Estimating SARS-CoV-2 seroprevalence and epidemiological parameters with uncertainty from serological surveys

Daniel B Larremore; Bailey K Fosdick; Kate M Bubar; Sam Zhang; Stephen M Kissler; C. Jessica E. Metcalf; Caroline Buckee; Yonatan Grad

To illustrate the use of these calculations in practice, we first simulated serological data from populations with seroprevalence rates ranging from 1% to 50% using the reported sensitivity (93%) and specificity (97.5%) of a test approved for sale in the EU (Supplementary Table S1 ), and with the number of samples ranging from 100 to 5000. Next, we constructed Bayesian posterior estimates of seroprevalence (see Methods), finding that, when seroprevalence is 10% or lower, around 1000 samples are necessary to estimate seroprevalence to within two percentage points (Fig. 2) . Tests with other characteristics required around 1000 tests (93.8% sensitivity, 97.5% specificity; Supplementary Fig. S1A ) and 750 tests (97.2% sensitivity and 100% specificity; Supplementary Fig. S1B ) to achieve the same uncertainty levels, relative to the minimum of around 650 tests for a theoretical test with perfect sensitivity and specificity ( Supplementary Fig. S1C ).