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Investigating the importance of social vulnerability in opioid-related mortality across the United States

2024-12-03 · Andrew Deas, Adam Spannaus, Dakotah D. Maguire, Jodie Trafton, Anuj J. Kapadia, Vasileios Maroulas

The opioid crisis remains a critical public health challenge in the United States. Despite national efforts to reduce opioid prescribing rates by nearly 45\% between 2011 and 2021, opioid overdose deaths more than tripled during this 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 socioeconomic 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 socioeconomic 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 components of the Social Vulnerability Index (SVI). 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 social factors 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.

📄 PDF Abstract BibTeX arXiv:2412.15218

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Feature Importance

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Softmax The Softmax output function transforms a previous layer's output into a vector of probabilities. It is commonly used for multiclass classification. Given an input vector $x$…
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