Is "no test is better than a bad test"? Impact of diagnostic uncertainty in mass testing on the spread of COVID-19

Gray, Nicholas and Calleja, Dominic and Wimbush, Alexander and Miralles-Dolz, Enrique and Gray, Ander and De Angelis, Marco and Derrer-Merk, Elfriede and Oparaji, Bright Uchenna and Stepanov, Vladimir and Clearkin, Louis and Ferson, Scott (2020) Is "no test is better than a bad test"? Impact of diagnostic uncertainty in mass testing on the spread of COVID-19. PLoS ONE, 16 (2). e0247129. ISSN 1932-6203 (

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Testing is viewed as a critical aspect of any strategy to tackle epidemics. Much of the dialogue around testing has concentrated on how countries can scale up capacity, but the uncertainty in testing has not received nearly as much attention beyond asking if a test is accurate enough to be used. Even for highly accurate tests, false positives and false negatives will accumulate as mass testing strategies are employed under pressure, and these misdiagnoses could have major implications on the ability of governments to suppress the virus. The present analysis uses a modified SIR model to understand the implication and magnitude of misdiagnosis in the context of ending lockdown measures. The results indicate that increased testing capacity alone will not provide a solution to lockdown measures. The progression of the epidemic and peak infections is shown to depend heavily on test characteristics, test targeting, and prevalence of the infection. Antibody based immunity passports are rejected as a solution to ending lockdown, as they can put the population at risk if poorly targeted. Similarly, mass screening for active viral infection may only be beneficial if it can be sufficiently well targeted, otherwise reliance on this approach for protection of the population can again put them at risk. A well targeted active viral test combined with a slow release rate is a viable strategy for continuous suppression of the virus.