Related Experiment Video
Updated: Dec 20, 2025

Alternative In Vitro Methods for the Determination of Viral Capsid Structural Integrity
Published on: November 16, 2017
Can Use of Viral Load Improve Norovirus Clinical Diagnosis and Disease Attribution?
Kayoko Shioda1, Leslie Barclay1, Sylvia Becker-Dreps2
1Division of Viral Diseases, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia.
Background:
Real-time reverse-transcriptase polymerase chain reaction (RT-PCR) is the state-of-the-art diagnostic for norovirus. Cycle threshold (Ct), an indicator of viral load, may be associated with symptomatic disease as well as demographic and outbreak characteristics.
Methods:
Data on (1) outbreak and sporadic cases and (2) asymptomatic controls in the United States and Latin America were analyzed. With multivariate regression models, we assessed relationships between various factors and Ct values, and we calculated odds ratios (ORs) for the presence of symptoms and attributable fractions of norovirus. Receiver-operating characteristic analysis was performed to define an optimal Ct cutoff to identify disease-causing infections.
Results:
Cycle threshold values were lower (ie, higher viral loads) among symptomatic cases (model-adjusted mean ± standard error: 25.3 ± 1.2) compared with asymptomatic controls (28.5 ± 1.4). Cycle threshold values were significantly different across age groups, norovirus genogroups, timing of specimen collection, outbreak settings, and transmission modes. Genogroup II (GII) Ct values were associated with presence of symptoms (OR = 1.1), allowing us to estimate that 16% of diarrheal disease was attributable to norovirus. The optimized Ct cutoff led to poor sensitivity and specificity for genogroup I and GII.
Conclusions:
Cycle threshold values were associated with host, pathogen, and outbreak factors. Cycle threshold values may not effectively distinguish disease-causing infection for individual patients, but they are useful for epidemiological studies aiming to attribute disease.

