Women who inject drugs are among the most vulnerable to HIV through both unsafe injections and unprotected sex. They are also among the most hidden affected populations, as they are more stigmatized than their male counterparts. Many sell sex to finance their own and their partner’s drug habit and often their partner exerts a significant amount of control over their sex work, condom use and injection practices. Women who use drugs all over the world face many different barriers to HIV service access including police harassment, judgmental health personnel and a fear of losing their children. In order to enable these women to access life-saving services including needle-syringe and condom programs, opioid substitution therapy and HIV testing and treatment, it is essential to create a conducive environment and provide tailor-made services that are adapted to their specific needs. In this commentary, we explore the risks and vulnerabilities of women who use drugs as well as the interventions that have been shown to reduce their susceptibility to HIV infection.

Identification of recent HIV infection within populations is a public health priority for accurate estimation of HIV incidence rates and transmitted drug resistance. Determining HIV incidence rates by prospective follow-up of HIV-uninfected individuals is challenging and serological assays have important limitations. HIV diversity within an infected host increases with duration of infection. In this analysis, we explore a simple bioinformatics approach to assess viral diversity by determining the percentage of ambiguous base calls in sequences derived from standard genotyping of HIV-1 protease and reverse transcriptase. Sequences from 691 recently infected (≤1 year) and chronically infected (>1 year) individuals from Sweden, Vietnam and Ethiopia were analyzed for ambiguity. A significant difference (p <0.0001) in the proportion of ambiguous bases was observed between sequences from individuals with recent and chronic infection in both HIV-1 subtype B and non-B infection, consistent with previous studies. In our analysis, a cutoff of <0.47% ambiguous base calls identified recent infection with a sensitivity and specificity of 88.8% and 74.6% respectively. 1,728 protease and reverse transcriptase sequences from 36 surveys of transmitted HIV drug resistance performed following World Health Organization guidance were analyzed for ambiguity. The 0.47% ambiguity cutoff was applied and survey sequences were classified as likely derived from recently or chronically infected individuals. 71% of patients were classified as likely to have been infected within one year of genotyping but results varied considerably amongst surveys. This bioinformatics approach may provide supporting population-level information to identify recent infection but its application is limited by infection with more than one viral variant, decreasing viral diversity in advanced disease and technical aspects of population based sequencing. Standardization of sequencing techniques and base calling and the addition of other parameters such as CD4 cell count may address some of the technical limitations and increase the usefulness of the approach.

Background India has the third largest HIV-1 epidemic with 2.4 million infected individuals. Molecular epidemiological analysis has identified the predominance of HIV-1 subtype C (HIV-1C). However, the previous reports have been limited by sample size, and uneven geographical distribution. The introduction of HIV-1C in India remains uncertain due to this lack of structured studies. To fill the gap, we characterised the distribution pattern of HIV-1 subtypes in India based on data collection from nationwide clinical cohorts between 2007 and 2011. We also reconstructed the time to the most recent common ancestor (tMRCA) of the predominant HIV-1C strains. Methodology/Principal Findings Blood samples were collected from 168 HIV-1 seropositive subjects from 7 different states. HIV-1 subtypes were determined using two or three genes, gag, pol, and env using several methods. Bayesian coalescent-based approach was used to reconstruct the time of introduction and population growth patterns of the Indian HIV-1C. For the first time, a high prevalence (10%) of unique recombinant forms (BC and A1C) was observed when two or three genes were used instead of one gene (p<0.01; p = 0.02, respectively). The tMRCA of Indian HIV-1C was estimated using the three viral genes, ranged from 1967 ( gag ) to 1974 ( env ). Pol- gene analysis was considered to provide the most reliable estimate [1971, (95% CI: 1965–1976)]. The population growth pattern revealed an initial slow growth phase in the mid-1970s, an exponential phase through the 1980s, and a stationary phase since the early 1990s. Conclusions/Significance The Indian HIV-1C epidemic originated around 40 years ago from a single or few genetically related African lineages, and since then largely evolved independently. The effective population size in the country has been broadly stable since the 1990s. The evolving viral epidemic, as indicated by the increase of recombinant strains, warrants a need for continued molecular surveillance to guide efficient disease intervention strategies.

Background: Toxoplasma gondii is a zoonotic parasite of global importance. In common with many protozoan parasites it has the capacity for sexual recombination, but current evidence suggests this is rarely employed. The global population structure is dominated by a small number of clonal genotypes, which exhibit biallelic variation and limited intralineage divergence. Little is known of the genotypes present in Africa despite the importance of AIDS-associated toxoplasmosis.