lower population prevalence was used as a conservative estimate. To account for varying heterosexual transmission rates according to disease stage, multiple rapes, presence of sexually transmitted infections, and other confounding factors, we assumed low, intermediate and high rates of HIV transmission. On the low end, we assumed an HIV transmission rate of 0.0028, which is the acknowledged rate for HIV heterosexual HIV transmission among asymptomatic and symptomatic individuals (i.e. >500 to >200 CD4+ counts). On the upper end, we assumed a rate of 0.008, the rate of heterosexual transmission among individuals with acute and recent primary HIV infection [26
]. This upper rate was then multiplied two and four times to take into account potential factors associated with higher rates of transmission, such as genital and/or rectal trauma associated with rape by multiple assailants [27
]. The number of women at risk of HIV transmission is the product of the total population of women in this age-group by the probability of rape, taking into account those who are already HIV positive. The number of newly infected women is, therefore, the product of the number of women at risk by the probability of the assailant being positive and the probability of transmission. The absolute increase in prevalence is the number of newly infected women divided by the total population. The relative increase in the total population is therefore this rate divided by the country specific rate (Table ).