Publications by authors named "Brandon D L Marshall"

Background: The overlapping epidemics of opioid use disorder (OUD) and HIV present a critical public health challenge. Although people with OUD frequently engage with healthcare settings, uptake of HIV prevention services such as pre-exposure prophylaxis (PrEP) remains low. Integrating HIV prevention into routine OUD care could reduce new infections, but scalable, evidence-based strategies are lacking.

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Objectives: In Rhode Island, drug overdose deaths increased by 28% in the first 6 months of the COVID-19 pandemic in 2020 as compared with the previous year (2019), mirroring national trends. We explored how the spatial distribution of overdose deaths overlapped with that of COVID-19 cases to identify levels and increased prevalence of these health issues among census tracts in Rhode Island.

Methods: We used data from the Rhode Island Department of Health and the US Census Bureau to calculate annualized COVID-19 case rates (from March 20, 2020, through December 31, 2021) and unintentional overdose death rates by census tract (from January 1, 2018, through December 31, 2021).

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Purpose: Develop a spatially dynamic agent-based model to assess the impact of gentrification-induced migration on HIV transmission among heterosexual African American/Black women.

Methods: We simulated a population of heterosexual African American/Black adults diagnosed with or at risk for HIV in a spatially dynamic agent-based model. We included behavioral and HIV-related probabilities based on neighborhood of residence, distance to healthcare facilities from their neighborhood, and neighborhood disadvantage status.

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Background: Previous research has documented differing drug use patterns and risk behaviors by gender identity and sex at birth, although variations in harm reduction practices by these characteristics have not yet been fully assessed.

Methods: We utilized data from the Rhode Island Prescription and Illicit Drug Study (RAPIDS), which enrolled adults who used drugs from 2020 to 2023. Participants were analyzed based on gender identity: men, women, and other (including those identifying as non-binary or something else).

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Context: Predictive modeling can identify neighborhoods at elevated risk of future overdose death and may assist community organizations' decisions about harm reduction resource allocation. In Rhode Island, PROVIDENT is a research initiative and randomized community intervention trial that developed and validated a machine learning model that predicts future overdose at a census block group (CBG) level. The PROVIDENT model prioritizes the top 20th percentile of CBGs at highest risk of future overdose death over the subsequent 6-month period.

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Introduction: This study describes the distribution and administration of naloxone throughout one state heavily impacted by the opioid overdose crisis. We sought to: 1) assess whether naloxone kits were used in rescue attempts in the same communities where they were distributed, and 2) explore how best to define geographical boundaries for comparing naloxone supply to demand, accounting for naloxone mobility patterns to identify areas of surplus or shortage.

Methods: used data from Massachusetts' Overdose Education and Naloxone Distribution (OEND) programs for 2018-2020, linking participants' residence, overdose rescue attempt, and refill locations at the ZIP code level.

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Policy Points State and local governments are receiving over $50 billion in opioid settlement funds over 18 years to mitigate the harms from the opioid crisis. Lessons learned from the Tobacco Master Settlement of the 1990s can ensure that funds are administered according to best practices and are spent on evidence-based interventions. Recent efforts to track opioid settlement spending around the country shed light on encouraging trends such as overdose rate reductions, unmet challenges like reducing inequities, and areas in need of continued vigilance and improvement like transparency and evaluation.

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Background: The bidirectional relationships between opioid use and depressive symptom severity among people living with HIV (PLHIV) are poorly understood. We hypothesized that higher opioid use frequency would be associated with greater subsequent depressive symptom severity and that greater depressive symptom severity would be associated with higher subsequent opioid use frequency.

Methods: We analyzed data from the Veterans Aging Cohort Study (VACS) - survey sample, a prospective cohort including PLHIV receiving care at 8 US Veterans Health Administration sites.

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Background: The unregulated illicit drug supply is a key factor in Canada's ongoing drug crisis and a significant public health concern. This study explores whether having a regular drug dealer impacts the likelihood of obtaining drug checking results consistent with expectations (i.e.

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Policy Points We can leverage data science and artificial intelligence to inform state and local resource allocation for overdose prevention. Data science and artificial intelligence can help us answer four questions: (1) What is the impact of laws on access to interventions and overdose risk? (2) Where should interventions be targeted? (3) Which types of demographic subgroups benefit the most and the least from interventions? and (4) Which types of interventions should they invest in for each setting and population? Advances in data science and artificial intelligence can accelerate the pace at which we can answer these critical questions and help inform an effective overdose prevention response.

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More than one million people have died from drug overdose in the United States in the past 20 years. The overdose crisis started in the late 1990s with the proliferation of overdoses involving prescription opioids, transitioned to heroin-involved overdoses in 2010, and is currently driven by illegally manufactured synthetic opioids such as fentanyl. In response to this crisis, New York City implemented two publicly recognized overdose prevention centers (OPCs) in the nation in November 2021.

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To meet the needs of diverse communities, public health authorities are increasingly reliant on hyperlocal interventions targeting specific health issues and distinct populations. To facilitate epidemiological evaluation of hyperlocal interventions on community-level outcomes, we developed a framework of six practice-based considerations for researchers: spatial zone of impact, temporal resolution of impact, outcome of interest, definition of a plausible comparison group, micro vs. macro impacts, and practitioner engagement.

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As the United States grapples with an ongoing overdose crisis, states and jurisdictions are adopting novel approaches to reduce overdose mortality. In one novel approach, public health researchers and leaders in Rhode Island leveraged the state's robust surveillance data and collaborations between government, academic, and community-based organizations (CBOs) to launch the PROVIDENT (PReventing OVerdose using Information and Data from the EnvironmeNT) project, a population-based randomized controlled research trial (NCT05096429) in December 2019. The PROVIDENT trial utilizes machine learning (ML) methods to identify neighborhoods at risk of future overdose deaths at the census-block-group level to inform community-level overdose prevention resource distribution.

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Introduction: Overdose deaths have increased sharply in the past five years. States have implemented overdose education and naloxone distribution (OEND) initiatives to mitigate overdose deaths at a population level. Irvine et al.

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Background: A barrier to remaining in substance use treatment in the U.S. is abstinence-based policies, which can lead to premature treatment termination.

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Following federal regulatory changes during the COVID-19 pandemic, Rhode Island expanded methadone access for opioid treatment programs (OTPs) in March 2020. The policy, which permitted take-home dosing for patients, contrasted with longstanding restrictions on methadone. This study used patient-level OTP admission and discharge records to compare six-month retention before and after the policy change.

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Overdose prevention centers (OPCs) offer supervised environments for drug consumption and harm reduction services, yet their implementation in the United States (US) remains limited. The present study analyzed the perspectives of residents and employees within a 0.75-mile radius of the first state-authorized OPC in the US (N=125).

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Noninvasive nonpharmacologic therapies are recommended for managing acute low back pain (aLBP) and have the potential to mitigate opioid-related harms. However, little is known about whether incorporating nonpharmacologic therapies into aLBP management affects adverse outcomes. The objective was to determine if receiving nonpharmacologic pain therapies, alone or combined with pharmacologic options, is associated with drug-related overdose hospitalizations among Medicare beneficiaries with aLBP.

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Objectives: To evaluate the predictive performance of different data sources to forecast fatal overdose in Rhode Island neighborhoods, with the goal of providing a template for other jurisdictions interested in predictive analytics to direct overdose prevention resources.

Methods: We evaluated seven combinations of data from six administrative data sources (American Community Survey (ACS) five-year estimates, built environment, emergency medical services non-fatal overdose response, prescription drug monitoring program, carceral release, and historical fatal overdose data). Fatal overdoses in Rhode Island census block groups (CBGs) were predicted using two machine learning approaches: linear regressions and random forests embedded in a nested cross-validation design.

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Adolescents in the juvenile legal system have unaddressed sexual health needs. Factors at multiple ecological levels-including caregivers or neighborhoods-may promote or hinder sexual health for this group. We aimed to identify targets for future intervention by determining the associations between sexual behaviors and multilevel risk and protective factors among adolescents involved in the juvenile legal system.

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Introduction: In July 2021, Rhode Island became the first state in the United States (US) to legalize overdose prevention centers (OPCs). To inform the design and implementation of an OPC in Providence, Rhode Island's capital, we explored perceptions of OPCs and programmatic needs among people who use drugs.

Methods: The study conducted in-depth qualitative interviews from December 2023 to March 2024 with 25 people who use drugs.

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Background: As in much of the United States, there have been significant increases in overdose deaths among non-Hispanic Black and Hispanic/Latinx populations in Rhode Island over the past decade. Given the shifting dynamics of the overdose epidemic, there is an urgent need for focused interventions that address the specific needs of diverse communities. This study explores differences in drug use patterns, harm reduction behaviors and types and barriers to treatment by race and ethnicity.

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Objectives: The escalating overdose crisis in the United States points to the urgent need for new and novel data tools. Overdose data tools are growing in popularity but still face timely delays in surveillance data availability, lack of completeness, and wide variability in quality by region. As such, we need innovative tools to identify and prioritize emerging and high-need areas.

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