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Table 2 Formulæ employed to calculate outcomes of applying a one- or two-test diagnostic strategy to a population of 10,000 individuals with several prevalences of infections

From: One or two serological assay testing strategy for diagnosis of HBV and HCV infection? The use of predictive modelling

One-Test Strategy Two-Test Strategy
TP1= N x E x SenA TP2 = TP1 x SenB
TN1 = (N x (1 – E)) – (N x (1 – E) x (1 – SpecA)) TN2 = TN1 + (FP1 x SpecB)
FP1 = N x (1 – E) x (1 – SpecA) FP2 = FP1 x (1 – SpecB)
FN1 = N x E x (1 – SenA) FN2 = FN1 + (TP1 x (1 – SenB))
PPV1 = TP1 / (TP1 + FP1) PPV2 = TP2 / (TP2 + FP2)
NPV1 = TN1 / (TN1 + FN1) NPV2 = TN2 / (TN2 + FN2)
POR1 = TP1 / FP1 POR2 = TP2 / FP2
  1. N Population size, E Prevalence of infection, TP True positive, SenA Assay A sensitivity, SpecA Assay A specificity, TN True negatives, SenB Assay B sensitivity, SpecB Assay B specificity, FP False positives, PPV Positive predictive value, FN False negatives, NPV Negative predictive value, POR Ratio of true to false positive tests