Canadian COVID-19 Antibody and Health Survey (CCAHS)

Detailed information for January 2020 to August 2022





Record number:


The Canadian COVID-19 Antibody and Health Survey (CCAHS), is collecting key information relevant to the COVID-19 pandemic to learn as much as possible about the virus, how it affects overall health, how it spreads, and whether Canadians are developing antibodies against it.

Data release - October 17, 2022


The Canadian COVID-19 Antibody and Health Survey will collect information in two parts. The first part is an electronic questionnaire about general health and exposure to COVID-19. The second part is two self-administered tests; an at-home finger-prick blood test called a dried blood spot (DBS) test, which will be used to measure the presence of antibodies against SARS-CoV-2 from vaccination or prior infection. The second at-home test is a polymerase chain reaction (PCR) saliva test which will determine if there is an active SARS-CoV-2 infection. Both tests should be done as soon as possible after the questionnaire.

The data will be used to:
- estimate how many Canadians test positive for antibodies against COVID-19. By using each participant's DBS samples combined with their survey responses, we will also have a better idea of how many Canadians have antibodies against COVID-19 due to infection, vaccination or both.
- to provide a platform to explore emerging public health issues;
- assist in the development of programs and services to respond to the needs of the current pandemic.
- to identify active COVID-19 infections in Canada.

Reference period: Varies according to the question (e.g. March 2020 until today, in the past 12 months, etc.).

Collection period: April 2022 - August 2022


  • Diseases and health conditions
  • Health
  • Lifestyle and social conditions

Data sources and methodology

Target population

The target population for the survey is adults 18 years of age and older living in the 10 provinces.

The observed population excludes: persons living in the three territories; persons living on reserves and other Indigenous settlements in the provinces; full-time members of the Canadian Forces; the institutionalized population and residents of certain remote regions.

Instrument design

The content for the survey was developed by Statistics Canada's Centre for Population Health Data, with input from the COVID-19 Immunity Task Force (CITF) and in consultation with Health Canada and the Public Health Agency of Canada.

The survey takes place in two parts: an electronic questionnaire about general health and exposure to COVID-19. The second part is two self-administered tests. The first is an at-home finger-prick blood test and the second is a PCR saliva test. The samples are sent to a lab to determine the presence of COVID-19 antibodies and active COVID-19 infections.


This is a sample survey with a cross-sectional design.

Dwelling Universe File (DUF) is used to select dwellings for persons 18 and over. Their contact information is then updated where possible using the 2021 Census database.

Sample design
It is a stratified random sample of dwellings, and age order selection will chose the respondent within the dwelling. The strata are based on the provinces and their census metropolitan area (CMA) regions within.

Sampling unit
The following sampling units are used in order to have accurate information on dwellings.

Residential Telephone Frame (RTF)
Dwelling Universe File (DUF)
Census 2021

Given the heterogeneity of COVID-19 in the population, particularly by geography, sub-provincial strata were created and the sample was allocated across these strata.

In the provinces, 27 strata were created from first subdividing each province into CMA and non-CMA areas. The CMAs of St. John's, Halifax, Saint John, Montréal, Québec, Toronto, Ottawa, Hamilton, Winnipeg, Regina, Saskatoon, Calgary, Edmonton and Vancouver form their own strata. From Ontario, Québec and British Columbia there are three additional strata of aggregated remaining CMA areas. Finally, there are 10 non-CMA regions, one for each province.

Stratification method
Typically, the population size of a stratum contributes to the sample size determination, where larger strata get more sample. This is then balanced by the need to ensure all strata receive sufficient sample to produce estimates. Increasing the sample in larger populations and increasing the sample in populations with more heterogeneity leads to more precise results at the national level. In this context, this means increasing the sample in large CMAs and strata with more COVID-19 confirmed cases leads to increased precision in the national estimates. Statistical sample allocation formulae were adapted to fit this specific situation, where the specific population size and proportion of confirmed COVID-19 cases for all strata were used in the allocation. Strata sample sizes were determined by a formula that favors larger population sizes and higher proportions of COVID-19 confirmed cases. The formula was then balanced to ensure sufficient sample was allocated to smaller strata with fewer cases. The results provide a sample allocation that will facilitate analysis for the hardest hit and larger strata with the added benefit of yielding more precise results nationally. Weighting that incorporates the sampling design will ensure that the final weighted sample is representative of the population.

Sampling and sub-sampling
Age-group definition:
The age groups defined in the proposal are quite broad being defined as 18-39, 40-59 and 60 and over, but analysis is not limited to these broad groups.

Within each household, one individual aged 18+ will be selected based on specific instructions within the letter they receive (or provided by the interviewer if they respond by phone). The instructions will use the age of household members to determine who is selected, and will vary from one household to another. For some households, the oldest member is selected, others the second oldest, or the youngest, etc. These letters are randomly assigned to the selected dwellings ensuring that the selected individual from within the dwelling is random. This method randomly selects individuals of all ages (18+) and given the proposed sample sizes, analysis can be conducted at much finer age groups for aggregated geographies. Weighting of the sample will also be performed for these finer age groups to ensure representativeness.

This comprehensive sample will provide nationally representative estimates as well as facilitating more granular estimation.

For those aged 18 and over, dwellings with a mailing address will be randomly selected, and one person from within the dwelling will be selected at random to participate. There will be strict instructions to ensure the selected individual does not choose a different person in the household.

A sample size of 100,000 people was selected for the survey, split between 3 approximately equal and overlapping waves of collection. Respondents of wave 1 of collection will receive a dried blood spot (DBS) antibody test, while respondents of wave 2 and 3 of collection (approximately 70,000 respondents) will receive a DBS antibody test and a PCR saliva test.

A response rate of 50% for the questionnaire, 30% for the DBS antibody test and 30% for the PCR saliva test is assumed. It is hypothesized that the prevalence of Canadians aged 18 years and older with antibodies against the SARS-CoV-2 virus during collection is approximately 90%. This represents persons that have previously had an infection from or have been vaccinated against SARS-CoV-2, and have antibodies against the virus. It is hypothesized that the prevalence of Canadians aged 18 years and older with an active SARS-CoV-2 infection during waves 2 and 3 of collection is less than 5%.

Data sources

Data collection for this reference period: 2022-04-01 to 2022-08-31

Responding to this survey is voluntary.

Data are collected directly from survey respondents.

1- Collection methods
A) Electronic questionnaire
The only contact with respondents is a letter sent through the mail with the DBS and PCR saliva test kits. The letter informs people living at the sampled address that a randomly selected person has been chosen to participate in the survey. On the letter there is a code which gives access to the online questionnaire. The electronic questionnaire takes on average 20 minutes to complete. Respondents are asked a series of questions covering a wide range of COVID-19 related questions as well as questions on chronic conditions, medication, health behaviour and interactions with the health care system.

i. Dried blood spots (DBS) sample
The respondents are asked to provide a small blood sample (via finger prick) to be tested for COVID-19 antibodies. Respondents must prick their finger and place up to 5 blood spots on a test strip.
ii. A saliva test (polymerase chain reaction (PCR)) which you will administer to yourself as soon as possible after completing the electronic questionnaire and the finger prick. You will then return the saliva test using the enclosed prepaid package. The lab will analyse the sample to determine if there is an active SARS-CoV-2 infection.

All materials related to the survey (initial letter, questionnaire, DBS, PCR instructions, etc.) are available in both official languages.

2- Follow-up methods
A Statistics Canada interviewer may call, email or text the respondent to follow up if we do not receive the respondent's complete questionnaire. Afterword, a tracking system will be implemented in order to flag the DBS cards and PCR tests that have not be sent. Follow up calls will be done by CCAHS staff.

3- Languages offered
The questionnaire was developed in both official languages.

4- Average time to complete the survey
The electronic questionnaire takes on average 20 minutes to complete and the dry blood spot test takes approximately 10 minutes.

Coverage Error
The CCAHS covers the population aged 18 and older living in the 10 provinces. Excluded from the survey's coverage are:
persons living in the three territories; persons living on reserves and other Indigenous settlements in the provinces; full-time members of the Canadian Forces; the institutionalized population and residents of certain remote regions. For the respondents 18 and over, this represents about 3% of the target population.

View the Questionnaire(s) and reporting guide(s) .

Error detection

Electronic files containing the daily transmissions of completed respondent survey records were combined to create the "raw" survey file. Before further processing, verification was performed to identify and eliminate potential duplicate records and to drop non-response and out-of-scope records.

In addition, some out-of-scope respondent records were found during the data clean-up stage. All respondent records that were determined to be out-of-scope and those records that contained no data were removed from the data file.

After the verification stage, editing was performed to identify errors and modify affected data at the individual variable level. The first editing step was to identify errors and determine which items from the survey output needed to be kept on the survey master file.

Subsequent to this, invalid characters were deleted and the remaining data items were formatted appropriately.


The metadata will be provided upon release.


The estimation of population characteristics from a sample survey is based on the premise that each person in the sample represents a certain number of other persons in addition to themselves. This number is referred to as the survey weight. The process of computing survey weights for each survey respondent involves several steps.

1) Each selected dwelling (in the household sample) is given an initial weight equal to the inverse of its selection probability from the sampling frame (DUF). Dwellings identified as out-of-scope during collection are dropped from the sample.

2) The weights for responding households are adjusted to represent the households that did not respond. Adjustment factors are calculated separately by province, and using a nonresponse model based on frame information.

3) The household weights are calibrated so that the sum of the weights match province level household size demographic counts.

4) Person weights are computed by multiplying the household level weights by the inverse of the probability of selecting the person within the household.

5) Each selected person in the targeted respondent sample is given an initial weight to the inverse of the selection probability from the person frame. Persons identified as out of scope are dropped from the sample.

6) The weights of respondents are adjusted to represent the persons which did not respond to the survey. Adjustment factors are computed separately by province, based on a nonresponse model using frame information.

7) The person weights coming from the household sample and the targeted respondent sample are pooled together.

8) The person weights are calibrated so that the sum of the weights match demographic population counts at the region by age group and by sex. The weights are also calibrated to demographic counts for large Census Metropolitan Areas (CMAs).

Sampling variance estimation is based on a resampling method called the bootstrap.

The Generalized Estimation System (G-Est) was used to generate the survey weights and bootstrap weights.

Quality evaluation

While quality assurance mechanisms are applied at all stages of the statistical process, the validation and detailed review of data by statisticians is the final verification of quality prior to release. Many validation measures were implemented, they include:

a. Verification of estimates through cross-tabulations

b. Consultation with stakeholders internal to Statistics Canada

c. Consultation with external stakeholders

Survey weights were also adjusted to minimise any potential bias that could arise from survey non-response; non-response adjustments and calibration using available auxiliary information were applied and are reflected in the survey weights provided with the data file.

Extensive validations of survey estimates were also performed and examined from a bias analysis perspective. Despite these rigorous adjustments and validations, the high non-response increases the risk of a remaining bias and the magnitude with which such a bias could impact estimates produced using the survey data. Therefore, users are advised to use the CCAHS data with caution, especially when creating estimates for small sub-populations or when comparing to other publicly available sources of data.

Disclosure control

Statistics Canada is prohibited by law from releasing any information it collects that could identify any person, business, or organization, unless consent has been given by the respondent or as permitted by the Statistics Act. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data.

Estimates with less than 5 positive counts in the numerator are suppressed for confidentiality reasons.

Estimates for which the effective sample size is below 30 are also suppressed.

Revisions and seasonal adjustment

This methodology does not apply.

Data accuracy

The survey aims at producing unbiased national and provincial estimates of good quality. Age group and sex breakdowns are also possible, but careful considerations of sample size and quality indicator (confidence interval) must be taken into account.

In all, 106,000 persons were selected to participate in the Canadian COVID-19 Antibody and Health Survey cycle 2 (CCAHS-2) by two-stage sampling (household, then person).

Response Rate

The metadata will be provided upon release.

Coverage Error

The CCAHS covers the population aged 18 and over living in the 10 provinces. Excluded from the survey's coverage are: persons living in the three territories; persons under the age of 18; persons living on reserves and other Indigenous settlements in the provinces; full-time members of the Canadian Forces; persons living in institutions and residents of certain remote regions.

Non-sampling Errors

Much time and effort was devoted to reducing non-sampling errors in the survey. Quality assurance measures were applied at each stage of the data collection and processing cycle to control the quality of the data.

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