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

Each of the graphs in the two figures shows the effect of different prevalences of antibodies in the population. To be clear, this is the proportion of the population that has contracted the virus and recovered but are in quarantine. Sir Patrick Vallance, the UK Government Chief Scientific Advisor, in the daily press briefing on the 9 April 2020 stated his belief that this prevalence is likely to be less than 10%, possibly much less. The analysis has explored a range for prevalence from 0.1% to 50%. Figure 5 explores the impact of a variation in sensitivity, from a test with 50% sensitivity (i.e no diagnostic value) to tests with a high sensitivity of 98%. It can be seen, considering the top half of the graphs, that the sensitivity of the test has no discernible impact on the number of infections. The prevalence entirely dominates. This is possibly counter intuitive, but as was discussed in section 2.1, even a highly accurate test produces a very large number of false positives when prevalence is low. In this case that would mean a large number of people are allowed to re-enter the population, placing them at risk, with a false sense of security that they have immunity.