WG/GLIMPRINT Seminars: Barhak, Lessons Learned from Modeling COVID-19: Part 2, January 22, 2026 скачать в хорошем качестве

WG/GLIMPRINT Seminars: Barhak, Lessons Learned from Modeling COVID-19: Part 2, January 22, 2026

Lessons Learned from Modeling COVID-19: Steps to Take at the Start of the Next Pandemic: Part 2 Jacob Barhak, PhD This episode in the new GLIMPRINT subseries “Lessons Learned from Modeling COVID” continues the conversation initiated in Jacob Barhak’s earlier seminar on Lessons Learned from Modeling COVID-19: Steps to Take at the Start of the Next Pandemic (July 10, 2025). Building on that foundation, the follow-on discussion focuses on how we disseminate modeling information to the public—including communicating uncertainty and limitations, tracing data and assumptions for reproducibility, and addressing errors transparently to strengthen trust. Participants also revisit practical infrastructure needs (e.g., durable public data repositories, version control, and scalable computing) and the role of ensemble/agent-based approaches in moving from “forecasting” toward better explanations that can support preparedness and decision-making in future outbreaks. For the first part of this discussion see: Lessons Learned from Modeling COVID-19: Steps to Take at the Start of the Next Pandemic, Part 1 https://youtube.com/live/ww1_xH3WSwc To learn more, see: Lessons Learned from Modeling COVID-19: Steps to Take at the Start of the Next Pandemic: https://www.preprints.org/manuscript/... Presentation to MIDAS:    • MIDAS Webinar Series March 2025 - Jacob Ba...   Contents 00:00 - Introduction 04:40 - Lessons Learned from Modeling COVID-19, Part 2. Presentation by Jacob Bahrak and Discussion Moderated by: James A. Glazier and Tomas Helikar If you found this video useful, please check out our other videos on computational modeling, infection and immunology:    • IMAG/MSM WG and GLIMPRINT Seminars on Mult...   Please consider joining our IMAG/MSM WG on Multiscale Modeling and Viral Pandemics: https://www.imagwiki.nibib.nih.gov/co... Please also consider joining the Global Alliance for Immune Prediction and Intervention: http://glimprint.org/