A Retrospective Look at Covid-19 Testing Performance

Research Mentor(s)

Kimihiro Noguchi

Description

In this research paper, we analyzed the sensitivity (the likelihood that those with the disease will test positive), specificity (the likelihood that those without the disease will test negative), and prevalence values of the Covid-19 testing procedures. We use a set of different sensitivity and specificity values with a reasonable range of prevalence values to evaluate the test’s performance in terms of positive predictive value (PPV) and negative predictive value (NPV). The disease prevalence has a significant impact on the sensitivity and specificity values necessary for high PPV and NPV. With a prevalence of less than 0.01, it would be unrealistic to require a specificity value high enough to achieve a strong PPV.

Document Type

Event

Start Date

May 2022

End Date

May 2022

Location

Carver Gym (Bellingham, Wash.)

Department

CSE - Mathematics

Genre/Form

student projects; posters

Type

Image

Rights

Copying of this document in whole or in part is allowable only for scholarly purposes. It is understood, however, that any copying or publication of this document for commercial purposes, or for financial gain, shall not be allowed without the author’s written permission.

Language

English

Format

application/pdf

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May 18th, 9:00 AM May 18th, 5:00 PM

A Retrospective Look at Covid-19 Testing Performance

Carver Gym (Bellingham, Wash.)

In this research paper, we analyzed the sensitivity (the likelihood that those with the disease will test positive), specificity (the likelihood that those without the disease will test negative), and prevalence values of the Covid-19 testing procedures. We use a set of different sensitivity and specificity values with a reasonable range of prevalence values to evaluate the test’s performance in terms of positive predictive value (PPV) and negative predictive value (NPV). The disease prevalence has a significant impact on the sensitivity and specificity values necessary for high PPV and NPV. With a prevalence of less than 0.01, it would be unrealistic to require a specificity value high enough to achieve a strong PPV.