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Increasing COVID-19 Testing Capability through Pooled Testing


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by: Hyun-Soo Ahn

Publication Date: August 10, 2021
Length: 6 pages
Product ID#: 6-671-361

Core Disciplines: Economics, Operations Management/Supply Chain

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Description

One of the most significant challenges in tackling the COVID-19 pandemic in the United States was the shortage of test capability. At the beginning of April 2020, fewer than 200,000 tests per day were being performed, much less than public health experts had recommended. Also, in many cases, it often took several days or even weeks for a person to receive the test result. Many experts believed the testing turnaround time was one of the most significant failure points to contain COVID-19. Heading into fall 2020 and winter of 2021, U.S. healthcare experts continued to cite testing capability (and fast results) as the first necessary condition of getting back to everyday life. One solution to increase the testing capacity was called a pooled test.

In this case, the government of Ann Arbor is considering whether the city should use pooled COVID-19 testing and, if so, how the test should be designed since there are several different versions. Students are asked to apply probability theory and develop Excel models that can help decision makers.

Teaching Objectives

After reading and discussing the material, students should:

  • Carry out Excel modeling (extracting the information from data, building a decision model).
  • Understand and apply probability theory and random variables.
  • Grasp binomial distribution and Bayes’ rule.