Faculty Bibliography

We investigated how different models of HIV transmission, and assumptions regarding the distribution of unprotected sex and syringe-sharing events ('risk acts'), affect quantitative understanding of HIV transmission process in people who inject drugs (PWID). The individual-based model simulated HIV transmission in a dynamic sexual and injecting network representing New York City. We constructed four HIV transmission models: model 1, constant probabilities; model 2, random number of sexual and parenteral acts; model 3, viral load individual assigned; and model 4, two groups of partnerships (low and high risk). Overall, models with less heterogeneity were more sensitive to changes in numbers risk acts, producing HIV incidence up to four times higher than that empirically observed. Although all models overestimated HIV incidence, micro-simulations with greater heterogeneity in the HIV transmission modelling process produced more robust results and better reproduced empirical epidemic dynamics.

Human immunodeficiency virus type 1 (HIV-1) was discovered in the early 1980s when the virus had already established a pandemic. For at least three decades the epidemic in the Western World has been dominated by subtype B infections, as part of a sub-epidemic that traveled from Africa through Haiti to United States. However, the pattern of the subsequent spread still remains poorly understood. Here we analyze a large dataset of globally representative HIV-1 subtype B strains to map their spread around the world over the last 50years and describe significant spread patterns. We show that subtype B travelled from North America to Western Europe in different occasions, while Central/Eastern Europe remained isolated for the most part of the early epidemic. Looking with more detail in European countries we see that the United Kingdom, France and Switzerland exchanged viral isolates with non-European countries than with European ones. The observed pattern is likely to mirror geopolitical landmarks in the post-World War II era, namely the rise and the fall of the Iron Curtain and the European colonialism. In conclusion, HIV-1 spread through specific migration routes which are consistent with geopolitical factors that affected human activities during the last 50years, such as migration, tourism and trade. Our findings support the argument that epidemic control policies should be global and incorporate political and socioeconomic factors.

OBJECTIVE:Although our understanding of viral transmission among people who inject drugs (PWID) has improved, we still know little about when and how many times each injector transmits HIV throughout the duration of infection. We describe HIV dynamics in PWID to evaluate which preventive strategies can be efficient. DESIGN:Due to the notably scarce interventions, HIV-1 spread explosively in Russia and Ukraine in 1990s. By studying this epidemic between 1995 and 2005, we characterized naturally occurring transmission dynamics of HIV among PWID. METHOD:We combined publicly available HIV pol and env sequences with prevalence estimates from Russia and Ukraine under an evolutionary epidemiology framework to characterize HIV transmissibility between PWID. We then constructed compartmental models to simulate HIV spread among PWID. RESULTS:In the absence of interventions, each injector transmits on average to 10 others. Half of the transmissions take place within 1 month after primary infection, suggesting that the epidemic will expand even after blocking all the post-first month transmissions. Primary prevention can realistically target the first month of infection, and we show that it is very efficient to control the spread of HIV-1 in PWID. Treating acutely infected on top of primary prevention is notably effective. CONCLUSION:As a large proportion of transmissions among PWID occur within 1 month after infection, reducing and delaying transmissions through scale-up of harm reduction programmes should always form the backbone of HIV control strategies in PWID. Growing PWID populations in the developing world, where primary prevention is scarce, constitutes a public health time bomb.

BACKGROUND:Young Black men who have sex with men (YBMSM) are at highest risk for HIV seroconversion in the United States. Successful movement through the HIV care continuum is an important intervention for limiting onwards HIV transmission. OBJECTIVE:Little data exists on how substances most commonly used by YBMSM, such as marijuana, are related to the HIV continuum, which represents the primary aim of this study. METHODS:A cohort of YBMSM (n = 618) was generated through respondent-driven sampling. Frequency of marijuana use and marijuana use as a sex-drug were assessed across the HIV care continuum using weighted logistic regression models. RESULTS:Study participants reported more intermittent marijuana use (n = 254, 56.2%) compared to heavy use (n = 198, 43.8%). Our sample contained 212 (34.3%) HIV seropositive participants of which 52 (24.5%) were unaware of their HIV positive status. Study participants who were heavy marijuana users were more likely to be unaware of their HIV seropositive status (AOR: 4.18; 95% CI 1.26, 13.89). All other stages in the care continuum demonstrated no significant differences between those who use marijuana intermittently or heavily or as a sex-drug and nonusers. CONCLUSIONS:YBMSM who used marijuana heavily were more likely to be HIV-positive unaware than those who never used marijuana. Findings were inconclusive regarding the relationships between marijuana use and other HIV care continuum metrics. However, knowledge of ones' HIV status is a critical requirement for engaging in care and may have implications for onwards HIV transmission.

Macro-social/structural events ("big events") such as wars, disasters, and large-scale changes in policies can affect HIV transmission by making risk behaviors more or less likely or by changing risk contexts. The purpose of this study was to develop new measures to investigate hypothesized pathways between macro-social changes and HIV transmission. We developed novel scales and indexes focused on topics including norms about sex and drug injecting under different conditions, involvement with social groups, helping others, and experiencing denial of dignity. We collected data from 300 people who inject drugs in New York City during 2012-2013. Most investigational measures showed evidence of validity (Pearson correlations with criterion variables range = 0.12-0.71) and reliability (Cronbach's alpha range = 0.62-0.91). Research is needed in different contexts to evaluate whether these measures can be used to better understand HIV outbreaks and help improve social/structural HIV prevention intervention programs.

Black men who have sex with men (BMSM) are highest risk for HIV seroconversion in the United States. Little attention has been paid to marijuana use among BMSM and potential for HIV risk. A sample of 202 BMSM was generated through respondent driven sampling. The relationship between differential marijuana use and both HIV risk behavior and social network factors were examined using weighted logistic regression. Of the BMSM in this sample 60.4 % use marijuana in general and 20.8 % use marijuana as sex-drug. General marijuana use was significantly associated with participation in group sex (AOR 3.50; 95 % CI 1.10-11.10) while marijuana use as a sex drug was significantly associated with both participation in condomless sex (AOR 2.86; 95% CI 1.07-7.67) and group sex (AOR 3.39; 95% CI 1.03-11.22). Respondents with a moderate or high perception of network members who use marijuana were more likely to use marijuana both in general and as a sex-drug. Network member marijuana use, while not associated with risk behaviors, is associated with individual marijuana use and individual marijuana use in the context of sex is associated with risk practices. Targeting interventions towards individuals and their respective networks that use marijuana as a sex drug may reduce HIV risk.

The number of public health applications for molecular epidemiology and social network analysis has increased rapidly since the improvement in computational capacities and the development of new sequencing techniques. Currently, molecular epidemiology methods are used in a variety of settings: from infectious disease surveillance systems to the description of disease transmission pathways. The latter are of great epidemiological importance as they let us describe how a virus spreads in a community, make predictions for the further epidemic developments, and plan preventive interventions. Social network methods are used to understand how infections spread through communities and what the risk factors for this are, as well as in improved contact tracing and message-dissemination interventions. Research is needed on how to combine molecular and social network data as both include essential, but not fully sufficient information on infection transmission pathways. The main differences between the two data sources are that, firstly, social network data include uninfected individuals unlike the molecular data sampled only from infected network members. Thus, social network data include more detailed picture of a network and can improve inferences made from molecular data. Secondly, network data refer to the current state and interactions within the social network, while molecular data refer to the time points when transmissions happened, which might have happened years before the sampling date. As of today, there have been attempts to combine and compare the data obtained from the two sources. Even though there is no consensus on whether and how social and genetic data complement each other, this research might significantly improve our understanding of how viruses spread through communities.