ISSUE: The COVID-19 pandemic has highlighted many challenges for HEOR modelers, but these challenges are not necessarily new. The need for modeling to be responsive to fast-paced changes in technology, treatments and care delivery made accurate and timely modeling of critical outcomes difficult. Borrowing modeling theories and methods from population biology may offer a new direction for rigorous and timely value assessment.

OVERVIEW: This panel will discuss the challenges associated with existing modeling, slow adaptiveness in data collection and forecasting techniques, which are being used to support decision making during the COVID-19 global pandemic and why health decision analysis tools may have become less effective in responding to COVID-19 problems. We will consider well-established modeling solutions from population biology to determine their applicability to address future challenges of healthcare systems at multiple scales from micro level treatment implications within patients to long term impact on quality of life and societal economics. Such multi-scale modeling would represent a fundamental shift in how health and medical research are approached. Dr. Mubayi will moderate and provide an overview of the health modeling as well as a framework for thinking through the data and modeling challenges being learned during current COVID-19 pandemic. Dr. Meltzer will describe answers from ecology of infectious diseases to those challenges that may be useful to use them as an input to healthcare modeling methods. Dr. Townsend will review advanced modeling techniques from population biology that have been or could be implemented in supporting COVID-19 decision making. Finally, Dr. Hyman will describe efforts relating to assessing population dynamics tools for value assessment that can adapt in real time using continuously changing empirical information for evaluating health technologies. After 5 minutes of introduction from the moderator, each panelist will present for approx 8 minutes, reserving 30 minutes for Q/A discussion.