ISSUE: The COVID-19 global pandemic is an unprecedented public health challenge requiring significant resources to evaluate the problem and determine the best solutions from a health and economic perspective. Much of the decision making related to COVID-19 have been centered around prevention, which requires forecasting. This issue panel will discuss the data and modeling needs for policy makers, health care decision makers, and the average US resident for the COVID-19 pandemic, specifically, with blue sky considerations for a non-specific future pandemic.

OVERVIEW: This panel will discuss the modeling and real-time data needs to support good decision making during the COVID-19 global pandemic. The panel will consider past challenges in data collection and forecasting, and the solutions that were used, as well as remaining challenges. The panel will also debate the role of the scientist in communicating critical data to decision makers at all levels of government and health system. Ms. Chou will moderate and provide an overview of the pandemic from a US perspective as well as a framework for thinking through the data and modeling challenges for COVID-19. Dr. Karaca Mandic will describe the challenges with real-time data collection and interpretation with the University of Minnesota COVID-19 Hospitalization Tracking Project. Dr. Singh will review advanced modeling techniques that have been or could be implemented in supporting COVID-19 decision making. Finally, Dr. Waller will describe his efforts relating to assessing inequity in spatial access to testing sites between racial and ethnic groups in Atlanta, Georgia. After a 6 minute introduction from the moderator, each panelist will present for approximately 8 minutes, reserving 30 minutes for a moderated Q/A discussion, with the option for attendees to submit questions to the panel.