Sexual Risk Behaviors Associated with Sexually Transmitted Infections in a US Military Population Living with HIV After the Repeal of "Don't Ask, Don't Tell"

Risk behaviors associated with sexually transmitted infections (STIs) among people living with HIV (PLWH) have not been well characterized in the US military. We identified risk behaviors associated with a new STI in this population after the repeal of "Don't Ask, Don't Tell." US Military HIV Natural History Study participants who completed the risk behavior questionnaire (RBQ) between 2014 and 2017 and had at least 1 year of follow-up were included (n = 1589). Logistic regression identified behaviors associated with incident STI in the year following RBQ completion. Overall, 18.9% acquired an STI and 52.7% reported condom use at last sexual encounter. Compared with those with no new sex partners, participants with between one and four or five or more new partners were 1.71 [1.25-2.35] and 6.12 [3.47-10.79] times more likely to get an STI, respectively. Individuals reporting low or medium/high perceived risk of STI were 1.83 [1.23-2.72] and 2.65 [1.70-4.15] times more likely to acquire a new STI than those reporting no perceived risk, respectively. Participants who preferred not to answer about sexual preference, number of new partners, or perceived STI risk were also more likely to acquire a new STI. Our study illustrates that despite regular access to health care and accurate perceptions of risk, rates of STI among PLWH remain high in the US military setting, as in others. Given the potential individual and public health consequences of STI coinfection after HIV, more work is needed to assess interventions aimed at sexual behavior change for PLWH.

High genomic diversity of multi-drug resistant wastewater Escherichia coli

Wastewater treatment plants play an important role in the emergence of antibiotic resistance. They provide a hot spot for exchange of resistance within and between species. Here, we analyse and quantify the genomic diversity of the indicator Escherichia coli in a German wastewater treatment plant and we relate it to isolates’ antibiotic resistance. Our results show a surprisingly large pan-genome, which mirrors how rich an environment a treatment plant is. We link the genomic analysis to a phenotypic resistance screen and pinpoint genomic hot spots, which correlate with a resistance phenotype. Besides well-known resistance genes, this forward genomics approach generates many novel genes, which correlated with resistance and which are partly completely unknown. A surprising overall finding of our analyses is that we do not see any difference in resistance and pan genome size between isolates taken from the inflow of the treatment plant and from the outflow. This means that while treatment plants reduce the amount of bacteria released into the environment, they do not reduce the potential for antibiotic resistance of these bacteria.