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Official April BARUG Meetup
6:30 - Food, drink and networking 7:00 - Announcements 7:05 - TBD 7:45 - Dan Putler: Locating Opioid Treatment Centers in Under Served Areas Using R and Alteryx ############# Dan Putler Locating Opioid Treatment Centers in Under Served Areas Using R and Alteryx In 2016 there were nearly 64,000 drug overdose deaths in the United States, the lion's share of these due to opioid abuse. It is now recognized that America is facing an Opioid epidemic. Treatment of opioid addiction is one of the primary tools available for addressing the epidemic. However, many of the areas hardest hit by opioid use are believed to be under served from a treatment perspective. One issue currently impeding the location of treatment facilities is the lack of fine grained data associated with the location of individuals who abuse opioids. This talk presents an app that is designed to assist public health officials and others in locating opioid treatment facilities in under served areas. To do this, estimates of the number of adults who abuse opioids at the census tract level are developed using R along with data from the U. S. Department of Health and Human Service's National Survey on Drug Use and Health and both census tract level data and the microdata sample from the U. S. Census Bureau's American Community Survey. The census tract level estimates of adult opioid abusers is used, along with data on the locations of existing opioid treatment facilities, to locate new facilities in areas that are further than ten miles from existing facilities, and maximize the estimated number of abusers within a ten mile radius of the new facilities. The optimization is done using an evolutionary algorithm that is implemented in Alteryx. The resulting application can then be deployed on the web via the Alteryx Gallery.


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    R is an open source programming language for statistical computing, data analysis, and graphical visualization. R has an estimated one million users worldwide, and its user base is growing. While most commonly used within academia, in fields such as computational biology and applied statistics, it is gaining currency in commercial areas such as quantitative finance and business intelligence.

    Among R's strengths as a language are its powerful built-in tools for inferential statistics, its compact modeling syntax, its data visualization capabilities, and its ease of connectivity with persistent data stores (from databases to flatfiles).

    In addition, R's open source nature and its extensibility via add-on "packages" has allowed it to keep up with the leading edge in academic research.

    For all its strengths, though, R has an admittedly steep learning curve; the first steps towards learning and using R can be challenging.

    To this end, the Bay Area R Users Group is dedicated to bringing together area practitioners of R to exchange knowledge, inspire new users, and spur the adoption of R for innovative research and commercial applications.

    (Tags: rstats, BARUG, RUG)

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