COVID-19 Screening: Can Testing More People Flatten the Curve?
Introduction
I created this project for a class I took at UNM called Complex Adaptive Systems by Melanie Moses. The course was fantastic! It just so happens that one of the topics of this class was the complexities of viruses and epidemic spread. Little did I know that a global pandemic was literally around the corner. When COVID-19 started to change the world, I was taking a class that pushed me to study it with more detail than I otherwise would.
At this time, no one understood anything about this virus. There were many people performing research on the topic. Almost none of it was peer-reviewed, so we built a research paper based on outstanding research, but ultimately no one knew the truth. At the time, the term asymptomatic was spreading across society. It was in everyone’s vocabulary. This idea of an asymptomatic sick person spreading SARS-COV-2 was something my research partner, Anas Gauba, and I wanted to explore in detail. We knew we needed some Agent-Based Model (ABM) to explore these questions. While there exist some software packages made to build ABM’s, we decided to build one from scratch using Java.
Using our own ABM, we explored the question: Can Testing More People Flatten the Curve?
