Analysis and Prediction of Opioid Crisis Based on Data Mining
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The final report released by the White House Commission on combating drug addiction and the opioid crisis (2017), noted that opioid prescriptions have quadrupled since 1999 with more than 27 million people using them in non-prescription way. Opioid crisis breaks down geographic and demographic boundaries. This report calls on the government, various institutions and the masses to work together to overcome the opioid crisis. We hope to provide some effective advice through our efforts. First, we use four charts to visually analyze synthetic opioid and heroin cases in five states and their counties. Second, in order to verify the relationship between socioeconomic factors and opioid, we filter the socioeconomic data of five states and summarize them into 16 categories of indicators according to their definitions. Finally, in response to the proliferation of heroin in the Ohio, we recommend the government's two strategies for encouraging military service, increasing adult enlistment rates, and managing immigration with drug-related crime records. In the process of solving the problem, we mainly use R language and Python to draw pictures and build models.
Opioid, crisis, prescription, proliferation, socioeconomic factors