Figure - PMC

Skip to main content

An official website of the United States government

Here's how you know

Here's how you know

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

View full-text article in PMC

. 2021 Feb 25;36(2):179–196. doi: 10.1007/s10654-021-00727-7

Search in PMC
Search in PubMed
View in NLM Catalog
Add to search

© The Author(s) 2021

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

PMC Copyright notice

Fig. 3 — The relative importance of test sensitivity and specificity depends on the underlying seroprevalence in the study population. The value of a test can be described through the positive predictive value (PPV), which is defined as the probability that an individual truly has been infected with the virus given that they test positive and is calculated as the number of true positives divided by the total number of positive tests. Similarly, the negative predictive value (NPV) is defined as the probability that an individual truly has not been infected with the virus given that they test negative and is calculated as the number of true negatives divided by the total number of negative tests. When the underlying seroprevalence is low, test performance is largely a function of specificity, as the majority of individuals in the population have not been infected, while sensitivity is more important as seroprevalence increases. Note that the negative predictive values for the baseline and low specificity tests are very similar so the curves nearly overlap in the figure