w209 Final Project

Introduction

Instructions

All of the data visualizations are interactive, so please explore the plots to drill down and examine their various elements.

It is recommended that users expand each visualization to full screen for optimal display.

There is complementary text in each section to provide context for the visualizations. Please reference as needed.

Motivation & Purpose

The opioid epidemic in United States has driven a rapid increase in drug overdose deaths. According to the CDC, from 1999 to 2017, more than 700,000 people have died from a drug overdose in the U.S. and these deaths have increasingly involved opioids.

As public attention and media coverage focuses more on this epidemic, policymakers have faced increasing pressure to take action. The purpose of this study is, therefore, to use data visualization to inform policymakers on the nature of the epidemic and the various factors influencing its spread so that they can be well-informed in designing intervention strategies.

Topics

This report focuses on three research areas that are relevant for potential policy interventions and are commonly discussed (though perhaps misunderstood) in the public discourse:

Drug Categories	The changing landscape of classes of opioids causing overdose deaths
Prescription Opioids	The relationship of the increase in overdose deaths with the prescription opioid market
Socio-Economic Factors	Potential geographical and socio-econmic factors to be considered for more targeted opioid intervention policies

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Drug Categories

Synthetic Opioid Overdose Deaths are Increasing Rapidly

Drug Class	Description
Natural/Semisynthetic Opioids	Drugs (primarily prescription opioids [RxOs]) containing (or derived from) natural opiate chemicals found in the opium plant (e.g. morphine [natural], oxycondone [semi-synthetic])
Heroin	A particular semi-sythetic opioid that is distributed illicitly
Synthetic Opioids	Opioids not derived from the opium plant, but rather completely lab-created chemicals (e.g. fentanyl)
Methadone	A synthetic opioid that is widely used to treat opioid addiction as a means to weaken cravings and withdrawl symptoms

Drug overdose deaths attributable to synthetic opioids have increased 10x since 2012. Increased availability and potency of fentanyl in particular has been driving this trend. Fentanyl can be made in a lab, thereby making it easier to produce and distribute illicitly. Fentanyl is also much more potent than heroin and RxOs, making it especially dangerous; while a standard dosage of RxOs for chronic pain treatment would be roughly 50 morphine-milligram-equivalent per day, the lethal does of fentanyl is only one milligram.

For context, alcohol-related deaths (other, i.e. non-poisoning such as liver disease) and non-opioid-related overdose deaths have increased across that span as well (see bottom 2 charts). However opioid-related overdoses have surpassed both in the past 3 years and the trend is only increasing. A rapid increase in heroin overdose deaths preceded the rise of fentanyl but appears to have plateaued.

Note that deaths here are defined according to ICD-10 Cause-of-Death codes. This limits the represented deaths here according to medical diagnoses at time of death. This is important context when interpretting these results. Read more here.

Prescription Opioids

Prescriptions Opioids Correlated with RxO Overdose, but not Heroin or Synthetic Opioid Overdose

One common story shared from the opioid epidemic is that of people prescribed RxOs who then begin to misuse and abuse their prescriptions. These people may then become opioid dependent or addicted and potentially divert to taking an illicit opioid, such as heroin.

In this plot we compare RxO prescribing rates with overdose deaths across the 3 main opioid drug classes. Each point represents an annual observation for a single state in one of the three most rercent years of data (2015-2017). Note that state-level reporting for overdose deaths by class is limited and these results have been limited to only include those states with available data.

The scatter plots here appear to indicate that states in years with higher RxO prescribing rates have a slightly higher number of RxO overdose deaths on average, but the inverse is true for heroin and synthetic opioid overdoses.

It stands to reason that these plots may indicate that availability of RxOs will make that a more likely source for opioid abuse, whereas where there are fewer RxOs users may tend to seek heroin and fentanyl.

Socio-Economic Factors

Ongoing Opioid Epidemic has Caused Personal & Financial Toll on the Public

U.S. Department of Health and Human Services provides grants to States for substance abuse treatment and prevension programs via Substance Abuse and Mental Health Services Administration (SAMHSA).

Figure on the right shows SAMHSA budget between 2007 and 2018. Opioid deaths per 100,000 are also shown. Federal and State governments response to the epidemic (at least budgetarily) has lagged behind.

In the following page, we will dive into the opioid epidemic metrics, state government spending to combat the epidemic and socio-economic parameters during the same time period.

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Resources

The data underlying this project were gathered from the following sources:

Data	Source
Opioid Overdose Deaths by Class (US)	CDC, Data Brief 329. Drug Overdose Deaths in the United States, 1999–2017
Alcohol and Drug Deaths (by State)	CDC, WONDER. Database Query.
Prescribing Rates (by State)	CDC, U.S. Opioid Prescribing Rate Maps.
RxO Misuse + Heroin Use Rates (by State)	SAMHSA, NSDUH Estimated Totals by State. Tables 5/9: Heroin Use in the Past Year. Tables 11/12: Pain Reliever Misuse in the Past Year (year-dependent)
Opioid Abuse Prevention and Treatment Budget per State	SAMHSA Annual Budget (2009-2018) (year-dependent)
Population (by State)	US Census
Unemployment (by State)	Bureau of Labor Statistics

Tim

Murat