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Updated: Jul 11, 2025

Two-Step Reverse Transcription Droplet Digital PCR Protocols for SARS-CoV-2 Detection and Quantification
Published on: March 31, 2021
Digital PCR to Measure SARS-CoV-2 RNA, Variants, and Outcomes in Youth
Diego R Hijano1,2, Jose A Ferrolino1, Zhengming Gu3
1Departments of Infectious Diseases, St. Jude Children's Research Hospital, Memphis, Tennessee, USA.
Background:
The role of SARS-CoV-2 viral load in predicting contagiousness, disease severity, transmissibility, and clinical decision-making continues to be an area of great interest. However, most studies have been in adults and have evaluated SARS-CoV-2 loads using cycle thresholds (Ct) values, which are not standardized preventing consistent interpretation critical to understanding clinical impact and utility. Here, a quantitative SARS-CoV-2 reverse-transcription digital PCR (RT-dPCR) assay normalized to WHO International Units was applied to children at risk of severe disease diagnosed with COVID-19 at St. Jude Children's Research Hospital between March 28, 2020, and January 31, 2022.
Methods:
Demographic and clinical information from children, adolescents, and young adults treated at St. Jude Children's Research Hospital were abstracted from medical records. Respiratory samples underwent SARS-CoV-2 RNA quantitation by RT-dPCR targeting N1 and N2 genes, with sequencing to determine the genetic lineage of infecting virus.
Results:
Four hundred and sixty-two patients aged 0-24 years (median 11 years old) were included during the study period. Most patients were infected by the omicron variant (43.72%), followed by ancestral strain (22.29%), delta (13.20%), and alpha (2.16%). Viral load at presentation ranged from 2.49 to 9.14 log10 IU/mL, and higher viral RNA loads were associated with symptoms (OR 1.32; CI 95% 1.16-1.49) and respiratory disease (OR 1.23; CI 95% 1.07-1.41). Viral load did not differ by SARS-CoV-2 variant, vaccination status, age, or baseline diagnosis.
Conclusions:
SARS-CoV-2 RNA loads predict the presence of symptomatic and respiratory diseases. The use of standardized, quantitative methods is feasible, allows for replication, and comparisons across institutions, and has the potential to facilitate consensus quantitative thresholds for risk stratification and treatment.
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