Published on Thu Nov 12 2020

Age-Specific SARS-CoV-2 Infection Fatality and Case Identification Fraction in Ontario, Canada

Fisman, D., Drews, S. J., Tuite, A., O'Brien, S.

SARS-CoV-2 is a novel pandemic pathogen that displays great variability in virulence across cases. Due to limitations in diagnostic testing only a subset of infections are identified. Underestimation of true infections makes calculation of infection fatality ratios (IFR) challenging. We estimated that 5.88 infections occurred for every case identified.

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Abstract

BackgroundSARS-CoV-2 is a novel pandemic pathogen that displays great variability in virulence across cases. Due to limitations in diagnostic testing only a subset of infections are identified. Underestimation of true infections makes calculation of infection fatality ratios (IFR) challenging. Seroepidemiology allows estimation of true cumulative incidence of infection in populations, for estimation of IFR. MethodsSeroprevalence estimates were derived using retention samples stored by Canadian Blood Services in May 2020. These were compared to non-long-term care-linked case and fatality data from the same period. Estimates were combined to generate IFR and case identification fraction estimates. ResultsOverall IFR was estimated to be 0.80% (0.75 to 0.85%), consistent with estimates from other jurisdictions. IFR increased exponentially with age from 0.01% (0.002 to 0.04%) in those aged 20-29 years, to 12.71% (4.43 to 36.50%) in those aged 70 and over. We estimated that 5.88 infections (3.70 to 9.21) occurred for every case identified, with a higher fraction of cases identified in those aged 70 and older (42.0%) than those aged 20-29 (9.4%). IFR estimates in those aged 60 and older were identical to pooled estimates from other countries. ConclusionsTo our knowledge these are the first Canadian estimates SARS-CoV-2 IFR and case identification fraction. Notwithstanding biases associated with donor sera they are similar to estimates from other countries, and approximately 80-fold higher than estimates for influenza A (H1N1) during the 2009 epidemic. Ontarios first COVID-19 pandemic wave is likely to have been accurately characterized due to a high case identification fraction.