Web and phone-based COVID-19 syndromic surveillance in Canada: A cross-sectional study

Lauren Lapointe-Shaw; Benjamin Rader; Christina M Astley; Jared B Hawkins; Deepit Bhatia; William J Schatten; Todd C Lee; Jessica J Liu; Noah M Ivers; Nathan M Stall; Effie Gournis; Ashleigh R Tuite; David N Fisman; Isaac I Bogoch; John S Brownstein

doi:10.1371/journal.pone.0239886

. 2020 Oct 2;15(10):e0239886. doi: 10.1371/journal.pone.0239886

Web and phone-based COVID-19 syndromic surveillance in Canada: A cross-sectional study

Lauren Lapointe-Shaw ^1,^2,^*, Benjamin Rader ^3,⁴, Christina M Astley ^3,⁵, Jared B Hawkins ^3,⁵, Deepit Bhatia ¹, William J Schatten ⁶, Todd C Lee ⁷, Jessica J Liu ^1,², Noah M Ivers ^8,⁹, Nathan M Stall ^2,¹⁰, Effie Gournis ¹¹, Ashleigh R Tuite ¹², David N Fisman ^2,¹², Isaac I Bogoch ^1,^2,^#, John S Brownstein ^3,^5,^#

Editor: Francesco Di Gennaro¹³

¹Department of Medicine, University Health Network, Toronto, Canada

²Department of Medicine, University of Toronto, Toronto, Canada

³Computational Epidemiology Lab, Boston Children’s Hospital, Boston, MA, United States of America

⁴Department of Epidemiology, Boston University, Boston, MA, United States of America

⁵Department of Pediatrics, Harvard Medical School, Boston, MA, United States of America

⁶Forum Research, Toronto, Canada

⁷Department of Medicine, McGill University Health Centre and Clinical Practice Assessment Unit, McGill University, Montreal, Canada

⁸Department of Family and Community Medicine, University of Toronto, Toronto, Canada

⁹Department of Family Medicine, Women’s College Hospital, Toronto, Canada

¹⁰Department of Medicine, Sinai Health System, Toronto, Canada

¹¹Toronto Public Health, Toronto, Canada

¹²Dalla Lana School of Public Health, University of Toronto, Toronto, Canada

¹³National Institute for Infectious Diseases Lazzaro Spallanzani-IRCCS, ITALY

Competing Interests: WJ Schatten is a paid employee of Forum Research. This commercial affiliation does not alter our adherence to PLOS ONE policies on sharing data and materials. II Bogoch has consulted to BlueDot, a social benefit corporation that tracks the spread of emerging infectious diseases. The remaining authors have no disclosures.

^✉

* E-mail: lauren.lapointe.shaw@utoronto.ca

Contributed equally.

Roles

Lauren Lapointe-Shaw: Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Writing – original draft, Writing – review & editing

Benjamin Rader: Data curation, Formal analysis, Writing – review & editing

Christina M Astley: Data curation, Formal analysis, Methodology, Writing – review & editing

Jared B Hawkins: Conceptualization, Data curation, Writing – review & editing

Deepit Bhatia: Formal analysis, Writing – review & editing

William J Schatten: Data curation, Writing – review & editing

Todd C Lee: Conceptualization, Writing – review & editing

Jessica J Liu: Conceptualization, Writing – review & editing

Noah M Ivers: Conceptualization, Methodology, Writing – review & editing

Nathan M Stall: Conceptualization, Writing – review & editing

Effie Gournis: Conceptualization, Writing – review & editing

Ashleigh R Tuite: Methodology, Writing – review & editing

David N Fisman: Methodology, Writing – review & editing

Isaac I Bogoch: Conceptualization, Methodology, Project administration, Resources, Writing – review & editing

John S Brownstein: Conceptualization, Methodology, Project administration, Resources, Writing – review & editing

Francesco Di Gennaro: Editor

PMCID: PMC7531838 PMID: 33006990

Abstract

Background

Syndromic surveillance through web or phone-based polling has been used to track the course of infectious diseases worldwide. Our study objective was to describe the characteristics, symptoms, and self-reported testing rates of respondents in three different COVID-19 symptom surveys in Canada.

Methods

This was a cross-sectional study using three distinct Canada-wide web-based surveys, and phone polling in Ontario. All three sources contained self-reported information on COVID-19 symptoms and testing. In addition to describing respondent characteristics, we examined symptom frequency and the testing rate among the symptomatic, as well as rates of symptoms and testing across respondent groups.

Results

We found that over March- April 2020, 1.6% of respondents experienced a symptom on the day of their survey, 15% of Ontario households had a symptom in the previous week, and 44% of Canada-wide respondents had a symptom in the previous month. Across the three surveys, SARS-CoV-2-testing was reported in 2–9% of symptomatic responses. Women, younger and middle-aged adults (versus older adults) and Indigenous/First nations/Inuit/Métis were more likely to report at least one symptom, and visible minorities were more likely to report the combination of fever with cough or shortness of breath.

Interpretation

The low rate of testing among those reporting symptoms suggests significant opportunity to expand testing among community-dwelling residents of Canada. Syndromic surveillance data can supplement public health reports and provide much-needed context to gauge the adequacy of SARS-CoV-2 testing rates.

Introduction

While SARS-CoV-2 has rapidly spread globally, ascertaining its true incidence remains a challenge [1, 2]. This is because a large proportion of those infected (20–75%) are minimally symptomatic or asymptomatic [3, 4]. Further, in many regions only those with severe illness or identified as a priority group are tested, and thus eligible for laboratory test-based confirmation [5]. Until a rapid test is widely available or barriers to diagnostic testing in Canada are lowered, there will be a reliance on symptoms for early detection [1]. Yet, the range of presenting symptoms is broad, including generally common complaints (headache, fatigue) and more specific symptoms such as loss of smell or new onset chilblains [6–9].

Syndromic surveillance is a public health tool that has been used extensively to identify the beginning of seasonal influenza outbreaks in the United States [10–12] and Canada, and for other viral and bacterial diseases globally [13]. Where testing is incomplete, self-reported symptoms data is used to supplement confirmed case counts and estimate the true extent of disease [1]. The value of syndromic surveillance is higher when syndromes are illness-specific. However, because of the broad range of symptomatic presentations observed in SARS-CoV-2-infected individuals, a highly specific definition is likely to lack sensitivity and miss most people who would be eligible for testing [7]. Whereas grouping symptoms into clinical syndromes is likely to increase specificity, looking at the occurrence of any described symptom is the most sensitive way to measure all those who would be eligible for COVID-19 testing.

In Canada, phone and internet methods have been used to collect symptomatic and testing information from voluntary public participants. The primary objective of this study was to describe the characteristics, symptoms, and self-reported testing rates of respondents across three different COVID-19 symptom and testing surveys. The one phone and two internet-based polls we studied covered varied population subsets and timeframes.

Methods

In this cross-sectional study we retrospectively analyzed existing phone and internet survey data. This study was approved by the Ethics Review Board of University Health Network, which waived the requirement for informed consent. The data were de-identified prior to sharing with our study team. The only remaining identifiers were age, gender, and the first three digits of a six-digit Canadian postal code [14].

Data sources

Three data sources were used for this study. Survey response rates and relevant survey questions are in S1–S4 Tables.

The Angus Reid Institute COVID-19 symptom poll was administered online from April 1–6, 2020 to a randomly selected sample of Angus Reid Forum panel members (a group of over 50,000 Canadian residents who have volunteered to regularly fill out surveys in exchange for gift card or sweepstake rewards) [15, 16]. Respondents were asked about symptoms during the previous month, and about SARS-CoV-2 testing. Respondents were not asked about test results.

COVID Near You (covidnearyou.org) is a web-based participatory health surveillance tool created by infectious disease epidemiologists at Boston Children’s Hospital [17]. This team also created Flu Near You (flunearyou.org), a similar tool for influenza symptoms, which has been validated against clinical data sources and applied to predict influenza trends [10–12]. Between the Canadian launch on April 3^rd and April 26^th, there were over 420,000 responses. For individuals opting to include their phone number to be contacted for follow-up surveys (12% of responses) subsequent responses with the same age/sex/phone number were excluded (N = 3,511). Respondents were asked to report on present symptoms, and related healthcare encounters, testing, and results.

The Forum & Mainstreet Research poll on COVID-19 symptoms was administered by telephone and SMS (text) message to randomly selected households in Ontario in two waves: April 11–12 and April 18–19, 2020 [18, 19]. Datasets from both survey waves were combined; only the first survey was used for households that appeared in both waves (N = 158). Respondents were asked to report on new symptoms in the household over the previous week, about testing since the onset of symptoms, and test results.

Measures

Symptoms of possible COVID-19 were defined as inclusive of any of the following, where information was consistently available (>50% of sample was exposed to the question): fever, fatigue, runny nose, cough, aches and pains, chills/night sweats, sore throat, diarrhea, headache, shortness of breath, nausea, and loss of taste or smell. We excluded sneezing and rash as these are not described symptoms of COVID-19. We also reported on the self-reported combination of fever with either cough or shortness of breath, a COVID-like illness definition used by the World Health Organization [20]. Where possible, demographic variables were categorized to facilitate qualitative comparison between surveys.

Analysis

Due to considerable methodological differences across sources, results were analyzed separately. Where survey weights were included in sources (Angus Reid and Forum polls), we reported unweighted counts and weighted frequencies. As the COVID Near You team does not derive or use survey weights, we report unweighted counts and frequencies for results from this source. For Canada-wide data reported at the individual-level (Angus Reid Institute and COVID Near You surveys), we further reported the frequency of any symptom, the syndrome of fever with cough or shortness of breath [20], and testing across demographic groups. For data reported at the household level (Forum poll), we reported the frequency of symptoms, testing, and test results across household size and income groups. Testing for differences was done using Rao-Scott Chi-square tests for weighted results and Chi-square tests and Fisher exact tests (if small cells) for unweighted results, all at a two-tailed p<0.05 significance threshold. The data were analyzed using SAS software, version 9.4 (SAS Institute Inc., Carey, NC).

Results

Angus Reid Poll- Canada-wide, April 1–6, 2020

There were 4,240 respondents, their median age was 46.5 years (IQR 33–61), 52.0% (n = 2,152) were women, nearly half had completed some college or university (46.8%, n = 2,023), and 13.1% (n = 529) reported being a visible minority (Table 1). Completed testing was reported by 1.3% (n = 53), while 2.1% (n = 93) were not able to get tested, and 30.7% (n = 1,338) completed a COVID-19 self-assessment through a government website or app.

Table 1. Self-reported characteristics of respondents in each of the three data sources^a.

	Angus Reid Institute	COVID Near You	Forum/Mainstreet
	N = 4,240	N = 409,207	N = 9,147
	Individuals	Responses	Ontario households
Age group of respondent, n (%)
Under 35 years	1,197 (28.3)	114389 (28.0)	1,288 (13.0)
35–54	1,491 (34.6)	195140 (47.7)	2,854 (31.2)
55–64	755 (17.9)	64765 (15.8)	2,119 (24.0)
65–74	618 (14.8)	29855 (7.3)	1,798 (19.6)
75+ years	179 (4.4)	5057 (1.2)	1,088 (12.2)
Gender of respondent, n (%)
Female	2,152 (52.0)	237,150 (58.0)	4,931 (53.3)
Male	2,066 (47.6)	164,487 (40.2)	4,044 (45.0)
Other/No response	22 (0.4)	7,570 (1.8)	172 (1.7)
Annual Household Income (CAD), n (%)^b
Under 25,000	422 (9.7)	-	842 (7.3)^b
25,000-<50,000	761 (17.5)		2,719 (24.4)^b
50,000-<100,000	1,296 (30.3)		1,937 (20.3)^b
100,000-<150,000	762 (18.3)		1,860 (28.4)^b
150,000-<200,000	312 (7.7)
>200,000	166 (4.1)
Don’t know/rather not say	521 (12.4)		1,789 (19.6)^b
Highest Level of Education of Respondent, n (%)
Secondary or less	1,043 (25.1)	-	1,829 (18.3)
Some college or university	2,023 (46.8)		3,335 (34.7)
Completed undergraduate	819 (19.4)		2,405 (27.6)
Post-graduate degree	355 (8.8)		1,578 (19.4)
Respondent is Indigenous/First Nations/Inuit/Métis, n (%)	321 (7.3)	-	-
Respondent is a visible minority, n (%)	529 (13.1)	-	-
Household size, n (%)
1	693 (15.8)	-	1,620 (23.9)
2	1,637 (38.1)		3,362 (34.5)
3	790 (19.0)		1,526 (16.0)
4	715 (17.3)		1,525 (15.3)
5+	405 (9.8)		1,114 (10.4)
Province, n (%)
Alberta	422 (11.2)	55,257 (13.5)	-
BC	788 (13.1)	70,634 (17.3)
Manitoba	259 (3.5)	15,239 (3.7)
New Brunswick	81 (1.8)	5,765 (1.4)
Newfoundland/Labrador	73 (1.8)	1,786 (0.4)
Nova Scotia	147 (3.4)	13,220 (3.2)
Ontario	1,200 (37.7)	214,300 (52.4)
PEI	9 (0.2)	571 (0.1)
Quebec	1,010 (24.1)	20,344 (5.0)
Saskatchewan	251 (3.1)	11,777 (2.9)
Northwest Territories	-	102 (0.0)
Yukon	-	176 (0.0)
Nunavut	-	21 (0.0)

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^a Cells <6 have been suppressed (denoted with a “-“).

^b The household income categories for the Forum/Mainstreet poll are: Under 20,000, 20,000–60,000, 60,000–100,000, >100,000, and “rather not say”.

Over the previous month n = 1,863 (43.4%) reported at least one symptom. The most common symptoms were sore throat (n = 1229, 28.6%) and cough (n = 1154, 27.0%). The combination of fever with either cough or shortness of breath was reported by 6.9% of respondents (n = 295). Among those reporting any symptom, 2.6% (n = 46) reported having received testing. Among those reporting fever with either cough or shortness of breath, 5.7% (n = 15) reported having received COVID-19 testing.

More female than male respondents reported at least one symptom (45.3% vs 41.2%, p = 0.01, Table 2). Older persons (ages 65–74 and 75+) were less likely to report at least one symptom (p<0.0001) and the combination of fever with either cough or shortness of breath (p<0.0001). Indigenous/First Nations/Inuit/Metis had significantly higher rates of symptoms (49.3% vs 42.9%, p = 0.04) and testing (3.7% vs 1.1%, p = 0.0004) than those not reporting this background. This group (11.0% vs 6.5%, p = 0.005) and visible minorities (10.3% vs 6.3%, p = 0.001) also reported a higher rate of fever with cough or shortness of breath.

Table 2. Prevalence of symptoms and testing within sociodemographic groups in Angus Reid poll, April 1–6, 2020^a.

	Any symptom, n (%)	Fever + (cough OR shortness of breath), n (%)	Reported testing, n (%)
Age	p<0.0001	p<0.0001	p = 0.72
Under 35 years	630 (52.0)	113 (9.4)	15 (1.4)
35–54	701 (46.6)	112 (7.2)	23 (1.5)
55–64	276 (36.4)	40 (5.8)	9 (1.2)
65–74	197 (31.4)	24 (3.6)	-
75+ years	59 (32.2)	6 (3.3)	-
Gender	p = 0.02	p = 0.14	p = 0.03
Female	991 (45.3)	159 (7.2)	26 (1.2)
Male	861 (41.2)	133 (6.4)	26 (1.2)
Other/no response	11 (52.1)	-	-
Age among Females	p < 0.0001	p = 0.04	NA
Under 35 years	335 (53.5)	58 (8.8)	8 (1.5)
35–54	370 (49.1)	63 (8.1)	11 (1.5)
55–64	148 (37.3)	22 (6.4)	-
65–74	106 (34.0)	13 (4.2)	-
75+ years	32 (33.8)	-	-
Age among Males	p < 0.0001	p = 0.003	p = 0.94
Under 35 years	285 (50.0)	52 (9.7)	6 (1.1)
35–54	331 (44.1)	49 (6.2)	12 (1.5)
55–64	127 (35.3)	18 (5.3)	-
65–74	91 (28.3)	11 (2.9)	-
75+ years	27 (30.6)	-	-
Annual Household Income (CAD)	p = 0.36	p = 0.54	p = 0.26
Under 25,000	197 (45.9)	39 (8.7)	-
25,000-<50,000	335 (43.7)	50 (6.4)	8 (1.1)
50,000-<100,000	580 (44.4)	97 (7.6)	15 (1.3)
100,000-<150,000	340 (43.1)	52 (6.7)	12 (1.4)
150,000-<200,000	142 (45.6)	15 (5.1)	8 (2.7)
>200,000	65 (39.6)	10 (6.7)	-
Don’t know/would rather not say	204 (38.9)	32 (5.8)	-
Highest Level of Education	p = 0.13	p = 0.80	p = 0.99
Secondary or less	437 (40.6)	75 (7.1)	11 (1.3)
Some college or university	903 (44.6)	147 (7.1)	25 (1.3)
Completed undergraduate	374 (45.1)	51 (6.4)	11 (1.2)
Post-graduate degree	149 (41.2)	22 (5.8)	6 (1.4)
Indigenous/First nations/Inuit/Métis	p = 0.04	p = 0.005	p = 0.0004
Indigenous/First nations/Inuit/Métis	161 (49.3)	36 (11.0)	11 (3.7)
Visible minority	p = 0.31	p = 0.001	p = 0.10
Visible minority	245 (45.5)	56 (10.3)	10 (2.1)
Province^b	p = 0.25	p = 0.41	NA
Alberta	191 (44.6)	33 (7.5)	-
British Columbia	359 (45.7)	54 (6.6)	8 (1.2)
Manitoba	124 (47.3)	26 (10.7)	-
New Brunswick	42 (51.5)	8 (9.2)	-
Newfoundland/Labrador	26 (36.1)	-
Nova Scotia	67 (46.8)	7 (5.1)	-
Ontario	499 (41.4)	88 (7.3)	13 (1.1)
Quebec	435 (43.1)	59 (5.7)	20 (2.0)
Saskatchewan	115 (45.9)	15 (6.1)	-

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^a All percentage are weighted row percentages, reflecting the prevalence of column variables in each row group. p-values for between-group differences are at the top of each cell (for example in the top left cell, p-value is for the 5x2 table of age groups by any symptom yes/no). Cells <6 have been suppressed (denoted with a “-“). NA = not applicable (p-value could not be calculated due to zero cells and weighted data)

^b Prince Edward Island results were suppressed due to small cells (< 6 observations).

COVID Near You- Canada-wide, April 3—April 26, 2020

After excluding duplicates, there were 409,207 responses. The median age was 42 years (IQR 33–54) and 58.0% (n = 237,150) were women (Table 1). Testing was reported in 0.2% (n = 612) of responses, and 0.4% (n = 1,479) reported seeing a health professional. Positive test results were reported in 0.03% (n = 105); some 0.1% (n = 213) reported that they were still waiting for their result. Among all respondents, 0.1% (n = 313) reported travel outside Canada in the previous two weeks and 0.1% (n = 324) reported contact with a known case of COVID-19.

The overall prevalence of symptoms was 1.6% (n = 6,746) and the most common symptoms were fatigue (n = 3,982, 1.0%), cough (n = 3,416, 0.8%) and headache (n = 3,406, 0.8%). The combination of fever with either cough or shortness of breath was reported by 0.2% of respondents (n = 758). Among those reporting any symptom, 8.9% (n = 598) reported being tested. Among those reporting fever with cough or shortness of breath, 21.0% (n = 159) reported being tested. Of the symptomatic who were tested, 17.2% (n = 103) reported a positive result.

More female than male respondents reported at least one symptom (2.0% vs 1.2%, p<0.001, Table 3), and were tested (0.2% vs 0.1%, p<0.001). Females and males had similar rates of positive test results (0.3% vs 0.2%, p = 0.44). Younger or middle-aged groups were more likely to report symptoms than older groups (p<0.001). Those under the age of 35 or over age 75 were more likely to have been tested (p = 0.009). A positive test result was significantly more common among those over age 75 (14% compared to 2–3% in other groups, p = 0.002). The rate of symptoms varied significantly across provinces–reporting at least one symptom was most common in British Columbia (2.1%) and Nova Scotia (2.0%, p<0.001) and reported testing rates were the highest in Nova Scotia (0.4%) and Saskatchewan (0.3%, p<0.001).

Table 3. Prevalence of self-reported symptoms, testing and positive test results within age, gender and province groups in COVID Near You poll, April 4–26, 2020^a.

	Any symptom, n (%)	Fever + (cough OR shortness of breath), n (%)	Reported testing, n (%)	Reported positive test result, n (%)
Age	p <0.001	p = 0.44	p = 0.009	p = 0.002
Under 35 years	1,969 (1.7)	227 (0.2)	195 (0.2)	31 (0.03)
35–54	3,172 (1.6)	348 (0.2)	292 (0.1)	45 (0.02)
55–64	1,137 (1.8)	121 (0.2)	77 (0.1)	13 (0.02)
65–74	397 (1.3)	49 (0.2)	35 (0.1)	9 (0.03)
75+ years	70 (1.4)	13 (0.3)	13 (0.3)	7 (0.14)
Gender	p <0.001	p <0.001	p <0.001	p = 0.003
Female	4,672 (2.0)	511 (0.2)	432 (0.2)	61 (0.03)
Male	1,904 (1.2)	210 (0.1)	158 (0.1)	36 (0.02)
Other/no response	170 (2.2)	37 (0.5)	22 (0.3)	8 (0.11)
Age among Females	p <0.001	p = 0.64	p = 0.34	p = 0.014
Under 35 years	1,335 (1.9)	141 (0.2)	132 (0.2)	19 (0.03)
35–54	2,229 (2.0)	247 (0.2)	216 (0.2)	27 (0.02)
55–64	807 (2.2)	82 (0.2)	55 (0.2)	8 (0.02)
65–74	271 (1.7)	34 (0.2)	24 (0.2)	-
75+ years	30 (1.5)	7 (0.3)	-	-
Age among Males	p < 0.001	p = 0.003	p = 0.003	p = 0.36
Under 35 years	562 (1.4)	76 (0.2)	54 (0.1)	9 (0.02)
35–54	870 (1.1)	84 (0.1)	68 (0.1)	16 (0.02)
55–64	320 (1.2)	37 (0.1)	19 (0.1)	-
65–74	118 (0.9)	10 (0.1)	10 (0.1)	-
75+ years	34 (1.2)	3 (0.1)	7 (0.3)	-
Province^b	p < 0.001	p < 0.001	p < 0.001	p = 0.08
Alberta	868 (1.6)	68 (0.1)	97 (0.2)	7 (0.01)
BC	1483 (2.1)	218 (0.3)	95 (0.1)	21 (0.03)
Manitoba	242 (1.6)	25 (0.2)	16 (0.1)	-
New Brunswick	91 (1.6)	8 (0.1)	9 (0.2)	-
Newfoundland /Labrador	26 (1.5)	-	-	-
Nova Scotia	269 (2.0)	18 (0.1)	49 (0.4)	-
Ontario	3336 (1.6)	377 (0.2)	291 (0.1)	67 (0.03)
PEI	7 (1.2)	-	-	-
Quebec	249 (1.2)	22 (0.1)	22 (0.1)	-
Saskatchewan	170 (1.4)	18 (0.2)	31 (0.3)	-

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^a All percentage are row percentages, reflecting the prevalence of column variables in each row group. p-values for between-group differences are at the top of each cell (for example in the top left cell, p-value is for the 5x2 table of age groups by “any symptom” yes/no). Cells <6 have been suppressed (denoted with a “-“).

^b Due to small cell sizes (<6), results for Yukon, Northwest Territories and Nunavut were suppressed.

Forum & Mainstreet Research phone poll- Ontario, April 11–12 and April 18–19, 2020

There were 9,147 unique households surveyed, and 41.7% (n = 4,165) consisted of at least 3 residents (Table 1). The survey respondents were more often women (53.3%, n = 4,931) than men. Completed testing was reported by 3.2% of all households (n = 299), and positive test results by 0.4% (n = 43). In addition, 0.5% (n = 50) were still awaiting test results.

The overall prevalence of any new symptom in the previous week was 14.9% (n = 1,385). The most common symptoms reported were headache (n = 662, 7.0%), sore throat (n = 377, 3.9%) and diarrhea (N = 345, 3.8%). The combination of fever with either cough or shortness of breath within the same household was reported by 0.8% (n = 82). Among those with any symptom, 6.5% (n = 94) reported that a household member had been tested. Among those with fever and either cough or shortness of breath, 37.5% (n = 31) reported that a household member had been tested. Positive test results were reported for 26.5% (n = 25) of all symptomatic households tested.

The lowest and highest income households had a significantly higher prevalence of COVID-19 symptoms (16.2% and 17.0%, p = 0.002, Table 4). The lowest income group was most likely to report a positive test result (1.2% in lowest vs 0.4% in highest, p = 0.05). The largest households were significantly more like to have at least one person with a COVID-19 symptom (19.6% in largest vs 12.4% in smallest, p<0.0001) and to report that at least one member was tested (5.0% vs 2.5%, p = 0.006). Households of one or 5+ persons were more likely to report flulike illness than households of 2–4 people (0.8% and 0.4% compared to 0.1–0.2%, p = 0.005).

Table 4. Prevalence of self-reported symptoms, testing and positive test results within household groups in Forum & Mainstreet Research phone poll, April 11–12 and 18–19, 2020^a.

	Any symptom, n (%)	Fever + (cough OR shortness of breath), n (%)	Reported testing, n (%)	Reported positive test result, n (%)
Household Income ($), n (%)	p = 0.002	p = 0.62	p = 0.17	p = 0.05
Under 20,000	139 (16.2)	12 (1.4)	34 (4.2)	10 (1.2)
20,000-<60,000	411 (14.6)	26 (0.8)	93 (3.2)	13 (0.5)
60,000-<100,000	285 (14.1)	15 (0.8)	48 (2.4)	7 (0.4)
>100,000	323 (17.0)	15 (0.8)	61 (3.1)	7 (0.4)
Don’t know/rather not say	227 (12.7)	14 (0.8)	63 (3.5)	6 (0.3)
Household size, n (%)	p<0.0001	p = 0.005	p = 0.006	p = 0.28
1	202 (12.4)	13 (0.8)	44 (2.5)	8 (0.4)
2	454 (13.4)	23 (0.1)	100 (2.9)	19 (0.5)
3	236 (15.6)	11 (0.2)	42 (2.9)	-
4	276 (18.2)	9 (0.2)	56 (3.6)	-
5+	217 (19.6)	26 (0.4)	57 (5.0)	9 (0.7)

Open in a new tab

^a All percentage are weighted row percentages, reflecting the prevalence of column variables in each row group. p-values for between-group differences are at the top of each cell (for example in the top left cell, p-value is for the 5x2 table of household income groups by any symptom yes/no). Cells <6 have been suppressed (denoted with a “-“).

Discussion

In this study of syndromic surveillance data from three different survey sources, we find that described symptoms of COVID-19 were commonly reported by Canadian respondents. Specifically, 1.6% of respondents reported a symptom on the day of response, 15% of Ontario households had a new symptom in the previous week, and 43% of Canada-wide respondents had a symptom during March-early April 2020. Across the three studies, SARS-CoV-2-testing was reported in 2–9% of symptomatic responses, with a positive test rate among the symptomatic and tested of 17% in COVID Near You and 27% in the Forum Research poll. The three survey sources differed in geography (one covered only Ontario), time period (March to end of April 2020), and their representativeness across different demographic variables. Yet, after considering differences in the time window addressed with survey questions (present day, past week, past month), some consistent findings emerged.

In two different polls, women were more likely to report at least one symptom. In one poll, women were more likely to report testing. In Ontario, more women than men have been tested for SARS-CoV-2, yet men were more likely to have a positive test result [21]. Although the higher testing rate among women could reflect their greater presence in the healthcare sector, our findings also raise the possibility that women are more likely to report COVID-19-like symptoms. We further found that older respondents were less likely to report COVID-19 symptoms, but were more likely to test positive if tested. This higher self-reported rate of positivity is consistent with the concentration of early COVID-19 outbreaks among older Canadians, including (but not limited to) those residing in long-term care facilities (nursing homes) [22]. We found that Indigenous/First Nations/Inuit/Metis individuals reported a higher rate of symptoms and testing, and that visible minorities reported higher rates of fever with cough or shortness of breath. Residents of Indigenous communities were an early priority group for SARS-CoV-2 testing [5].

A report from the province of Ontario did not identify a consistent difference in testing rates across socioeconomic groups, although neighborhoods with higher ethnic concentration had a significantly higher rate of test positivity [23]. We did not identify significant differences in the frequency of possible COVID-19 symptoms across income or education groups at the level of the individual. However, we did find that households in the lowest income group were more likely to report symptoms and a positive test result among at least one resident. Larger households were also more likely to report that at least one person had symptoms or was tested–this may reflect the additional risk that comes from having more inhabitants or other characteristics potentially associated with larger households, such as level of education, income or ethnicity.

Whereas there were significant interprovincial differences in the proportion of COVID Near You respondents with symptoms, this was not the case for the Angus Reid poll. This may reflect differences in sample size, where a greater number of responses to COVID Near You meant that even small absolute differences in proportions reached statistical significance. Nonetheless, differences observed between provinces in both COVID Near You and the Angus Reid poll did not reflect differences in confirmed COVID-19 case activity. In COVID Near You, British Columbia and Nova Scotia had the highest proportion reporting at least one COVID-19 symptom. Yet, during March-April 2020, Quebec had considerably more cases than any other province [24]. This inconsistency with inter-provincial confirmed case trends likely reflects regional differences in survey uptake. Hence, some caution is warranted in attempting to compare rates of symptoms across provinces.

An important consideration in interpreting our findings is that many people with COVID-19 symptoms will not have COVID-19; conditions ranging from stress-related headaches and allergies to undiagnosed malignancies could also cause the same symptoms. Using only a more restrictive symptomatic definition such as fever with either cough or shortness of breath would miss many potential cases. Similarly, a recently developed algorithm that combines loss of smell or taste, fatigue, skipped meals, and cough, was only 65% sensitive for a positive SARS-CoV-2 test result [7]. To better understand current testing rates, we opted to use a broad symptom definition. This definition included anyone who would be eligible for testing on the basis of symptoms. To facilitate comparison, we also reported the proportion with fever and either cough or shortness of breath, an early syndromic definition used by the World Health Organization [20]. The weekly rate of household-level combination of fever with cough or shortness of breath in this study (Forum Research poll of Ontario in mid-April: 0.8%) was comparable to that obtained by the Public Health Agency of Canada’s FluWatchers for the combination of cough and fever in early April 2020 (0.5%) [25].

There have been no previous reports of COVID-19 symptoms among the broader Canadian population published in the peer-reviewed literature. Our study provides essential information on the prevalence of such symptoms, and the proportion of symptomatic persons being tested. Strengths of this study are its inclusion of self-reported data from three distinct sources, covering March-April 2020. The consistency of our findings with published public health data suggests it is representative of the general population. Finally, the information we provide allows for a more complete picture of COVID-19 in Canada than just that which manifests through healthcare encounters. Lower barriers to diagnostic testing are essential given the growing understanding that COVID-19 can present with myriad symptoms. This will be helpful in identifying and isolating cases and preventing outbreaks as public health measures are lifted.

Limitations

Our study also has several limitations. The variable time frames used in the three data sources complicate cross-study comparison, and longer time periods of self-report (e.g. “in the past month”) may lead to higher levels of recall bias than shorter time periods. Similarly, household-level reporting does not easily compare to individual report, and combining symptoms experienced within a household may erroneously attribute all those symptoms to the same individual. Furthermore, survey questions varied in terms of symptoms covered and the inclusion of questions relating to healthcare encounters or testing results. Sample sizes were also quite small within subgroups, particularly when looking at those that reported testing or testing positive. Although the Angus Reid and Forum Research polls had a random sampling strategy, respondents on COVID Near You were self-selected, and so it was important to compare their characteristics, symptom reports, and testing rates to those obtained in the other two studies. Finally, despite their overall higher risk for COVID-19, those residing in long-term care and other institutional settings are likely not represented in these data sources which focus on community-dwelling residents of Canada.

Conclusion

This study contributes essential data on the prevalence of COVID-19-related symptoms in Canada, and the proportion of symptomatic persons tested. This information complements public health-reported data on testing numbers and confirmed cases in Canada. We find that across three unique symptom surveys, less than 10% of those with symptoms in March-April 2020 reported having been tested for SARS-CoV-2. Our findings highlight the significant room to expand testing among community-dwelling residents of Canada. We have also identified groups with higher symptom prevalence (women, younger age groups, Indigenous/First Nations/Inuit/Métis), information which can be used to refine testing strategies and guide outreach efforts. Syndromic surveillance data such as these can supplement public health reports and provide much-needed context to gauge the adequacy of current SARS-CoV-2 testing rates.

Supporting information

S1 Table. Survey response rates.

(DOCX)

Click here for additional data file.^{(16.9KB, docx)}

S2 Table. Angus Reid poll questions used in this study.

(DOCX)

Click here for additional data file.^{(20.1KB, docx)}

S3 Table. COVID Near You tool questions used in this study.

(DOCX)

Click here for additional data file.^{(18.3KB, docx)}

S4 Table. Forum poll questions used in this study.

(DOCX)

Click here for additional data file.^{(18.9KB, docx)}

Acknowledgments

We thank Boston Children’s Hospital, the Angus Reid Institute, Forum Research and Mainstreet Research for providing the data used in this study. Boston Children’s Hospital, the Angus Reid Institute, Forum Research and Mainstreet Research bear no responsibility for the analyses or interpretations of the data presented here.

Data Availability

The data used in this study is the property of the Angus Reid Institute, Forum and Mainstreet Research, and the Boston Children’s Hospital. Data from the Forum and Mainstreet poll have been made available at https://doi.org/10.5683/SP2/YM8BCJ. Requests for access to Angus Reid or COVID Near You data should go to info@angusreid.org or john.brownstein@childrens.harvard.edu, respectively. Data from COVID Near You to be used for public health surveillance purposes can be requested at: https://www.atscale.com/covidnearyou/.

Funding Statement

This research was supported by the University of Toronto, Department of Medicine COVID-19 Funding Opportunity (Lapointe-Shaw). WJ Schatten is a paid employee of Forum Research, which collected and supplied the data resulting from the Forum & Mainstreet poll. Forum Research was not involved in study design, collection of data from other sources, data analysis, decision to publish, or preparation of the manuscript. Forum Research provided no other financial support to any study team members or their institutions. The specific role of all authors are described in the “author contributions” section.

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PLoS One. doi: 10.1371/journal.pone.0239886.r001

Decision Letter 0

Francesco Di Gennaro

22 Jul 2020

PONE-D-20-18024

Web and Phone-based COVID-19 Syndromic Surveillance in Canada: A Cross-Sectional Study

PLOS ONE

Dear Dr. Lauren Lapointe-Shaw

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Reviewer #1: Yes

Reviewer #2: Partly

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: I Don't Know

**********

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Reviewer #2: Yes

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Reviewer #1: This article provides estimates of the prevalence of COVID-19 symptoms in Canada which is valuable for modelling and public health planning. A few points for consideration:

1) How are the Angus Reid Forum panel members selected? Is this a random sample of Canadians?

2) At the start of page 8, Table 2 is referenced and I believe this should be Table 3.

3) Verify data in Table 3 as the proportion reporting at least one symptom for Ontario on page 8 differs from what is in Table 3

4) No regional differences were observed with the Angus Reid data but regional differences were observed in the COVID near you data. Any reasons to explain why?

Reviewer #2: Title: Web and Phone-based COVID-19 Syndromic Surveillance in Canada: A Cross-Sectional Study

This paper presents a study to describe the characteristics, symptoms, and self-reported testing rates of respondents in three different COVID-19 symptom surveys in Canada. However, there are questions that limit my enthusiasm of the paper, as outlined below.

1. Results:

a. Table 1: Authors considered (-) and 0. What I guess (-) shows cell<6. So please define that at the caption and fix that across all 3 tables. We don’t expect to have both 0 and (-) across tables.

b. Table 2: Authors did stratification for the age based on the gender.

i. Did authors find gender as a cofounder or important variable that is associated with Fever + (cough or shortness of breath)/Any symptom? Please clarify this part. In other words, I would like to know the reason of stratification of age by gender.

ii. At least for COVID Near You, there is enough samples for other/no response group. Please modify Table 3 and add that group result to the Table.

iii. Why not to consider age as an individual variable without being classified by gender and be added to the Tables. How about adding gender (F/M/other) to the Tables as well?

iv. Tables 2 and 3 can’t be followed easily. Please modify the tables.

v. (Rao-Scott) Chi-squared/Fisher tests assess the association between two categorical variables, or comparing proportions across cells for a given variable. Authors considered these methods to compare the proportions of cells (e.g., age groups) for a given variable (e.g., any symptom), is it right?

vi. Is there any reported testing results for Angus Reid Poll study (Table 2)?

c. Why authors didn’t include Table for Forum and mainstreet research phone poll? Please clarify this part.

2. I suggest authors consider parametric methods (e.g., logistic regression model) to add more results regarding the association between the demographic variables and two main variables (1) Fever + (cough OR shortness of breath) vs other symptom and (2) Reported positive test result/not.

3. In addition to the previous comment, how about comparing the results between web and phone-based sources? Authors introduced these three data sources, however there is not enough results to compare the data across these three studies.

4. Authors should be more precise about calling Tables across manuscript. Page 8, line 1 (results related to the COVID Near You), shows Table 3, not Table 2.

5. To improve results due to the lack of samples, integrating these three studies using meta-analysis approaches may improve results and power of analysis.

**********

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2020 Oct 2;15(10):e0239886. doi: 10.1371/journal.pone.0239886.r002

Author response to Decision Letter 0

19 Aug 2020

Please see submitted "responses" document.

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PLoS One. doi: 10.1371/journal.pone.0239886.r003

Decision Letter 1

Francesco Di Gennaro

16 Sep 2020

Web and phone-based COVID-19 syndromic surveillance in Canada: a cross-sectional study

PONE-D-20-18024R1

Dear Dr. Lapaoint-Shaw,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Francesco Di Gennaro

Academic Editor

PLOS ONE

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Dear Authors, congratulations!

Reviewers' comments:

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Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: No

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Reviewer #1: I have reviewed the responses to my questions and concerns. They have been addressed sufficiently. I have no further comments. I note that there are some restrictions to making the data publicly available and they appear to be warranted.

Reviewer #2: All the comments have been addressed. Just a minor comment is related to introduce the IQR in the method section before using at result section. Thank you

**********

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PLoS One. doi: 10.1371/journal.pone.0239886.r004

Acceptance letter

Francesco Di Gennaro

25 Sep 2020

PONE-D-20-18024R1

Web and phone-based COVID-19 syndromic surveillance in Canada: a cross-sectional study

Dear Dr. Lapointe-Shaw:

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Kind regards,

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on behalf of

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Table. Survey response rates.

(DOCX)

Click here for additional data file.^{(16.9KB, docx)}

S2 Table. Angus Reid poll questions used in this study.

(DOCX)

Click here for additional data file.^{(20.1KB, docx)}

S3 Table. COVID Near You tool questions used in this study.

(DOCX)

Click here for additional data file.^{(18.3KB, docx)}

S4 Table. Forum poll questions used in this study.

(DOCX)

Click here for additional data file.^{(18.9KB, docx)}

Attachment

Submitted filename: comments_07202020.docx

Click here for additional data file.^{(16.4KB, docx)}

Attachment

Submitted filename: Responses_ August192020.docx

Click here for additional data file.^{(45KB, docx)}

Data Availability Statement

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PERMALINK

Web and phone-based COVID-19 syndromic surveillance in Canada: A cross-sectional study

Lauren Lapointe-Shaw

Benjamin Rader

Christina M Astley

Jared B Hawkins

Deepit Bhatia

William J Schatten

Todd C Lee

Jessica J Liu

Noah M Ivers

Nathan M Stall

Effie Gournis

Ashleigh R Tuite

David N Fisman

Isaac I Bogoch

John S Brownstein

Roles

Abstract

Background

Methods

Results

Interpretation

Introduction

Methods

Data sources

Measures

Analysis

Results

Angus Reid Poll- Canada-wide, April 1–6, 2020

Table 1. Self-reported characteristics of respondents in each of the three data sourcesa.

Table 2. Prevalence of symptoms and testing within sociodemographic groups in Angus Reid poll, April 1–6, 2020a.

COVID Near You- Canada-wide, April 3—April 26, 2020

Table 3. Prevalence of self-reported symptoms, testing and positive test results within age, gender and province groups in COVID Near You poll, April 4–26, 2020a.

Forum & Mainstreet Research phone poll- Ontario, April 11–12 and April 18–19, 2020

Table 4. Prevalence of self-reported symptoms, testing and positive test results within household groups in Forum & Mainstreet Research phone poll, April 11–12 and 18–19, 2020a.

Discussion

Limitations

Conclusion

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Francesco Di Gennaro

Roles

Author response to Decision Letter 0

Decision Letter 1

Francesco Di Gennaro

Roles

Acceptance letter

Francesco Di Gennaro

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases

Table 1. Self-reported characteristics of respondents in each of the three data sources^a.

Table 2. Prevalence of symptoms and testing within sociodemographic groups in Angus Reid poll, April 1–6, 2020^a.

Table 3. Prevalence of self-reported symptoms, testing and positive test results within age, gender and province groups in COVID Near You poll, April 4–26, 2020^a.

Table 4. Prevalence of self-reported symptoms, testing and positive test results within household groups in Forum & Mainstreet Research phone poll, April 11–12 and 18–19, 2020^a.