A couple years ago I started becoming obsessed with the opioid epidemic. I spend a non-trivial amount of my time thinking about it and if I am ever scrambling for a topic in a social situation, it ends up being pretty much the only thing I can think of. (Because I am So Smooth.) As a public health devotee, the epidemic hits all of my passions. To name just a few: Issue exacerbated by outdated stigma? Check. Multiple demographics impacted? Big time. Heartbreaking narratives? You will never stop crying. Socioeconomic confounders? And how.
Recently, alarm over the epidemic has reached such a fever pitch that various agencies have started hosting opioid-crisis-focused datathons/codathons/hackathons. (Three different new words for essentially the same concept does seem a little excessive, I agree.)
Being a data scientist is pretty much the coolest thing, and the world seems to have caught on to this fact. This means that there is more competition to do the really interesting work, but it also means that there is a critical mass of data scientists who will be interested in sciencing together for a marathon period (24 hours straight at least) on particular topics in our personal time. I love attending them. They are a great opportunity to build less-exercised skills through a sudden flood of experience hours. So, you can just imagine how I feel about getting access to new opioid epidemic data as part of a hackathon. To spell it out: Teamwork + Opioid Epidemic + Data + Hackathon = G.O.A.T.
I have participated in 2 Opioid Hackathons in the past 6 months, and I and some of my coworkers are planning one of our own, sponsored by our company. One of my kick-ass data science colleagues, Catherine Ordun, submitted our results for these events in an abstract to the International Society for Disease Surveillance (ISDS) Conference in Orlando this year, and we are presenting tomorrow! I’ll be back to post more about the topic (unless I take another 3 year hiatus, obvi.)