Gaining health policy insight with small data sets — Collecting large amounts of data is a prerequisite for training and testing supervised machine learning models and making predictions. However, using small amounts of data and simple, yet foundational, mathematical models in R, we can generate large insights that can inform policy to alleviate infectious disease threats. …

Fitting distributions can be a challenging task for any data science, simulation, or modelling effort. In the back of your mind, you will always wonder if you truly found the best fitting distribution to describe your data. Recently, I stumbled upon an incredibly simple-to-use and helpful Python package designed to…

The new year brings many joys; one of the foremost of which is the NFL Playoffs. However, the end of the regular season marks the end of the fantasy football season, the end of hilarious memes, and the end of fantasy league smack talk until September. This year as league…

The COVID-19 pandemic brought the importance of infectious disease modeling to the forefront of our lives. I first became interested in infectious disease models in my undergraduate studies around the time the 2014 Ebola outbreak was raging through West Africa. I saw infectious disease modeling as the perfect way to…