Why Mandatory Mass Testing for COVID-19 is a Poor Policy

Alexander Maslov
Central Michigan University, Mount Pleasant, USA, This email address is being protected from spambots. You need JavaScript enabled to view it.

Journal of Economic Regulation, 2020, Vol. 11 (no. 4),

p. 57-63
DOI: 10.17835/2078-5429.2020.11.4.057-063

In this note I describe simple logic behind COVID-19 mass testing, which explains why any underlying policy is economically unsubstantiated. The application of basic probability theory shows that unless the testing accuracy is close to a hundred percent, even a small number of false positives introduces significant bias into random tests making them extremely unreliable, which is further aggravated by the presence of false negatives. For example, at 5% false positive rate, for a random person living in the USA without any symptoms or previous contact with infected people, the likelihood of actually having COVID-19 after testing positive is only 32.63%. This probability increases with lower false positive rates and higher infection rates. Still, at 3% false positive rate, a randomly selected person only in 12 states will have a probability higher than 50% (up to 56%) of having COVID-19 after testing positive. Assuming independence of tests, in some states (e.g. Vermont) a person who has no reason to suspect the disease may need to test a dozen times to make sure that he/she is actually sick.

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Keywords: COVID-19; Medical Testing; Public Policy

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Publisher: Ltd. "Humanitarian perspectives"
Founder: Ltd. "Humanitarian perspectives"
Online ISSN: 2412-6047
ISSN: 2078-5429