Comparing epidemics

n all likelihood, the US will end up with more (direct) deaths from COVID-19 than the “opioid epidemic” since 1999. Using the CDC WONDER data for opioid deaths and the NYTimes data for COVID-19, I show the cumulative deaths (y-axis) from all opioids (blue) and from COVID (red) over time (x-axis).

Things to consider before applying for a K99/R00

t officially looks like I’ll be awarded a K99/R00 (!!). The application process was a long, overwhelming slog — only possible with the generous support of mentors, colleagues, friends, and strangers. Here, I will try to pay it forward by sharing some thoughts and advice. There are plenty of good blog posts about applying for K99’s, so I’ll try to avoid repeating those. Instead, I’m going to focus on things I didn’t know before and/or didn’t read elsewhere. It will be based on (1) insight from others who applied, (2) advice from mentors of successfully funded applicants, and (3) my …

Looking at opioid-related mortality, by race, 1979 to 2016

ur paper (with Monica Alexander and Magali Barbieri) is out now (in published ahead-of-print form). Monica has a great, short Twitter thread on the findings so if you don’t want to read the whole thing, check that out. The publisher’s PDF is here. After submitting our paper, the NCHS released the 2016 multiple cause of death files — so a couple months ago we were curious to see how (or if) our results would change when adding the 2016 data. [NOTE (2/25/2019): Since this post, the 2017 data have also been released. I did a similar analysis comparing our original …

Shiny + deSolve = Interactive ODE Models

hile taking a disease dynamics course, I thought it would be a good opportunity to learn how to use the Shiny package in R and create an interactive interface for some of my problem sets. After a few trial runs with smaller, simpler setups, I have wrapped up the side project (for now). You can see it in action here 1 and you can view the final code on my Git. Show 1 footnote  Updated 02/13/15 — moved to ↩