Speaker: Jacob Barhak
The Reference Model for disease progression was initially a diabetes model. It used the approach of assembling models and validating them against different populations from clinical trials.
The model performs simulation at the individual level while modeling entire populations using the MIcro-Simulation Tool (MIST), employing High Performance Computing (HPC), and using machine learning techniques to combine models.
The Reference Model technology was transformed to model COVID-19 near the start of the epidemic. The model is now composed of multiple models from multiple contributors that represent different phenomena: It includes infectiousness models, transmission models, human response / behavior models, hospitalization models, mortality models, and observation models. Some of those models were calculated at different scales including cell scale, organ scale, individual scale, and population scale.
The Reference Model has therefore reached the achievement of being the first known multi-scale ensemble model for COVID-19. This project is ongoing and this presentation is constantly updated for each venue. To access the most recent publication please use this link
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 Evening of Python Coding meetup. For additional information please visit
