The MIDAS Webinar Series features research by MIDAS members, and is open to the public.
Date: Friday, March 28, 2025
Speaker: Dr. Jacob Barhak
Title: Lessons Learned from Modeling COVID-19: Steps to Take at the Start of the Next Pandemic
Abstract: This is joint work with: Christin Glorioso, Filippo Castiglione, Kayode Oshinubi, Aviral Chharia
The COVID-19 pandemic spurred many computational modeling efforts. Many mistakes were made and many lessons were learned. This study attempts to list the key lessons learned from a modeling perspective, highlighting both the successes and shortcomings observed during the pandemic. Additionally, this work attempts to compile a set of critical steps and best practices that the authors believe would prove helpful and should be implemented before the start of the next pandemic to avoid inaccuracies in modeling pandemic scenarios. This will help to improve preparedness and ensure that computational models can more effectively guide decision-making in future pandemics.
The manuscript behind this talk can be accessed here: https://doi.org/10.20944/preprints202411.2193.v1
Bio: Jacob Barhak is an independent Computational Disease Modeler focusing on machine comprehension of clinical data. The Reference Model for disease progression is patented technology that was self developed by Dr. Barhak. The Reference model is the most validated Diabetes model known worldwide and also the first COVID-19 multi-scale ensemble model. His efforts also include standardizing clinical data through ClinicalUnitMapping.com and he is the developer of the Micro Simulation Tool (MIST). Dr. Barhak has a diverse international background in engineering and computing science. He is active within the python community and organizes the Austin & DC Evening of Python Coding meetup. For additional information please visit https://sites.google.com/view/jacob-barhak/home