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Updated: Oct 23, 2025

Simultaneous Quantification of T-Cell Receptor Excision Circles TRECs and K-Deleting Recombination Excision Circles KRECs by Real-time PCR
Published on: December 6, 2014
COVID-19 Case Age Distribution: Correction for Differential Testing by Age
David N Fisman1, Amy L Greer2, Gabrielle Brankston2
1Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada (D.N.F., A.R.T.).
Background:
Despite expected initial universal susceptibility to a novel pandemic pathogen like SARS-CoV-2, the pandemic has been characterized by higher observed incidence in older persons and lower incidence in children and adolescents.
Objective:
To determine whether differential testing by age group explains observed variation in incidence.
Design:
Population-based cohort study.
Setting:
Ontario, Canada.
Participants:
Persons diagnosed with SARS-CoV-2 and those tested for SARS-CoV-2.
Measurements:
Test volumes from the Ontario Laboratories Information System, number of laboratory-confirmed SARS-CoV-2 cases from the Integrated Public Health Information System, and population figures from Statistics Canada. Demographic and temporal patterns in incidence, testing rates, and test positivity were explored using negative binomial regression models and standardization. Sources of variation in standardized ratios were identified and test-adjusted standardized infection ratios (SIRs) were estimated by metaregression.
Results:
Observed disease incidence and testing rates were highest in the oldest age group and markedly lower in those younger than 20 years; no differences in incidence were seen by sex. After adjustment for testing frequency, SIRs were lowest in children and in adults aged 70 years or older and markedly higher in adolescents and in males aged 20 to 49 years compared with the overall population. Test-adjusted SIRs were highly correlated with standardized positivity ratios (Pearson correlation coefficient, 0.87 [95% CI, 0.68 to 0.95]; P < 0.001) and provided a case identification fraction similar to that estimated with serologic testing (26.7% vs. 17.2%).
Limitations:
The novel methodology requires external validation. Case and testing data were not linkable at the individual level.
Conclusion:
Adjustment for testing frequency provides a different picture of SARS-CoV-2 infection risk by age, suggesting that younger males are an underrecognized group at high risk for SARS-CoV-2 infection.
Primary Funding Source:
Canadian Institutes of Health Research.
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