JIANG Honglin, TONG Yixin, XU Ning, ZHOU Yibiao, JIANG Qingwu. False positives of screening in large-scale population with low infection rate of an infectious diseasea: a modeling analysis[J]. Shanghai Journal of Preventive Medicine, 2022, 34(4): 314-317. DOI: 10.19428/j.cnki.sjpm.2022.22018
Citation: JIANG Honglin, TONG Yixin, XU Ning, ZHOU Yibiao, JIANG Qingwu. False positives of screening in large-scale population with low infection rate of an infectious diseasea: a modeling analysis[J]. Shanghai Journal of Preventive Medicine, 2022, 34(4): 314-317. DOI: 10.19428/j.cnki.sjpm.2022.22018

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

  • Objective To explore the positive predictive value (PPV) and false positive (FP) number of screening test in mass testing when the prevalence of infection is low.
    Methods Assuming 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%).
    Results For 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 <1.0%, the maximum PPV is only about 90.0%. When the infection rate is 0.1%, a screening test with more than 99.0% sensitivity could detect about 20 thousand TP cases in a population of 20 million. Additionally, the FP and PPV are estimated to be 599 thousand and 3.2% if the specificity is 97.0%, and 20 thousand and 50.0% if the specificity is 99.9%. When the infection rate is 1.0%, a screening test with ≥99.0% sensitivity and ≥97.0% specificity could detect about 0.198‒0.200 million TP cases; and the number of FP decreases from 594 thousand to 20 thousand when the specificity increases from 97.0% to 99.9%. When the infection rate is 5.0%, a screening test with ≥99.0% sensitivity and ≥97.0% specificity could detect about 0.99‒1.00 million TP cases; and the number of FP decreases from 570 thousand to 19 thousand when the specificity increases from 97.0% to 99.9%. When the infection prevalence is ≤5.0% in a total population of 20 million, there are about 20,000 FP cases even if the sensitivity and specificity reach the maximum values of 100.0% and 99.9%, respectively.
    Conclusion When the population is large and the infection prevalence is low, in addition to improving the specificity of the screening test in mass testing, the problem of a large number of false positives cannot be ignored.
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