Acceleration of Anxiety, Depression, and Suicide: Secondary Effects of Economic Disruption Related to COVID-19

Abstract

The SARS-CoV-2 (COVID-19) pandemic has contributed to increasing levels of anxiety, depression and other symptoms of stress around the globe. Reasons for this increase are understandable in the context of individual level factors such as self-isolation, lockdown, grief, survivor guilt, and other factors but also broader social and economic factors such as unemployment, insecure employment and resulting poverty, especially as the impacts of 2008 recession are still being felt in many countries further accompanied by social isolation. For those who are actively employed a fear of job and income loss and those who have actually become ill and recovered or those who have lost family and friends to illness, it is not surprising that they are stressed and feeling the psychological impact. Furthermore, multiple uncertainties contribute to this sense of anxiety. These fears and losses are major immediate stresses and undoubtedly can have long-term implications on mental health. Economic uncertainty combined with a sense of feeling trapped and resulting lack of control can contribute to helplessness and hopelessness where people may see suicide as a way out. Taking a macro view, we present a statistical model of the impact of unemployment, and national income declines, on suicide, separately for males and females over the life cycle in developed countries. This impact may reflect a potent combination of social changes and economic factors resulting in anomie. The governments and policymakers have a moral and ethical obligation to ensure the physical health and well-being of their populations. While setting in place preventive measures to avoid infections and then subsequent mortality, the focus on economic and social recovery is crucial. A global pandemic requires a global response with a clear inter-linked strategy for health as well as economic solutions. The models we have constructed represent predictions of suicide rates among the 38 highly industrialized OECD countries over a period of 18 years (2000–2017). Unemployment has a major effect on increasing suicide, especially in middle-aged groups. However, the impact of economic decline through losses of national income (GDP per capita) are substantially greater than those of unemployment and influence suicide throughout the life course, especially at the oldest ages.

Disrupted rhythms of life, work and entertainment and their associations with psychological impacts under the stress of the COVID-19 pandemic: A survey in 5854 Chinese people with different sociodemographic backgrounds

“…In this study, we found that people with low education levels or low income mostly suffer from irregular social rhythms, likely due to their weak competitiveness in the job market and inability to adapt to the new E-commerce models during the COVID-19 pandemic due to the isolation or even lockdown [ 26 ]. Moreover, they did not have sufficient judgment while facing various, overloaded and timely information on the COVID-19 pandemic, and easily felt stressed, depressive and anxious [ 27 ].…”

Drugs that offer the potential to reduce hospitalization and mortality from SARS-CoV-2 infection: The possible role of the sigma-1 receptor and autophagy

“…One of the main reasons is a lack in social connection and loneliness, which contributes to depression and subsequently leads to premature mortality, and this risk factor was indicated to be equivalent to grades 2 and 3 obesity [ 184 ]. Another source of pronounced depression and anxiety is economic damage that could further develop to long-term implications on mental health, resulting in shortened longevity and even suicide [ 185 ]. Not surprisingly, a prevalence of psychological and mental disorders in global level has been constantly increased following the pandemic with around 30% in each stress, anxiety, and depression category [ 186 ].…”

Cross-National Measures of the Intensity of COVID-19 Public Health Policies

“…In our set of time-varying predictors, we include raw COVID-19 cases and deaths to account for how governments enact reactive policies in response to rising case and death numbers, though we note that this is for the purposes of statistical adjustment, not to conclusively determine the effectiveness of the policies (Sebhatu et al 2020). We also include aggregated response data from Facebook surveys (using the percent who answer yes) about personal contact, financial anxiety, and general anxiety to explore how behavior and attitudes factor into policymak-ing (Brenner and Bhugra 2020). Likewise, we include Google data on retail, workplace, grocery, and parks mobility to investigate how governments use COVID-19 policies in response to changes in mobility (Maloney and Taskin 2020).…”