Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

COVID-19 Testing – Impact of Prevalence, Sensitivity, and Specificity on Patient Risk and Cost

Version 1 : Received: 18 June 2020 / Approved: 21 June 2020 / Online: 21 June 2020 (15:12:43 CEST)
Version 2 : Received: 7 July 2020 / Approved: 9 July 2020 / Online: 9 July 2020 (15:57:30 CEST)

How to cite: Brooks, Z.C.; Das, S. COVID-19 Testing – Impact of Prevalence, Sensitivity, and Specificity on Patient Risk and Cost. Preprints 2020, 2020060279 (doi: 10.20944/preprints202006.0279.v1). Brooks, Z.C.; Das, S. COVID-19 Testing – Impact of Prevalence, Sensitivity, and Specificity on Patient Risk and Cost. Preprints 2020, 2020060279 (doi: 10.20944/preprints202006.0279.v1).

Abstract

Since the beginning of the year 2020, the global healthcare system has been challenged by the threat of the SARS-COV 2 virus. Molecular, antigen, and antibody testing are the mainstay to identify infected patients and fight the virus. Molecular and antigen tests that detect the presence of the virus are relevant in the acute phase only. Serological assays detect antibodies to the Sars-CoV-2 virus in the recovering and recovered phase. Each testing methodology has its advantages and disadvantages. To evaluate the test methods, sensitivity (percent positive agreement - PPA) and specificity (percent negative agreement – PNA) are the most common metrics utilized, followed by the positive and negative predictive value (PPV and PNV), the probability that a positive or negative test result represents a true positive or negative patient. In this paper, we illustrate how patient risk and clinical costs are driven by false-positive and false-negative results. We demonstrate the value of reporting PFP (probability of false positives), PFN (probability of false negatives), and costs to patients and healthcare. These risk metrics can be calculated from the risk drivers of PPA and PNA combined with estimates of prevalence, cost, and Reff number (people infected by one positive SARS COV-2).

Subject Areas

COVID19; risk; clinical; metrics; cost; false-positive; false-negative; prevalence; sensitivity; specificity

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