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Andrew Deas

Publications and source records attributed to Andrew Deas.

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Investigating the importance of county-level characteristics in opioid-related mortality across the United States

The opioid crisis remains a critical public health challenge in the United States. Despite national efforts which reduced opioid prescribing rates by nearly 45\% between 2011 and 2021, opioid-related overdose deaths more than tripled during the same period. This alarming trend reflects a major shift in the crisis, with illegal opioids now driving the majority of overdose deaths instead of prescription opioids. Although much attention has been given to supply-side factors fueling this transition, the underlying structural conditions that perpetuate and exacerbate opioid misuse remain less understood. Moreover, the COVID-19 pandemic intensified the opioid crisis through widespread social isolation and record-high unemployment; consequently, understanding the underlying drivers of this epidemic has become even more crucial in recent years. To address this need, our study examines the correlation between opioid-related mortality and thirteen county-level characteristics related to population traits, economic stability, and infrastructure. Leveraging a nationwide county-level dataset spanning consecutive years from 2010 to 2022, this study integrates empirical insights from exploratory data analysis with feature importance metrics derived from machine learning models. Our findings highlight critical regional characteristics strongly correlated with opioid-related mortality, emphasizing their potential roles in worsening the epidemic when their levels are high and mitigating it when their levels are low.

cs.CY

Identifying Spatiotemporal Patterns in Opioid Vulnerability: Investigating the Links Between Disability, Prescription Opioids and Opioid-Related Mortality

The opioid crisis remains one of the most daunting and complex public health problems in the United States. This study investigates the national epidemic by analyzing vulnerability profiles of three key factors: opioid-related mortality rates, opioid prescription dispensing rates, and disability rank ordered rates. This study utilizes county level data, spanning the years 2014 through 2020, on the rates of opioid-related mortality, opioid prescription dispensing, and disability. To successfully estimate and predict trends in these opioid-related factors, we augment the Kalman Filter with a novel spatial component. To define opioid vulnerability profiles, we create heat maps of our filter's predicted rates across the nation's counties and identify the hotspots. In this context, hotspots are defined on a year-by-year basis as counties with rates in the top 5 percent nationally. Our spatial Kalman filter demonstrates strong predictive performance. From 2014 to 2018, these predictions highlight consistent spatiotemporal patterns across all three factors, with Appalachia distinguished as the nation's most vulnerable region. Starting in 2019 however, the dispensing rate profiles undergo a dramatic and chaotic shift. The initial primary drivers of opioid abuse in the Appalachian region were likely prescription opioids; however, it now appears that abuse is sustained by illegal drugs. Additionally, we find that the disabled subpopulation may be more at risk of opioid-related mortality than the general population. Public health initiatives must extend beyond controlling prescription practices to address the transition to and impact of illicit drug use.

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