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. 2022 Jan 11;17(1):e0262447.
doi: 10.1371/journal.pone.0262447. eCollection 2022.

Comparison of longitudinal trends in self-reported symptoms and COVID-19 case activity in Ontario, Canada

Arjuna S Maharaj  1 , Jennifer Parker  1 , Jessica P Hopkins  2   3   4 , Effie Gournis  4   5 , Isaac I Bogoch  6   7 , Benjamin Rader  8   9 , Christina M Astley  8   10   11 , Noah M Ivers  12   13 , Jared B Hawkins  8 , Liza Lee  14 , Ashleigh R Tuite  4 , David N Fisman  4   6 , John S Brownstein  8   15 , Lauren Lapointe-Shaw  6   7
Affiliations

Comparison of longitudinal trends in self-reported symptoms and COVID-19 case activity in Ontario, Canada

Arjuna S Maharaj et al. PLoS One. .

Abstract

Background: Limitations in laboratory diagnostic capacity impact population surveillance of COVID-19. It is currently unknown whether participatory surveillance tools for COVID-19 correspond to government-reported case trends longitudinally and if it can be used as an adjunct to laboratory testing. The primary objective of this study was to determine whether self-reported COVID-19-like illness reflected laboratory-confirmed COVID-19 case trends in Ontario Canada.

Methods: We retrospectively analyzed longitudinal self-reported symptoms data collected using an online tool-Outbreaks Near Me (ONM)-from April 20th, 2020, to March 7th, 2021 in Ontario, Canada. We measured the correlation between COVID-like illness among respondents and the weekly number of PCR-confirmed COVID-19 cases and provincial test positivity. We explored contemporaneous changes in other respiratory viruses, as well as the demographic characteristics of respondents to provide context for our findings.

Results: Between 3,849-11,185 individuals responded to the symptom survey each week. No correlations were seen been self-reported CLI and either cases or test positivity. Strong positive correlations were seen between CLI and both cases and test positivity before a previously documented rise in rhinovirus/enterovirus in fall 2020. Compared to participatory surveillance respondents, a higher proportion of COVID-19 cases in Ontario consistently came from low-income, racialized and immigrant areas of the province- these groups were less well represented among survey respondents.

Interpretation: Although digital surveillance systems are low-cost tools that have been useful to signal the onset of viral outbreaks, in this longitudinal comparison of self-reported COVID-like illness to Ontario COVID-19 case data we did not find this to be the case. Seasonal respiratory virus transmission and population coverage may explain this discrepancy.

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Conflict of interest statement

We have read the journal’s policy and the authors of this manuscript have the following competing interests: IIB has consulted to BlueDot, a social benefit corporation that tracks the spread of emerging infectious diseases. DNF reports personal consultant fees from Pfizer, AstraZeneca, and Seqirus, outside the submitted work. This does not alter our adherence to PLOS ONE policies on sharing data and materials

Figures

Fig 1
Fig 1. Comparison of surveillance signal from ONM to COVID-19 activity.
(A) Percent CLI and CLI2 vs new COVID-19 cases and symptomatic COVID-19 cases. (B) Percent CLI and percent positivity for SARS-CoV2. (C) Percent CLI and number of new COVID-19 cases based on the estimated date of symptom onset. (D) Percent CLI of those ≥19 years of age and new COVID-19 cases among those ≥19 years of age.
Fig 2
Fig 2. Percent positivity of seasonal respiratory viruses.
Coronavirus represents tests positivity of non-SARS-CoV2 coronaviruses.
Fig 3
Fig 3. Age group of ONM respondents for ISO week 17, 2020 –week 9, 2021.
Fig 4
Fig 4
Reported age of those with CLI from ONM (left) and age of reported COVID-19 cases in Ontario (right).
Fig 5
Fig 5. Household income in ONM and COVID-19 cases.
Distribution of responses in each quintile from ONM and COVID-19 cases in Ontario over time based on median annual household income (Canadian Dollars) in geographic area.
Fig 6
Fig 6. Percent recent immigrants in ONM and COVID-19 cases.
Distribution of responses in each quintile from ONM and COVID-19 cases in Ontario over time based on proportion recent immigrants (last 5 years) in geographic area sorted by quintile.
Fig 7
Fig 7. Percent visible minorities in ONM and COVID-19.
Distribution of responses in each quintile from ONM and COVID-19 cases in Ontario over time based on % visible minorities in geographic area.
See this image and copyright information in PMC

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