Household Impacts of COVID-19 Survey methodology

This publication presents results from the Household Impacts of COVID-19 Survey, Detailed Release, a topic on the Multipurpose Household Survey (MPHS). The MPHS, undertaken each financial year by the Australian Bureau of Statistics (ABS), is a supplement to the monthly Labour Force Survey (LFS) and is designed to collect statistics for a number of small, self-contained topics.

The COVID-19 topic was collected on the MPHS for the two months of May and June 2020 and was designed to provide information about how people in Australian households are faring in response to the changing social and economic environment caused by the COVID-19 pandemic.

The survey collected information from people about their level of concern, personal hygiene, intentions regarding flu vaccination, and actions taken (including changes to travel plans) in response to COVID-19, as well as whether they had received a Government stimulus payment and how they used it. Being a part of the MPHS, other information collected includes: their self-assessed health status, long term health conditions and private insurance as well as labour force status, whether currently studying for or completed a non-school qualification and other demographics.

This release forms part of a suite of additional products that the ABS is producing to measure the impacts of COVID-19 on the Australian economy and society.

For more information refer to https://www.abs.gov.au/covid19.

The scope of the Household Impacts of COVID-19 Survey, Detailed Release was restricted to people aged 18 years and over who were usual residents of private dwellings and excludes:

• members of the Australian permanent defence forces
• certain diplomatic personnel of overseas governments, customarily excluded from Census and estimated resident population counts
• overseas residents in Australia
• members of non-Australian defence forces (and their dependants)
• persons living in non-private dwellings such as hotels, university residences, boarding schools, hospitals, nursing homes, homes for people with disabilities, and prisons
• persons resident in the Indigenous Community Strata (ICS).
   

The scope included households residing in urban, rural, remote and very remote parts of Australia, except the ICS.

In the LFS, rules are applied which aim to ensure that each person in coverage is associated with only one dwelling, and hence has only one chance of selection in the survey. See Labour Force, Australia (cat. no. 6202.0) for more detail.

The Household Impacts of COVID-19 Survey, Detailed Release is one of a number of small, self-contained topics on the Multipurpose Household Survey (MPHS), conducted throughout Australia from July 2019 to June 2020. The MPHS is a supplement to the monthly LFS.

Each month, one eighth of the dwellings in the LFS sample were rotated out of the survey and selected for the MPHS. After the LFS had been fully completed for each person in scope and coverage, a usual resident aged 15 years or over was selected at random (based on a computer algorithm) and asked the additional MPHS questions in a personal interview. The Household Impacts of COVID-19 Survey, Detailed Release questions were only asked if the selected person was aged 18 years or over.

Data were collected using Computer Assisted Interviewing (CAI), whereby responses were recorded directly onto an electronic questionnaire in a notebook computer, with interviews conducted over the telephone.

After taking into account sample loss, the response rate for the May MPHS was 77%. In total, information was collected from 2,612 fully responding persons.

Weighting is the process of adjusting results from a sample survey to infer results for the total 'in-scope' population. To do this, a 'weight' is allocated to each enumerated person. The weight is a value which indicates the number of persons in the population represented by the sample person.

The first step in calculating weights for each unit is to assign an initial weight, which is the inverse of the probability of being selected in the survey. For example, if the probability of a person being selected in the survey was 1 in 600, then the person would have an initial weight of 600 (that is, they represent 600 people).

The initial weights were calibrated to align with independent estimates of the population of interest, referred to as 'benchmarks'. Weights calibrated against population benchmarks ensure that the survey estimates conform to the independently estimated distribution of the population rather than the distribution within the sample itself. Calibration to population benchmarks helps to compensate for over or under-enumeration of particular categories of persons/households which may occur due to either the random nature of sampling or non-response.

The survey was benchmarked to the Estimated Resident Population (ERP) living in private dwellings in each state and territory at May 2020. People living in Indigenous communities were excluded. These benchmarks are based on the 2016 Census.

While LFS benchmarks are revised every 5 years, to take into account the outcome of the 5-yearly rebasing of the ERP following the latest Census, the supplementary surveys and MPHS (from which the statistics in this publication are taken) are not. Small differences will therefore exist between the civilian population aged 15 years and over reflected in the LFS and other labour household surveys estimates, as well as over time.

Survey estimates of counts of persons are obtained by summing the weights of persons with the characteristic of interest.

To minimise the risk of identifying individuals in aggregate statistics, a technique is used to randomly adjust cell values. This technique is called perturbation. Perturbation involves a small random adjustment of the statistics and is considered the most satisfactory technique for avoiding the release of identifiable statistics while maximising the range of information that can be released. These adjustments have a negligible impact on the underlying pattern of the statistics.

After perturbation, a given published cell value will be consistent across all tables. However, adding up cell values to derive a total will not necessarily give the same result as published totals. The introduction of perturbation in publications ensures that these statistics are consistent with statistics released via services such as TableBuilder.

All sample surveys are subject to error which can be broadly categorised as either sampling error or non-sampling error. For more information refer to the Technical Note (cat. no. 4839.0).

Information recorded in this survey is 'as reported' by respondents, and may differ from that which might be obtained from other sources or via other methodologies. This factor should be considered when interpreting the estimates in this publication.

Information was collected on respondents' perception of their health status. Perceptions are influenced by a number of factors and can change quickly. Care should therefore be taken when analysing or interpreting the data.

Caution should be taken when comparing across ABS surveys. Estimates from the Household Impacts of COVID-19 Survey, Detailed Release differ from earlier releases due to differences in survey mode, methodology and questionnaire design.

Since the MPHS is conducted as a supplement to the LFS, data items collected in the LFS are also available in this publication. However, there are some important differences between the two surveys. The LFS had a response rate of over 90% compared to the MPHS response rate of 77%. The scope of the MPHS and the LFS also differ (refer to these sections above). Due to the differences between the samples, data from the MPHS and the LFS are weighted separately. Differences may therefore be found in the estimates for those data items collected in the LFS and published as part of the Household Impacts of COVID-19 Survey, Detailed Release.

Australian geographic data are classified according to the Australian Statistical Geography Standard (ASGS): Volume 1 - Main Structure and Greater Capital City Statistical Areas, July 2016 (cat. no. 1270.0.55.001). Remoteness areas are classified according to the Australian Statistical Geography Standard (ASGS): Volume 5 - Remoteness Structure, July 2016 (cat. no. 1270.0.55.005).

Country of birth data are classified according to the Standard Australian Classification of Countries (SACC), 2016 (cat. no. 1269.0).

Education data are classified according to the Australian Standard Classification of Education ASCED, 2001 (cat. no 1272.0). The ASCED is a national standard classification which can be applied to all sectors of the Australian education system including schools, vocational education and training and higher education. The ASCED comprises two classifications: Level of Education and Field of Education.

Data Cubes containing all tables for this publication in Excel spreadsheet format are available from the Data downloads section. The spreadsheets present tables of proportions, and their corresponding Margins of Error (MoEs).

As well as the statistics included in this and related publications, the ABS may have other relevant data available on request. Subject to confidentiality and sampling variability constraints, tables can be tailored to individual requirements. A list of data items from this survey is available from the Data downloads section. All enquiries should be made to the National Information and Referral Service on 1300 135 070, or email client.services@abs.gov.au.

ABS surveys draw extensively on information provided by individuals, businesses, governments and other organisations. Their continued cooperation is very much appreciated and without it, the wide range of statistics published by the ABS would not be available. Information received by the ABS is treated in strict confidence as required by the Census and Statistics Act 1905.

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