Uncovering Patterns in Accidental Drug Overdose Deaths: A Data-Driven Approach Using Demographic and Substance-Specific Analysis

The mounting tragedy of drug overdose deaths poses a critical public health issue globally. In this paper, patterns and drivers of fatal accidental overdoses from drugs are explored utilizing an extensive dataset named "Accidental_Drug_Related_Deaths.csv" containing 11,981 observations with demographic and substance factors. Employing exploratory data analysis and data mining methods, the research reveals primary trends in substance abuse, demographic risk, and regional clustering of drug-overdose mortality. Our findings indicate that opioids, including fentanyl, heroin, and cocaine, are among the most lethal drugs with varied impact on varied ages. Of concern is that unusual incidents in very old and young individuals hint at age-based risk due to unintentional intake or misuse of drugs. Besides, frequent patterns of overdose among residential spaces such as Hartford suggest socio-environmental risk and absence of rehab centers. The results of this study aim to inform health authorities, policymakers, and community leaders in how to develop more efficient prevention, treatment, and enforcement strategies to stem the drug overdose crisis.