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

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 3rd and April 26th, 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.

	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)

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.

	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
	161 (49.3)	36 (11.0)	11 (3.7)
Visible minority	p = 0.31	p = 0.001	p = 0.10
	245 (45.5)	56 (10.3)	10 (2.1)
Provinceb	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)	-

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.

	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)	-
Provinceb	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)	-

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.

	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)

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.

Survey response rates.

(DOCX)

Click here for additional data file.

Angus Reid poll questions used in this study.

(DOCX)

Click here for additional data file.

COVID Near You tool questions used in this study.

(DOCX)

Click here for additional data file.

Forum poll questions used in this study.

(DOCX)

Click here for additional data file.

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

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by 20 August. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Francesco Di Gennaro

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. In ethics statement in the manuscript and in the online submission form, please provide additional information about the patient records used in your retrospective study. Specifically, please ensure that you have discussed whether all data were fully anonymized before you accessed them and/or whether the IRB or ethics committee waived the requirement for informed consent. If patients provided informed written consent to have data from their medical records used in research, please include this information.

3. Thank you for including your competing interests statement; "I have read the journal's policy and the authors of this manuscript have the following competing interests: WJ Schatten is a paid employee for Forum Research. II Bogoch has consulted to BlueDot, a social benefit corporation that tracks the spread of emerging infectious diseases. The remaining authors have no disclosures."

We note that one or more of the authors are employed by a commercial company: Forum Research

Please provide an amended Funding Statement declaring this commercial affiliation, as well as a statement regarding the Role of Funders in your study. If the funding organization did not play a role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript and only provided financial support in the form of authors' salaries and/or research materials, please review your statements relating to the author contributions, and ensure you have specifically and accurately indicated the role(s) that these authors had in your study. You can update author roles in the Author Contributions section of the online submission form.

Please also include the following statement within your amended Funding Statement.

“The funder provided support in the form of salaries for authors [insert relevant initials], but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.”

If your commercial affiliation did play a role in your study, please state and explain this role within your updated Funding Statement.

2. Please also provide an updated Competing Interests Statement declaring this commercial affiliation along with any other relevant declarations relating to employment, consultancy, patents, products in development, or marketed products, etc.

Within your Competing Interests Statement, please confirm that this commercial affiliation does not alter your adherence to all PLOS ONE policies on sharing data and materials by including the following statement: "This does not alter our adherence to  PLOS ONE policies on sharing data and materials.” (as detailed online in our guide for authors http://journals.plos.org/plosone/s/competing-interests) . If this adherence statement is not accurate and  there are restrictions on sharing of data and/or materials, please state these. Please note that we cannot proceed with consideration of your article until this information has been declared.

Please include both an updated Funding Statement and Competing Interests Statement in your cover letter. We will change the online submission form on your behalf.

Please know it is PLOS ONE policy for corresponding authors to declare, on behalf of all authors, all potential competing interests for the purposes of transparency. PLOS defines a competing interest as anything that interferes with, or could reasonably be perceived as interfering with, the full and objective presentation, peer review, editorial decision-making, or publication of research or non-research articles submitted to one of the journals. Competing interests can be financial or non-financial, professional, or personal. Competing interests can arise in relationship to an organization or another person. Please follow this link to our website for more details on competing interests: http://journals.plos.org/plosone/s/competing-interests

4. We note you have included a table to which you do not refer in the text of your manuscript. Please ensure that you refer to Table 3 in your text; if accepted, production will need this reference to link the reader to the Table.

Additional Editor Comments (if provided):

I appreciate your paper, but need some revisions.

Following reviewer suggestions you can improve your manuscript

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

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

**********

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

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: No

**********

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

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

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.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

Submitted filename: comments_07202020.docx

Click here for additional data file.

19 Aug 2020

Please see submitted "responses" document.

Submitted filename: Responses_ August192020.docx

Click here for additional data file.

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.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Francesco Di Gennaro

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Dear Authors, congratulations!

Reviewers' comments:

Reviewer's Responses to Questions

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?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

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?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: Yes

**********

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

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

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

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

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:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Francesco Di Gennaro

Academic Editor

PLOS ONE