Additional file 1 of COVID-19 prevalence estimation by random sampling in population - optimal sample pooling under varying assumptions about true prevalence

Additional file 1 : Supplementary Table 1. Table containing prevalence estimates and, the estimated required number of tests, and the expected proportion incorrectly classified patients for all parameter combinations. Se = sensitivity. Sp = specificity. N = number of samples. k = pooling level. P = true prevalence. p 2.5%, p 50.0%, p 97.5% = 2.5, 50 and 97.5 quantile of estimated prevalence. T 2.5%, T 50.0%, T 97.5% = 2.5, 50 and 97.5 quantile of estimated number of tests required to get individual-level diagnoses. E(S) = Expected number of tests saved when compared to testing individually for this N. E(inc) = Expected percentage of patients that are diagnosed incorrectly at this parameter combination. [Excel file].