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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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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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.
The authors declare no competing interests.
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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.
Estimated treatment effects and 95% confidence intervals, separately for men and women. Data analysis based on the HILDA Survey.
Estimated treatment effects and 95% confidence intervals, separately for five policy-relevant groups (separately according to sex). Data analysis based on the HILDA Survey.
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.
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