HIV-1 subtype diversity and transmission strain source among men who have sex with men in Guangxi, China

With the rapid increase in HIV prevalence of men who have sex with men (MSM) in recent years and common human migration and travelling across different provinces in China, MSM are now finding it easier to meet each other, which might contribute to local HIV epidemics as well as fueling cross-province transmission. We performed a cross-sectional survey in 2018–2019 to investigate the current HIV subtype diversity and inferred HIV strain transmission origin among MSM in Guangxi province, China based on a phylogenetic analysis. Based on 238 samples, we found that the HIV-1 subtype diversity was more complicated than before, except for three major HIV subtypes/circulating recombinant forms (CRFs): CRF07_BC, CRF01_AE, CRF55_01B, five other subtypes/CRFs (CRF59_01B, B, CRF08_BC, CRF67_01B, CRF68_01B) and five unique recombinant forms (URFs) were detected. In total, 76.8% (169/220) of samples were infected with HIV from local circulating strains, while others originated from other provinces, predominantly Guangdong and Shanghai. The high diversity of HIV recombinants and complicated HIV transmission sources in Guangxi MSM indicates that there has been an active sexual network between HIV positive MSM both within and outside Guangxi without any effective prevention. Inter-province collaboration must be enforced to provide tailored HIV prevention and control services to MSM in China.

Generating a heterosexual bipartite network embedded in social network

We describe an approach to generate a heterosexual network with a prescribed joint-degree distribution embedded in a prescribed large-scale social contact network. The structure of a sexual network plays an important role in how all sexually transmitted infections (STIs) spread. Generating an ensemble of networks that mimics the real-world is crucial to evaluating robust mitigation strategies for controlling STIs. Most of the current algorithms to generate sexual networks only use sexual activity data, such as the number of partners per month, to generate the sexual network. Real-world sexual networks also depend on biased mixing based on age, location, and social and work activities. We describe an approach to use a broad range of social activity data to generate possible heterosexual networks. We start with a large-scale simulation of thousands of people in a city as they go through their daily activities, including work, school, shopping, and activities at home. We extract a social network from these activities where the nodes are the people, and the edges indicate a social interaction, such as working in the same location. This social network captures the correlations between people of different ages, living in different locations, their economic status, and other demographic factors. We use the social contact network to define a bipartite heterosexual network that is embedded within an extended social network. The resulting sexual network captures the biased mixing inherent in the social network, and models based on this pairing of networks can be used to investigate novel intervention strategies based on the social contacts among infected people. We illustrate the approach in a model for the spread of chlamydia in the heterosexual network representing the young sexually active community in New Orleans.

Association Between HIV PrEP Indications and Use in a National Sexual Network Study of Men Who Have Sex with Men

BACKGROUND: HIV preexposure prophylaxis (PrEP) is effective in preventing HIV transmission. US Public Health Service (USPHS) clinical practice guidelines define biobehavioral indications for initiation. To assess guideline implementation, it is critical to quantify PrEP non-users who are indicated and PrEP users who are not indicated. METHODS: Using data from a national web-based study of men who have sex with men (MSM) between 2017 and 2019, we estimated the association between PrEP use and PrEP indications. Log-binomial regression was used to estimate the relationship between PrEP indications and PrEP use, adjusted for geography and demographics. RESULTS: Of 3508 sexually active, HIV-negative MSM, 34% met indications for PrEP. The proportion with current PrEP use was 32% among those meeting indications and 11% among those without indications. Nearly 40% of those currently using PrEP did not meet indications for PrEP, and 68% of MSM with indications for PrEP were not currently using PrEP. After adjusting for geography and demographics, MSM with PrEP indications were about 3 times as likely to be currently using PrEP. This association varied slightly by geography and demography. CONCLUSIONS: Indications for PrEP strongly predicted current PrEP use among MSM. However, we identified substantial misalignment between indications and use in both directions (indicated MSM who were not benefitting from PrEP, and MSM taking PrEP while not presently being indicated). This calls for further implementation efforts to improve PrEP delivery to those most in need during periods of elevated sexual risk.

Disseminated Effects in Agent Based Models: A Potential Outcomes Framework and Application to Inform Pre-Exposure Prophylaxis Coverage Levels for HIV Prevention

Pre-exposure prophylaxis (PrEP) for HIV prevention may not only benefit the individual who uses it, but also their uninfected sexual risk contacts. We developed an agent-based model using a novel trial emulation approach to quantify disseminated effects of PrEP use among men who have sex with men in Atlanta, USA from 2015 to 2017. Components (subsets of agents connected through partnerships in a sexual network, but not sharing partnerships with any other agents) were first randomized to an intervention coverage level or control, then within intervention components, eligible agents were randomized to PrEP. We estimated direct and disseminated (indirect) effects using randomization-based estimators and reported corresponding 95% simulation intervals across scenarios ranging from 10% to 90% coverage in the intervention components. A population of 11,245 agents was simulated with an average of 1,551 components identified. Comparing agents randomized to PrEP in 70% coverage components to control agents, there was a 15% disseminated risk reduction in HIV incidence (95% simulation intervals = 0.65, 1.05). Individuals not on PrEP may receive a protective benefit by being in a sexual network with higher PrEP coverage. Agent-based models are useful to evaluate possible direct and disseminated effects of HIV prevention modalities in sexual networks.

Variations in sexual network connectivity may explain dramatic variations in sexually transmitted infection prevalence between populations and over time: a four-country analysis

Background: The incidence of sexually transmitted infections (STIs) has been noted to vary dramatically between population groups and over time. Here, the hypothesis that changes in network connectivity underpin these changes is explored. Methods: The incidence/prevalence estimates of HIV, herpes simplex virus-2, syphilis, chlamydia, and gonorrhoea, as well as two markers of sexual network connectivity (partner concurrency and multiple partnering) by ethnic group and sexual orientation in Kenya, South Africa, the United Kingdom (UK) and the United States (USA) were extracted from published studies. Pearson’s correlation was used to test the association between the markers of network connectivity and the incidence/prevalence of these five STIs. A literature review was performed to evaluate the possible causes of the increases and decreases in syphilis incidence over the past 60 years. Results: In each country, the five STIs were found to cluster in particular ethnic groups and sexual orientations and to be positively associated with the two markers of network connectivity. Syphilis incidence in the UK and USA was found to increase dramatically in the 1960s/1970s, decline in the 1980s and again increase in the late 1990s. These changes took place predominantly in men who have sex with men, and were preceded by corresponding changes in network connectivity. The large decline in antenatal syphilis prevalence in Kenya and South Africa in the 1990s were likewise preceded by declines in network connectivity. Conclusions: Although other explanatory variables are not controlled for, the present analysis is compatible with the hypothesis that differential network connectivity is a parsimonious explanation for variations in STI incidence over time and between populations.