Widespread rape does not directly appear to increase the overall HIV prevalence in conflict-affected countries: so now what?

BACKGROUND: Sub-Saharan Africa (SSA) is severely affected by HIV/AIDS and conflict. Sexual violence as a weapon of war has been associated with concerns about heightened HIV incidence among women. Widespread rape by combatants has been documented in Burundi, Sierra Leone, Rwanda, Democratic Republic of Congo, Liberia, Sudan and Uganda. To examine the assertion that widespread rape may not directly increase HIV prevalence at the population level, we built a model to determine the potential impact of varying scenarios of widespread rape on HIV prevalence in the above seven African countries. DISCUSSION: Our findings show that even in the most extreme situations, where 15% of the female population was raped, where HIV prevalence among assailants was 8 times the country population prevalence, and where the HIV transmission rate was highest at 4 times the average high rate, widespread rape increased the absolute HIV prevalence of these countries by only 0.023%. These projections support the finding that widespread rape in conflict-affected countries in SSA has not incurred a major direct population-level change in HIV prevalence. However, this must not be interpreted to say that widespread rape does not pose serious problems to women's acquisition of HIV on an individual basis or in specific settings. Furthermore, direct and indirect consequences of sexual violence, such as physical and psychosocial trauma, unwanted pregnancies, and stigma and discrimination cannot be understated. SUMMARY: The conclusions of this article do not significantly change current practices in the field from an operational perspective. Proper care and treatment must be provided to every survivor of rape regardless of the epidemiological effects of HIV transmission at the population level. Sexual violence must be treated as a protection issue and not solely a reproductive health and psychosocial issue. It is worth publishing data and conclusions that could be misconstrued and may not make much of a programmatic difference in the field. Data, if collected, analysed and interpreted carefully, help to improve our understanding of complicated and nuanced situations. Ultimately, 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.