OPINION: Rethinking Covid-19 Test Sensitivity — A Strategy for Containment

Rethinking Covid-19 Test Sensitivity — A Strategy for Containment | NEJM Perspective from The New England Journal of Medicine — Rethinking Covid-19 Test Sensitivity — A Strategy for Containment New England Journal of Medicine

It’s time to change how we think about the sensitivity of testing for Covid-19. The Food and Drug Administration (FDA) and the scientific community are currently almost exclusively focused on test sensitivity, a measure of how well an individual assay can detect viral protein or RNA molecules. Critically, this measure neglects the context of how the test is being used. Yet when it comes to the broad screening the United States so desperately needs, context is fundamental. The key question is not how well molecules can be detected in a single sample but how effectively infections can be detected in a population by the repeated use of a given test as part of an overall testing strategy — the sensitivity of the testing regimen.

A regimen of regular testing works as a sort of Covid-19 filter, by identifying, isolating, and thus filtering out currently infected persons, including those who are asymptomatic. Measuring the sensitivity of a testing regimen or filter requires us to consider a test in context: how often it’s used, to whom it’s applied, when in the course of an infection it works, and whether its results are returned in time to prevent spread.^1-3

Thinking about impact in terms of repeated uses is a familiar concept to clinicians and regulatory agencies; it’s invoked every time we measure the efficacy of a treatment regimen rather than a single dose. With Covid-19 cases accelerating or plateauing throughout much of the world, we urgently need to shift our attention from a narrow focus on the analytic sensitivity of a test (the lower limit of its ability to correctly detect small concentrations of molecules in a sample) to the more relevant measure of a testing regimen’s sensitivity to detect infections (the probability that infected persons learn they’re infected in time to be filtered out of the population and prevent spread to others). A point-of-care test that was inexpensive enough to use frequently would have a high sensitivity for detecting infections in time to act, without having to meet the benchmark analytic limit of detection (see diagram).

The tests we need are fundamentally different from the clinical tests currently being used, and they must be evaluated differently. Clinical tests are designed for use with symptomatic people, do not need to be low-cost, and require high analytic sensitivity to return a definitive clinical diagnosis given a single opportunity to test. In contrast, tests used in effective surveillance regimens intended to reduce the population prevalence of a respiratory virus need to return results quickly to limit asymptomatic spread and should be sufficiently inexpensive and easy to execute to allow frequent testing — multiple times per week. ...