False positives of screening in large-scale population with low infection rate of an infectious diseasea： a modeling analysis

ObjectiveTo explore the positive predictive value （PPV） and false positive （FP） number of screening test in mass testing when the prevalence of infection is low.MethodsAssuming a population of 20 million with the prevalence of disease infection ranging from 0.1% to 5.0%， PPV， true positive （TP） and FP numbers were calculated under different scenarios of combination of sensitivity （99.0%， 99.5%， and 100.0%） with specificity （97.0%， 97.5%， 98.0%， 98.5%， 99.0%， 99.5%， and 99.9%）.ResultsFor low infection prevalence （≤5.0%）， specificity has a greater impact on PPV than sensitivity； with the decrease of infection prevalence， the increase in PPV elevates when the specificity increases. When the infection prevalence is >1.0%， the closer the specificity is to 99.9%， the closer the PPV is to 100.0%. However， when the infection prevalence is