Background: The use of antiretrovirals to reduce the incidence of human immunodeficiency virus (HIV) infection has been evaluated in mathematical models as potential strategies for curtailing the epidemic. Cohort data from the Drug Resource Enhancement Against AIDS and Malnutrition (DREAM) Program was used to generate a realistic model for the HIV epidemic in sub-Saharan Africa.
Methods: Two combined stochastic models were developed: patient and epidemic models. Models were combined using virus load as a parameter of infectivity. DREAM data that assessed patient care in Mozambique and Malawi were used to generate measures of infectivity, survival, and adherence. The Markov chain prediction model was used for the analysis of disease progression in treated and untreated patients. A partnership model was used to assess the probability that an infected individual would transmit HIV.
Results: Data from 26565 patients followed up from January 2002 through July 2009 were analyzed with the model; 63% of patients were female, the median age was 35 years, and the median observation time was 25 months. In the model, a 5-fold reduction in infectivity (from 1.6% to 0.3%) occurred within 3 years when triple ART was used. The annual incidence of HIV infection declined from 7% to 2% in 2 years, and the prevalence was halved, from 12% to 6%, in 11 years. Mortality in HIV-infected individuals declined by 50% in 5 years. A cost analysis demonstrated economic efficiency after 4 years.
Conclusions: Our model, based on patient data, supports the hypothesis that treatment of all infected individuals translates into a drastic reduction in incident HIV infections. A targeted implementation strategy with massive population coverage is feasible in sub-Saharan Africa.