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Background Virtually all HIV-infected women in sub-Saharan Africa have evidence of Cytomegalovirus (CMV) infection and levels of specific anti-CMV IgG have been suggested to represent more intense reactivation of subclinical infection. Studies have also shown direct influence of CMV on lymphocytes. Objective The aim of this study was to determine if levels of anti-CMV specific antibodies could impact on the immunological response to antiretroviral treatment (ART) in HIV-infected pregnant women. Study design CMV-specific IgG were measured in HIV-infected pregnant women at 26 weeks of gestation (before ART initiation). Women received ART until 6 months postpartum or indefinitely according to local guidelines at the time of the study. Immunological and virological responses were assessed 6 months and 24 months after delivery. Results A total of 81 women were studied. At baseline high levels (above the median) of specific IgG were associated to a low CD4+ cell count (P< 0.001), a high viral load (P = 0.003), and to an older age (P = 0.051). In a multivariate model adjusting for baseline CD4+ count, baseline viral load and age, the presence of low levels of CMV IgG was the only independent predictor of a a CD4+ count above 500/mm 3 24 months after delivery among women on continuous therapy. Conclusions In this cohort, levels of CVM IgG had a significant influence on the immunological response to ART, adding information to the known impact of CMV infection in the HIV-positive population, and underlining the need of new strategies to contain the infection. [ABSTRACT FROM AUTHOR]

Universal human immunodeficiency virus (HIV) test-and-treat approaches have been evaluated in mathematical models. We developed a district-level model based on actual data from 26-patients in the Drug Resource Enhancement Against AIDS and Malnutrition Program in sub-Saharan Africa. Rapid decreases were observed in the incidence of HIV infection and population infectivity.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 26 565 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. [ABSTRACT FROM AUTHOR]