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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