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Quantifying the human impact of Melbourne’s 111-day hard lockdown experiment on the adult population

Nature Human Behaviour volume 7, pages 1652–1666 (2023)Cite this article

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Abstract

Lockdown was used worldwide to mitigate the spread of severe acute respiratory syndrome coronavirus 2 and was the cornerstone non-pharmaceutical intervention of zero-COVID strategies. Many previous impact evaluations of lockdowns are unreliable because lockdowns co-occurred with severe coronavirus disease related health and financial insecurities. This was not the case in Melbourne’s 111-day lockdown, which left other Australian jurisdictions unaffected. Interrogating nationally representative longitudinal survey data and quasi-experimental variation, and controlling for multiple hypothesis testing, we found that lockdown had some statistically significant, albeit small, impacts on several domains of human life. Women had lower mental health (−0.10 s.d., P = 0.043, 95% confidence interval (CI) = −0.21 to −0) and working hours (−0.13 s.d., P = 0.006, 95% CI = −0.22 to −0.04) but exercised more often (0.28 s.d., P < 0.001, 95% CI = 0.18 to 0.39) and received more government transfers (0.12 s.d., P = 0.048, 95% CI = 0.001 to 0.24). Men felt less part of their community (−0.20 s.d., P < 0.001, 95% CI = −0.30 to −0.10) and reduced working hours (−0.12 s.d., P = 0.004, 95% CI = −0.20 to −0.04). Heterogeneity analyses demonstrated that families with children were driving the negative results. Mothers had lower mental health (−0.27 s.d., P = 0.014, 95% CI = −0.48 to −0.06), despite feeling safer (0.26 s.d., P = 0.008, 95% CI = 0.07 to 0.46). Fathers increased their alcohol consumption (0.35 s.d., P = 0.002, 95% CI = 0.13 to 0.57). Some outcomes worsened with lockdown length for mothers. We discuss potential explanations for why parents were adversely affected by lockdown.

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Fig. 1: Description of the natural experiment with a timeline of COVID-19 daily infection numbers, lockdown dates and HILDA Survey data collection windows.
Fig. 2: Lockdown treatment effects (expressed in s.d.), separately for men and women.
Fig. 3: Lockdown treatment effects (expressed in s.d.), separately for men and women within socially relevant subgroups.
Fig. 4: Lockdown treatment effect (expressed in s.d.) for women for selected outcomes according to length of exposure and family status.
Fig. 5: Estimated treatment effect of lockdown (expressed in s.d.) for men and for selected outcomes according to the length of exposure and family status.

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Data availability

This paper uses unit record data from the HILDA Survey, conducted by the Melbourne Institute of Applied Economic and Social Research on behalf of the Australian Government DSS (release 20, https://dataverse.ada.edu.au/dataset.xhtml?persistentId=doi:10.26193/PI5LPJ, ADA Dataverse). The data used are available free of charge to researchers through the National Centre for Longitudinal Data Dataverse at the ADA (https://dataverse.ada.edu.au/dataverse/ncld). Access is subject to approval by the Australian Government DSS and is conditional on signing a licence specifying the terms of use. Source data are provided with this paper.

Code availability

All analyses were conducted with Stata 16.1MP. Replication codes, including codes on how to construct the working dataset and how to generate estimates, figures and tables, are accessible at https://www.dropbox.com/scl/fo/lmfiqa10lse6ymu22nwih/h?rlkey=mbgnrqwgds9czuvwyutlffdug&dl=0. This link will take the reader to a Dropbox folder.

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Acknowledgements

We received no specific funding for this work. This paper uses unit record data from the HILDA Survey conducted by the Melbourne Institute of Applied Economic and Social Research on behalf of the Australian Government Department of Social Services (DSS) (release 20; https://dataverse.ada.edu.au/dataset.xhtml?persistentId=doi:10.26193/PI5LPJ, Australian Data Archive (ADA) Dataverse). The findings and views reported in this paper are those of the authors and should not be attributed to the Australian Government, the DSS or the Melbourne Institute.

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Authors and Affiliations

  1. School of Economics, University of Sydney, Sydney, New South Wales, Australia

    Stefanie Schurer & Kadir Atalay

  2. IZA Institute of Labor Economics, Bonn, Germany

    Stefanie Schurer & Mark Wooden

  3. Australian Research Council Centre of Excellence, Families and Children over the Lifecourse, Sydney, New South Wales, Australia

    Stefanie Schurer, Kadir Atalay & Nick Glozier

  4. Sydney School of Medicine (Central Clinical School), Faculty of Medicine and Health, University of Sydney, Camperdown, New South Wales, Australia

    Nick Glozier

  5. Melbourne Institute of Applied Economic and Social Research, University of Melbourne, Parkville, Victoria, Australia

    Esperanza Vera-Toscano & Mark Wooden

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Contributions

S.S, K.A. and N.G. designed the research question. S.S. and K.A. designed the empirical strategy. K.A. estimated all regression models. All co-authors helped interpreting the estimation results. S.S. wrote the paper with inputs from A.A. on every aspect of the paper and inputs from M.W. on Melbourne’s lockdown strategy. E.V.-T. provided help with proof-checking references, figures and results. N.G. produced figures on the natural experiment and helped interpret effect sizes. All authors contributed to finalizing the paper.

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Correspondence to Stefanie Schurer.

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Nature Human Behaviour thanks Stephanie Rossouw and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Supplementary Tables 1–23 and Figs. 1–8.

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Source data

Source Data Fig. 1

Daily COVID-19 new infection numbers in Sydney and Melbourne. Data sourced from Anthony Macali, the curator of www.covidlive.com.au. Data made available under the CC-BY-4.0 site/licence.

Source Data Fig. 2

Estimated treatment effects and 95% confidence intervals, separately for men and women. Data analysis based on the HILDA Survey.

Source Data Fig. 3

Estimated treatment effects and 95% confidence intervals, separately for five policy-relevant groups (separately according to sex). Data analysis based on the HILDA Survey.

Source Data Fig. 4

Estimated treatment effects and 95% confidence intervals, separately for groups differentiated according to exposure length to lockdown (female sample). Data analysis based on the HILDA Survey.

Source Data Fig. 5

Estimated treatment effects and 95% confidence intervals, separately for groups differentiated according to exposure length to lockdown (male sample). Data analysis based on the HILDA Survey.

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Schurer, S., Atalay, K., Glozier, N. et al. Quantifying the human impact of Melbourne’s 111-day hard lockdown experiment on the adult population. Nat Hum Behav 7, 1652–1666 (2023). https://doi.org/10.1038/s41562-023-01638-1

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