The local and global mental health effects of the Covid-19 pandemic

Abstract

This paper investigates the mental health effects of the local and global level Covid-19 pandemic among the UK population. To identify the effect, we use a high-quality dataset and an original strategy where we match the previous day's confirmed pandemic cases to a four-month panel of individual mental health information observed during the interview next day. The approach suggested in this paper aims to identify the average mental health effect on the overall population for the first and second waves of the pandemic. Using a linear fixed-effects model specification, we report robust findings that the average mental health in the UK is substantially reduced by the local and global pandemic. The total reduction in the average mental health of the UK population during our sampling period (April - June, 2020) is about 1.5% for the local and 2.4% for the global cases, which sum up to a 3.9% reduction. Extrapolating the total reduction in average mental health during the first wave of the pandemic (February - September, 2020) sums up to 2.8% while the effect is as large as 9.6% for the first and second waves together, which covers roughly a year since the start. An extensive robustness check suggests that the findings are stable with respect to alternative pandemic datasets, measures, estimators, functional forms, and time functions. The characteristics of the most vulnerable individuals (e.g., elderly, chronic illness, and job security concerns) and their household conditions (e.g., living alone and no private space) are explored. The paper discusses on the implications of the results.

Keywords: Covid-19; Mental Health; Pandemic; Vulnerable Individuals.

Fig. 1

Local and Global Covid-19 Cases Over Time and Sampling. Note: For Panels A and B, data points represent the raw (WHO, 2020) Covid-19 confirmed cases for the UK and whole world. The local and global number of cases are rescaled by 1000. The pandemic cases are represented by hollow circles and the cases corresponding to the interview days in Wave 1 - Wave 4 in Understanding Society (2020) dataset are presented with filled circles. The exact dates and the corresponding number of interviews conducted are given in Appendix A, Table A.1. For Panels C and D, data points are obtained by averaging GHQ36 scores by the residuals of the UK and Global cases. We obtain the residuals from regressions which are conditioned on the linear trend, the day of the week, and wave dummies. The lines represent the linear regressions which use the underlying 29 data points. The grey area represents the 95% confidence intervals.

Fig. A.1

Balance Tests 1: Number of Interviews and Previous Day Covid-19 Cases. Note: Authors’ own calculations from Understanding Society (Understanding Society, 2020) and World Health Organisation (WHO, 2020). We obtain the residuals of the #interviews, the local, and global pandemic cases conditional on the time trend, the day of the week, and wave dummies. The solid line is the linear regression based on the underlying 29 observations.

Fig. B.1

Distributions of GHQ36 across Waves. Note: Authors’ own calculations from Understanding Society (2020).