Interpreting SARS-CoV-2 Diagnostic Tests: Common Questions and Answers

Understanding SARS-CoV-2 test performance is essential for managing the pandemic. Prior research has established that diagnostic tests can detect active infection, but uncertainty remains about how to interpret results in different clinical and epidemiological contexts. It was already known that molecular tests are highly specific, but their sensitivity varies. No prior work had resolved how to integrate test performance with clinical judgment and local disease prevalence. This gap motivated a review of test characteristics and interpretation strategies. That uncertainty drove the need to clarify when a negative test might still indicate infection. Researchers propose that test timing and pretest probability are critical factors. The challenge lies in balancing test limitations with clinical decision-making. No prior work had clearly explained how to use a leaf plot for posttest probability estimation.

This review aims to clarify how to interpret SARS-CoV-2 diagnostic and antibody tests in clinical and public health settings. The specific problem is the variability in test performance and the need to contextualize results with patient-specific and population-level factors. The motivation stems from the limitations of relying solely on test results for diagnosis or immunity inference. The study focuses on molecular and antigen tests for current infection and antibody tests for past infection. It addresses how test sensitivity and specificity affect diagnostic accuracy. The review considers how pretest probability influences posttest interpretation. The goal is to guide clinicians in using test results alongside clinical judgment. The study does not propose new tests but evaluates existing ones for diagnostic and screening use.

The review approach includes synthesizing evidence on test characteristics and interpretation strategies. The authors analyze molecular and antigen tests for detecting active SARS-CoV-2 infection. They evaluate antibody tests for identifying past infection. The study considers test timing in relation to symptom onset and disease progression. The analysis includes pretest probability factors such as exposure history and local prevalence. The authors use a leaf plot to illustrate how test sensitivity and specificity affect posttest probability. They compare diagnostic and antibody tests for their roles in managing patients and public health. The review does not include new data but compiles existing literature on test performance and interpretation.

Molecular and antigen tests have high specificity but differ in sensitivity. Antigen tests are more prone to false-negative results. Test timing relative to symptom onset affects diagnostic accuracy. Pretest probability should consider exposure, symptoms, and local prevalence. A leaf plot helps estimate posttest probability based on test characteristics. A negative test may not rule out infection if pretest probability is high. A symptom-based approach is preferred for ending isolation in most cases. Antibody tests may detect past infection but should not infer immunity or guide protective measures.

The authors synthesize evidence on interpreting SARS-CoV-2 diagnostic and antibody tests. They propose that test results should be considered alongside clinical judgment and pretest probability. Molecular tests are more reliable for ruling out infection than antigen tests. A negative test may still indicate infection if pretest probability is high. The review suggests using a leaf plot to estimate posttest probability. Antibody tests may detect past infection but should not be used to infer immunity. The authors emphasize a symptom-based approach for ending isolation. They conclude that diagnostic tests should not be the sole basis for clinical decisions.