No test is better than a bad test"": Impact of diagnostic uncertainty in mass testing on the spread of Covid-19

Nicholas Gray; Dominic Calleja; Alex Wimbush; Enrique Miralles-Dolz; Ander Gray; Marco De-Angelis; Elfride Derrer-Merk; Bright Uchenna Oparaji; Vladimir Stepanov; Louis Clearkin; Scott Ferson

A more concerning story can be seen when considering the graphs in figure 6 . Now we consider a range of antibody test specificities. Going from 50% (no value in ruling people out) to 98%. When the prevalence is low, a lower specificity of 75% not only leads to an initial large increase in the number of infections, but also, if employed throughout the year would lead to repeated peaks. This is because the active virus testing would still be employed along side the antibody testing. Falsely-diagnosed susceptible people leaving quarantine leads to a sharp rise in the number of infections. As the prevalence of virus in the non-quarantined population increases the active virus testing becomes more effective and subdues the rise in infections because the testing is more targeted on active virus cases. This would be followed by additional waves as further false positive tests for antibodies are observed. The number of people in quarantine with antibodies declines over the length of the simulation, so naturally the prevalence of immunity in the quarantined population declines. As the prevalence declines the N P V of the test declines.