Estimating the Under-ascertainment of COVID-19 cases in Toronto, Ontario, March to May 2020

Binyam N Desta; Sylvia Ota; Effie Gournis; Sara M Pires; Amy L Greer; Warren Dodd; Shannon E Majowicz

doi:10.1177/22799036231174133

Estimating the Under-ascertainment of COVID-19 cases in Toronto, Ontario, March to May 2020

J Public Health Res. 2023 May 12;12(2):22799036231174133. doi: 10.1177/22799036231174133. eCollection 2023 Apr.

Authors

Binyam N Desta¹, Sylvia Ota², Effie Gournis², Sara M Pires³, Amy L Greer⁴, Warren Dodd¹, Shannon E Majowicz¹

Affiliations

¹ School of Public Health Sciences, University of Waterloo, Waterloo, ON, Canada.
² Toronto Public Health, Toronto, ON, Canada.
³ Risk-Benefit Research Group, Technical University of Denmark, Lyngby, Denmark.
⁴ Department of Population Medicine, University of Guelph, Guelph, ON, Canada.

Abstract

Background: Public health surveillance data do not always capture all cases, due in part to test availability and health care seeking behaviour. Our study aimed to estimate under-ascertainment multipliers for each step in the reporting chain for COVID-19 in Toronto, Canada.

Design and methods: We applied stochastic modeling to estimate these proportions for the period from March 2020 (the beginning of the pandemic) through to May 23, 2020, and for three distinct windows with different laboratory testing criteria within this period.

Results: For each laboratory-confirmed symptomatic case reported to Toronto Public Health during the entire period, the estimated number of COVID-19 infections in the community was 18 (5th and 95th percentile: 12, 29). The factor most associated with under-reporting was the proportion of those who sought care that received a test.

Conclusions: Public health officials should use improved estimates to better understand the burden of COVID-19 and other similar infections.

Keywords: COVID-19; Canada; Ontario; disease; disease notification; public reporting of healthcare data; report; surveillance.