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Objectives To identify factors associated with detectable viral load and the emergence of drug resistance in a cohort of HIV-infected pregnant women in Malawi receiving antiretroviral combination regimens for the prevention of mother-to-infant transmission. Methods The study included 260 treatment-naive women who had received a three-drug nevirapine-based regimen from week 25 of gestational age until 6 months after delivery. HIV RNA was determined at month 6 and drug resistance was assessed if viral load was >50 copies/mL. Attendance at the scheduled follow-up visits was used as an indirect measure of treatment adherence. Results The rate of detectable HIV RNA at 6 months was 9.6% (25/260). The only significant predictor of this occurrence was the presence of ≥1 missed visit during follow-up (P = 0.012). Resistance was assessed in 19 of these women: 7 (37%) had a wild-type virus and the other 12 (63%) had resistance-associated mutations (nucleoside reverse transcriptase inhibitor, 7/12; non-nucleoside reverse transcriptase inhibitor, 11/12). Three of 12 cases (25%) in which mutations were detected had a viral load <1000 copies/mL. The emergence of resistance was not correlated with the presence of baseline mutations in either plasma or archived DNA. Conclusions In this cohort of women, detectable HIV RNA 6 months post-partum was infrequent and associated with low adherence to the treatment programme. Mutations were present in 63% of the women with detectable viral load at 6 months who had samples available for resistance testing. The impact of resistance on treatment re-initiation in women discontinuing drugs after the risk of transmission has ceased can be limited. [ABSTRACT FROM PUBLISHER]

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]