Faculty Bibliography

PURPOSE/OBJECTIVE:Estimates of HIV prevalence, and how it changes over time, are needed to inform action (e.g., resource allocation) to improve HIV-related public health. However, creating adequate estimates of (diagnosed and undiagnosed) HIV prevalence is challenging due to biases in samples receiving HIV testing and due to difficulties enumerating key risk populations. To our knowledge, estimates of HIV prevalence among high risk heterosexuals in the United States produced for geographic areas smaller than the entire nation have to date been only for single years and/or for single cities (or other single geographic locations). METHODS:The present study addresses these gaps by using multilevel modeling on multiple data series, in combination with previous estimates of HIV prevalence among heterosexuals from the extant literature, to produce annual estimates of HIV prevalence among high risk heterosexuals for each of 89 metropolitan statistical areas, from 1992 to 2013. It also produces estimates for these MSAs and years by racial/ethnic subgroup to allow for an examination of change over time in racial/ethnic disparities in HIV prevalence among high risk heterosexuals. RESULTS:The resulting estimates suggest that HIV prevalence among high risk heterosexuals has decreased steadily, on average, from 1992 to 2013. Examination of these estimates by racial/ ethnic subgroup suggests that this trend is primarily due to decreases among Black and Hispanic/Latino high risk heterosexuals. HIV prevalence among white high risk heterosexuals remained steady over time at around 1% during the study period. Although HIV prevalence among Black and Hispanic/Latino high risk heterosexuals was much higher (approximately 3.5% and 3.3%, respectively) than that among whites in 1992, over time these differences decreased as HIV prevalence decreased over time among these subgroups. By 2013, HIV prevalence among Hispanic/Latino high risk heterosexuals was estimated to be very similar to that among white high risk heterosexuals (approximately 1%), with prevalence among Black high risk heterosexuals still estimated to be almost twice as high. CONCLUSIONS:It is likely that as HIV incidence has decreased among heterosexuals from 1992 to 2013, mortality due to all causes has remained disparately high among racial/ethnic minorities, thereby outpacing new HIV cases. Future research should aim to empirically examine this by comparing changes over time in estimated HIV incidence among heterosexuals to changes over time in mortality and causes of death among HIV-positive heterosexuals, by racial/ethnic subgroup.

Criminal justice involved (CJI) individuals with a history of opioid use disorder (OUD) are at high risk of overdose and death in the weeks following release from jail. We developed the Justice-Community Circulation Model (JCCM) to investigate OUD/CJI dynamics post-release and the effects of interventions on overdose deaths. The JCCM uses a synthetic agent-based model population of approximately 150,000 unique individuals that is generated using demographic information collected from multiple Chicago-area studies and data sets. We use a high-performance computing (HPC) workflow to implement a sequential approximate Bayesian computation algorithm for calibrating the JCCM. The calibration results in the simulated joint posterior distribution of the JCCM input parameters. The calibrated model is used to investigate the effects of a naloxone intervention for a mass jail release. The simulation results show the degree to which a targeted intervention focusing on recently released jail inmates can help reduce the risk of death from opioid overdose.

HIV incidence among men who have sex with men (MSM) in Greece remains unchanged despite effective response to a recent outbreak among people who inject drugs (PWID). Network factors are increasingly understood to drive transmission in epidemics. The primary objective of the study was to characterize MSM in Greece, their sexual behaviors, and sexual network mixing patterns. We investigated the relationship between serostatus, sexual behaviors, and self-reported sex networks in a sample of MSM in Athens, Greece, generated using respondent driven sampling. We estimated mixing coefficients (r) based on survey-generated egonets. Additionally, multiple logistic regression was used to estimate adjusted odds ratios (AOR) and to assess relationships between serostatus, sexual behaviors, and sociodemographic indicators. A sample of 1,520 MSM participants included study respondents (n = 308) and their network members (n = 1,212). Mixing based on serostatus (r = 0.12, σ_r = 0.09-0.15) and condomless sex (r = 0.11, σ_r = 0.07-0.14) was random. However, mixing based on sex-drug use was highly assortative (r = 0.37, σ_r = 0.32-0.42). This study represents the first analysis of Greek MSM sexual networks. Our findings highlight protective behavior in two distinct network typologies. The first typology mixed assortatively based on serostatus and sex-drug use and was less likely to engage in condomless sex. The second typology mixed randomly based on condomless sex but was less likely to engage in sex-drug use. These findings support the potential benefit of HIV prevention program scale-up for this population including but not limited to PrEP.

Background: Structural properties of sociometric networks have been associated with behaviors related to HIV transmission. Very few studies, however, have explored the correlation between sociometric network factors and drug injection-related norms. Methods: This exploratory work: (i) describes basic structural qualities of a sociometric risk network of participants in the Transmission Reduction Intervention Project (TRIP) in Athens, Greece, in the context of a large HIV outbreak among people who inject drugs (PWID); (ii) measures HIV prevalence within specific structures within the sociometric risk network of PWID in TRIP; and (iii) explores the association of structural properties of the sociometric risk network in TRIP with drug injection-related norms. Results: The sociometric risk network in TRIP consisted of a large component (n = 241, 67.8%), a few small components (n = 36, 10.1%) with 2-10 individuals each, and some isolates (n = 79, 22.2%). HIV prevalence was significantly higher in the large component (55.6%), the 2-core (59.1%) and 3-core (66.3%) of the large component, and the 3-cliques of the cores. Drug injection-related norms were significantly associated with structural characteristics of the sociometric risk network. A safe behavioral pattern (use of unclean cooker/filter/rinse water was never encouraged) was significantly (p = 0.03) less normative among people who TRIP participants of the 2-core injected with (40.5%) than among network contacts of TRIP participants outside the 2-core (55.6%). On the contrary, at drug-using venues, 2-core members reported that safer behaviors were normative compared to what was reported by those without 2-core membership. Conclusions: Sociometric network data can give useful insights into HIV transmission dynamics and inform prevention strategies.Supplemental data for this article is available online at https://doi.org/10.1080/10826084.2021.1914103 .

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.

Big Events are periods during which abnormal large-scale events like war, economic collapse, revolts, or pandemics disrupt daily life and expectations about the future. They can lead to rapid change in health-related norms, beliefs, social networks and behavioural practices. The world is undergoing such Big Events through the interaction of COVID-19, a large economic downturn, massive social unrest in many countries, and ever-worsening effects of global climate change. Previous research, mainly on HIV/AIDS, suggests that the health effects of Big Events can be profound, but are contingent: Sometimes Big Events led to enormous outbreaks of HIV and associated diseases and conditions such as injection drug use, sex trading, and tuberculosis, but in other circumstances, Big Events did not do so. This paper discusses and presents hypotheses about pathways through which the current Big Events might lead to better or worse short and long term outcomes for various health conditions and diseases; considers how pre-existing societal conditions and changing 'pathway' variables can influence the impact of Big Events; discusses how to measure these pathways; and suggests ways in which research and surveillance might be conducted to improve human capacity to prevent or mitigate the effects of Big Events on human health.

More than 750,000 people in the United States died from an overdose between 1999 and 2018; two-thirds of those deaths involved an opioid. In this review, we present trends in opioid overdose rates during this period and discuss how the proliferation of opioid prescribing to treat chronic pain, changes in the heroin and illegally manufactured opioid synthetics markets, and social factors, including deindustrialization and concentrated poverty, contributed to the rise of the overdose epidemic. We also examine how current policies implemented to address the overdose epidemic may have contributed to reducing prescription opioid overdoses but increased overdoses involving illegal opioids. Finally, we identify new directions for research to understand the causes and solutions to this critical public health problem, including research on heterogeneous policy effects across social groups, effective approaches to reduce overdoses of illegal opioids, and the role of social contexts in shaping policy implementation and impact. Expected final online publication date for the Annual Review of Public Health, Volume 42 is April 1, 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

BACKGROUND:Big events (i.e., unique historical disruptions) like the COVID-19 epidemic and its associated period of social distancing can transform social structures, social interactions, and social norms. Social distancing rules and the fear of infection have greatly reduced face-to-face interactions, increased loneliness, reduced ties to helping institutions, and may also have disrupted the opioid use behaviors of people who use drugs. This research used Reddit to examine the impact of COVID-19 on the social networks and social processes of people who use opioids. METHODS:Data were collected from the social media forum, Reddit.com. At the beginning of the COVID-19 pandemic in the U.S. (March 5, 2020, to May 13, 2020), 2,000 Reddit posts were collected from the two most popular opioid subreddits (r/OpiatesRecovery, r/Opiates). Posts were reviewed for relevance to COVID-19 and opioid use resulting in a final sample of 300. Thematic analysis was guided by the Big Events framework. RESULTS:The COVID-19 pandemic was found to create changes in the social networks and daily lives among persons who use opioids. Adaptions to these changes shifted social networks leading to robust social support and mutual aid on Reddit, including sharing and seeking advice on facing withdrawal, dealing with isolation, managing cravings, and accessing recovery resources. CONCLUSIONS:Reddit provided an important source of social support and mutual aid for persons who use opioids. Findings indicate online social support networks are beneficial to persons who use opioids, particularly during big events where isolation from other social support resources may occur.

BACKGROUND:Improving HIV diagnosis, access to care and effective antiretroviral treatment provides our global strategy to reduce HIV incidence. To reach this goal we need to increase our knowledge about local epidemics. HIV infection dates would be an important information towards this goal, but they are largely unknown. To date, methods to estimate the dates of HIV infection are based mainly on laboratory or molecular methods. Our aim was to validate molecular clock inferred infection dates that were estimated by analysing sequences from 145 people living with HIV (PLHIV) with known transmission dates (clinically estimated infection dates). METHODS:All HIV sequences were obtained by Sanger sequencing and were previously found to belong to well-established molecular transmission clusters (MTCs). RESULTS:Our analysis showed that the molecular clock inferred infection dates were correlated with the clinically estimated ones (Spearman's Correlation coefficient = 0.93, p < 0.001) and that there was an agreement between them (Lin's concordance correlation coefficient = 0.92, p < 0.001). For most cases (61.4%), the molecular clock inferred preceded the clinically estimated infection dates. The median difference between clinically and molecularly estimated dates of infection was of 0.18 (IQR: -0.21, 0.89) years. The lowest differences were identified in people who inject drugs of our study population. CONCLUSIONS:) of nodes within clusters provides a reliable approximation of HIV infections for PLHIV infected within MTCs. Next-generation sequencing data and molecular clock estimates based on heterochronous sequences provide, probably, more reliable methods for inferring infection dates. However, since these data are not available in most of the HIV clinical laboratories, our approach, under specific conditions, can provide a reliable estimation of HIV infection dates and can be used for HIV public health interventions.