Published: April 22, 2021
From the moment the earliest cases of the coronavirus were detected in the U.S., the ability to test for and track infection rates and cases has been one of the most significant tools in combatting the virus, and played an essential role in developing guidelines and policies to reduce its spread. And today, testing paired with increasing access to vaccines, continues to play an important role in our gradual reopening and return to normal.
To take a look back over the types of testing, their levels of accuracy, how they developed and their impact, I am pleased to welcome my guests for today’s episode, Kimon Drakopoulos and Ramandeep Randhawa, both professors with the department of data sciences and operations, Marshall School of Business at the University of Southern California. We will be discussing their study, “Why Perfect Tests May Not be Worth Waiting for: Information as a Commodity,” which took place during the pandemic and will be published in the INFORMS journal Management Science.
This hesitation in getting tested because of whether you will have a false positive or a false negative, this is something that really motivated us to try and understand how people react, or how this would impact their ability to take tests. So one aspect is how easy it is to get tested from a pure operational perspective, the wait times, things like that. But then how do people react to all these factors, especially the accuracy of tests? That was something that really motivated us to look into this more carefully.
Interviewed this episode:
Kimon Drakopoulos and Ramandeep Randhawa
Marshall School of Business at the University of Southern California
Kimon Drakopoulos is an Assistant Professor in the Data Sciences and Operations department at USC Marshall School of Business. His research focuses on the operations of complex networked systems, social networks, stochastic modeling, game theory and information economics. Kimon, prior to joining USC, completed his PhD at the Laboratory for Information and Decision systems at MIT focusing on the analysis and control of contagion processes on networks.
Ramandeep S. Randhawa is an operations research scholar whose research interests include designing service systems, revenue management, stochastic modeling, and mechanism and incentive design. His work has been published in journals that include Management Science, Manufacturing and Service Operations Management, and Operations Research. Prior to joining the Marshall School, he was a faculty member at the McCombs School of Business at the University of Texas.