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Drug Checking and Current Supply Trends (Harm Reduction Academy, May 2025)
No full textPresentation to the NC Harm Reduction Academy on drug checking technology and current trends in the unregulated drug supply
Tracking Venus: A Transatlantic Comparative Study of Historical Sites Commemorating the Slave Trade
No full textWith the support of the Burch Fellowship, I spent six weeks in the summer of 2024 following the route of Venus, a slaving ship that stole and carried 320 souls across the Atlantic Ocean in 1784. Throughout my travels to England, Ghana, and the American South, I examined the ways nuanced narratives are employed at various monuments, museums, and other public-facing forms of historical commemoration. At the start of the summer I had no idea how this journey would become one of the most immersive and challenging endeavors I’ve ever undertaken.
The museums I visited in London and Liverpool revealed an incredible wealth of resources, yet a systemic reluctance to critically engage with Britain’s colonial legacy. Conversations with exhibit curators and historians like Hakim Adi highlighted my understanding of the limitations imposed by institutional interests, making it clear how much work remains in presenting a truthful narrative on Britain’s role as an oppressive colonial figure.
In Ghana, I was met with incredible warmth and generosity. My guide, Enoch, quickly became both an academic peer and a dear friend. Enoch was instrumental in connecting me with local historians and griots who shared invaluable insights. Unlike the detached exhibits in London, Ghanaian sites like Assin Manso or Cape Coast Castle have transformed painful historical locations into places of healing. In addition to my research, I embraced traditional experiences—from cooking lessons, to drum performances, and lessons from textile artisans—which allowed me to fully appreciate Ghana’s cultural richness.
Although my time in Charleston was temporarily curtailed by the flooding caused by Hurricane Debby, it was nonetheless impactful. I encountered a complex intersection of memory and heritage unique to the American South. Visiting the International African American Museum and the Old Slave Mart Museum reminded me that Charleston, like London, carries a burden of history often veiled by preservation for tourism. These sites also bore the unmistakable weight of the American South's painful past, defined by the legacies still impacting affected communities today. My time in Charleston reaffirmed the importance of integrating contemporary voices and perspectives into memorial spaces, further enriching my thesis
Intersection Between Public Transit and Pedestrian Connectivity in North Carolina’s Triangle Region
Get PDFPedestrian infrastructure and transit stops are often planned separately, leading to poor connectivity between bus stops and the riders’ origins or destinations. This disconnectivity can contribute to inequities in safe and accessible transit options. This study investigates the spatial relationship between existing pedestrian infrastructure and transit stops within the Triangle region. Applying a scoring methodology, focused on existing sidewalk coverage as well as destination, safety, and demographic data, to all of the bus stops and running a spatial cluster analysis allowed for the identification of areas in need of pedestrian infrastructure improvement. High-need areas often lacked not only immediate sidewalk access but also adequate sidewalk coverage within their 5-minute walksheds. Additionally, many of these high-need areas correlate with communities experiencing high social vulnerability. Evaluating these high-need areas in relation to existing funding sources and planning processes allows for targeted recommendations for strengthening pedestrian-transit connectivity. This methodology serves as a tool to identify areas requiring pedestrian improvements in proximity to existing transit stops. The results, specific to Raleigh, North Carolina, can inform local transportation planning efforts and help eliminate gaps in pedestrian connectivity, ultimately enhancing access to local and regional transit systems.Master of City and Regional Plannin
Exploring the Intersection of Data Center Expansion and Generative Artificial Intelligence via an Equity Impact Assessment
Get PDFThis work provides an in-depth analysis of the impacts of data center expansion with the understanding that the need for large data centers is growing due to the introduction of generative AI. The author adapted the structure of an Equity Impact Assessment to complete the work. The author completed this analysis using material from PubMed, SCOPUS, Nexus Uni, and advanced Google searches with a domain limited to “gov”. These searches yielded perspectives from governmental agencies, community members surrounding the data centers, and academic leaders. The findings of this work include environmental justice concerns, unequal hiring practices, strain on energy grids, and an increase in cost to local communities. These concerns are likely to compound with existing environmental injustices like the impacts of concentrated animal farm operations and solid waste landfills, both of which disproportionately negatively impact communities of color, rural communities, and people with low socio-economic status. This work can inform future public health endeavors in practice and research. Key recommendations include examining the hiring practices and the environmental impacts associated with large data centers. It is essential to involve community members in the research process, given the current lack of information from their perspectives. Additionally, decisions about land use and energy alternatives must incorporate input from community members and environmental justice leaders, who are often excluded. The evaluation of existing programs, such as incentives and community college training programs also offer opportunities to prepare communities for introduction of large data centers.
Keywords: data center(s), generative artificial intelligence, environmental impact(s), equity impact assessmentMaster of Public Healt
Clusters, Cities, and COVID-19: The Impacts on Employment Centers in Virginia
Get PDFThis project sought to do two things—attempt to understand the still-unfolding impacts of the 2020 COVID-19 pandemic on the city itself, and the ways in which defining that city alters the outcome. More narrowly, I sought to understand the impact of COVID-19 on employment centers. To do this, I employed a Hierarchical Density-based Spatial Clustering of Applications with Noise (HDBSCAN) to create spatial clusters to identify significant clusters of employment using from the U.S. Census Bureau’s synthetic employment data. I measured -COVID-19's impacts through variables such as wages, industry diversity, employment change and changes in sales volume. Throughout this process I sought to refine and explore the clustering methodology and understand its limitations and successes in context with the economic state of Virginia, as an example. The results varied by region, showing that both the impacts of COVID-19, as well as modeling and data, are spatially dependent. I find that there may be a loss in low- to mid-wage jobs, or a movement of wages upwards, that results in better outlooks for the number of high wage jobs post-COVID-19. I also find there is some relation to the impacts of COVID-19 and employment clustering, and there does seem to be potential movement out of centers and into sub- and outer centers, but that is also dependent on what centers they are, and where they are.Master of City and Regional Plannin
Probabilistic classification of gene-by-treatment interactions on molecular count phenotypes.
Get PDFGenetic variation can modulate response to treatment (G×T) or environmental stimuli (G×E), both of which may be highly consequential in biomedicine. An effective approach to identifying G×T signals and gaining insight into molecular mechanisms is mapping quantitative trait loci (QTL) of molecular count phenotypes, such as gene expression and chromatin accessibility, under multiple treatment conditions, which is termed response molecular QTL mapping. Although standard approaches evaluate the interaction between genetics and treatment conditions, they do not distinguish between meaningful interpretations such as whether a genetic effect is only observed in the treated condition or whether a genetic effect is observed but accentuated in the treated condition. To address this gap, we have developed a downstream method for classifying response molecular QTLs into subclasses with meaningful genetic interpretations. Our method uses Bayesian model selection and assigns posterior probabilities to different types of G×T interactions for a given feature-SNP pair. We compare linear and nonlinear regression of log -scale counts, noting that the latter accounts for an expected biological relationship between the genotype and the molecular count phenotype. Through simulation and application to existing datasets of molecular response QTLs, we show that our method provides an intuitive and well-powered framework to report and interpret G×T interactions. We provide a software package, ClassifyGxT [1]
Barriers and facilitators to oral pre-exposure prophylaxis uptake among adolescents girls and young women at elevated risk of HIV acquisition in Lilongwe, Malawi: A qualitative study
Get PDFAmong the estimated 12,500 new HIV infections in Malawi among people aged 15-24 each year, 70 percent occur in Adolescent Girls and Young Women (AGYW). The Ministry of Health (MoH) in Malawi rolled out an oral Pre-Exposure Prophylaxis (PrEP) prevention program targeting populations at elevated risk of HIV acquisition, including AGYW, in 2021. Since PrEP roll-out, there has been limited research exploring the factors that influence uptake of PrEP among AGYW. This study explored the barriers and facilitators to the uptake of PrEP among AGYW at elevated risk of HIV acquisition. it was an exploratory qualitative study conducted at Kawale Health Center in Lilongwe, Malawi, in February 2023, which employed a phenomenological design. Data were collected using semi-structured in-depth interviews and vignettes from purposively sampled 20 AGYW and 10 health care workers (HCWs) based on their PrEP status (on PrEP versus not on PrEP) and involvement in PrEP provision, respectively. The data were digitally recorded, managed using NVivo software and analysed using a thematic approach guided by the Consolidated Framework for Implementation Research (CFIR). AGYW identified perceived HIV risk and vulnerability and PrEP knowledge as facilitators. HCWs identified AGYW perceived HIV risk, HCW altitudes, and availability of youth friendly service center and resources as facilitators to PrEP uptake. Barriers identified by AGYW included PrEP side effects, limited PrEP information, lack of privacy, stigma, and lack of transportation. HCWs identified limited resources and burden of work as barriers. In conclusion, PrEP's full potential as an HIV prevention tool for AGYW requires a holistic approach that considers their particular requirements, removes systemic hurdles, and guarantees access to high-quality services. In addition, there is a need to create demand to increase the uptake of PrEP
Elucidating the mechanistic relationships between peroxisome proliferator–activated receptors and hepatic fibrosis using the ROBOKOP knowledge graph
Get PDFWe developed the Reasoning Over Biomedical Objects linked in Knowledge Oriented Pathways (ROBOKOP) application as an open-source knowledge graph system to support evidence-based biomedical discovery and hypothesis generation. This study aimed to apply ROBOKOP to suggest biological mechanisms that might explain the hypothesized relationship between exposure to the herbicide and lipid-lowering drug clofibrate, an activator of peroxisome proliferator-activated receptor-α (PPARA), and hepatic fibrosis. We queried ROBOKOP to first establish that it could demonstrate a relationship between clofibrate and PPARA as a validation test and second to identify intermediary genes and biological processes or activities that might relate the activation of PPARA by clofibrate to hepatic fibrosis. Queries of ROBOKOP returned several paths relating clofibrate, PPARA, and hepatic fibrosis. One path suggested the following: clofibrate – affects / increases_ expression_ of / increases_ activity_ of / increases_ response_ to / decreases_ response_ to / is_ related_ to – PPARA – is_ actively_ involved_ in – cellular response to lipid – actively_ involves – CCL2 – is_ genetically_ associated_ with – hepatic fibrosis. This result established a relationship between clofibrate and PPARA and further suggested that PPARA is actively involved in the cellular response to lipids, which actively involves the chemokine ligand CCL2, a gene genetically associated with hepatic fibrosis; thus, we can infer that PPARA, upon activation by clofibrate, plays a role in hepatic fibrosis. We conclude that ROBOKOP can be used to derive insights into biological mechanisms that might explain relationships between environmental exposures and liver toxicity
Evaluation of a combination adherence strategy to support HIV antiretroviral therapy for pregnancy and breastfeeding in Malawi: A pilot randomized clinical trial
Get PDFBackground There has been tremendous progress in reducing vertical transmission of HIV in the past two decades due to the broad availability of antiretroviral therapy (ART) globally. Despite this progress, new paediatric infections are still occurring. Methods In a pilot study, we evaluated a combination adherence support package, which included an adapted motivational interviewing-informed counselling approach (Integrated Next Step Counselling, iNSC) and an optional adherence supporter, for pregnant and breastfeeding women living with HIV. Participants were recruited from the antenatal clinic in Lilongwe, Malawi. Eligible participants were randomly allocated 1:1 to receive either the combination adherence package (intervention) or standard care (control) at the health facility. Our clinical outcome, measured at three- and six-month follow-up, was a composite endpoint of study retention with HIV viral suppression (HIV RNA <40 copies per mL). Results We screened 106 women living with HIV between March and July 2020. Of these, 100 women enrolled and were randomly assigned to intervention (n=51) or control (n=49). The majority of participants (94 of 100; 94%) were newly diagnosed with HIV. Retention in care was 92% at three months and 84% at six months. Three-quarters of women retained in care were virally suppressed at the three- and six-month study visits. At three months, our composite outcome (retention & viral suppression) was achieved by 70.6% (36/51) and 69.4% (34/49) of women in the intervention and control groups, respectively. At six months, this composite outcome was achieved by 68.6% (35/51) of the intervention group and 61.2% (30/49) of the control group (probability difference: 7.4%, 95% CI: -11.3%, 26.1%). Conclusion These encouraging pilot findings suggest that this combination adherence package could be used to support ART adherence among pregnant and breastfeeding women living with HIV. We demonstrate feasibility of using a combined measure of adherence and viral suppression as an outcome measure. Trial registration ClinicalTrials.gov (NCT04330989)
TREE-BASED MODELS FOR LEARNING COMPLEX DISTRIBUTIONS
Get PDFTree-based models are some of the most successful machine learning models. Their simplicity makes them considerably faster to tune and more robust than deep learning, leading to their dominant performance on tabular datasets. We investigate the use of tree-based models on two problem types. The first is feature importance in nonlinear settings using Shapley values and Shapley-inspired methods. While model-based Shapley values might be accurate explainers of model predictions, machine learning models themselves are often poor explainers of the DGP even if the model is highly accurate. We introduce a novel metric, Shapley Marginal Surplus for Strong Models, that samples the space of possible models to come up with a truly explanatory measure of feature importance. We compare this method to other popular feature importance methods, both Shapley-based and non-Shapley based, and demonstrate significant outperformance relative to other methods. We also provide potential extensions using Bayesian optimization and online reinforcement learning to improve performance. The second problem is using a tree-based representation of a bargaining game to predict coalition formation in parliamentary governments. Represented as extensive form bargaining games, single trials of these games have orders of magnitude more states than existing game theory challenge problems such as poker. Using a heavily coarsened game tree and a novel constrained fictitious play algorithm for most of the actors in the model, we reduce these incalculably large game trees to manageable dimensions and then find optimal coalitions using Monte Carlo counterfactual regret (MCCFR) tree search.Doctor of Philosoph