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Abstract
The COVID-19 pandemic has exposed the deep links and fragility of economic, health
and social systems. Discussions of reconstruction include renewed interest in moving
beyond GDP and recognizing “human capital”, “brain capital”, “mental capital”, and
“wellbeing” as assets fundamental to economic reimagining, productivity, and prosperity.
This paper describes how the conceptualization of Mental Wealth provides an important
framing for measuring and shaping social and economic renewal to underpin healthy,
productive, resilient, and thriving communities. We propose a transdisciplinary application
of systems modeling to forecast a nation's Mental Wealth and understand the extent
to which policy-mediated changes in economic, social, and health sectors could enhance
collective mental health and wellbeing, social cohesion, and national prosperity.
Specifically, simulation will allow comparison of the projected impacts of a range
of cross-sector strategies (education sector, mental health system, labor market,
and macroeconomic reforms) on GDP and national Mental Wealth, and provide decision
support capability for future investments and actions to foster Mental Wealth. Finally,
this paper introduces the Mental Wealth Initiative that is harnessing complex systems
science to examine the interrelationships between social, commercial, and structural
determinants of mental health and wellbeing, and working to empirically challenge
the notion that fostering universal social prosperity is at odds with economic and
commercial interests.
Background Before 2020, mental disorders were leading causes of the global health-related burden, with depressive and anxiety disorders being leading contributors to this burden. The emergence of the COVID-19 pandemic has created an environment where many determinants of poor mental health are exacerbated. The need for up-to-date information on the mental health impacts of COVID-19 in a way that informs health system responses is imperative. In this study, we aimed to quantify the impact of the COVID-19 pandemic on the prevalence and burden of major depressive disorder and anxiety disorders globally in 2020. Methods We conducted a systematic review of data reporting the prevalence of major depressive disorder and anxiety disorders during the COVID-19 pandemic and published between Jan 1, 2020, and Jan 29, 2021. We searched PubMed, Google Scholar, preprint servers, grey literature sources, and consulted experts. Eligible studies reported prevalence of depressive or anxiety disorders that were representative of the general population during the COVID-19 pandemic and had a pre-pandemic baseline. We used the assembled data in a meta-regression to estimate change in the prevalence of major depressive disorder and anxiety disorders between pre-pandemic and mid-pandemic (using periods as defined by each study) via COVID-19 impact indicators (human mobility, daily SARS-CoV-2 infection rate, and daily excess mortality rate). We then used this model to estimate the change from pre-pandemic prevalence (estimated using Disease Modelling Meta-Regression version 2.1 [known as DisMod-MR 2.1]) by age, sex, and location. We used final prevalence estimates and disability weights to estimate years lived with disability and disability-adjusted life-years (DALYs) for major depressive disorder and anxiety disorders. Findings We identified 5683 unique data sources, of which 48 met inclusion criteria (46 studies met criteria for major depressive disorder and 27 for anxiety disorders). Two COVID-19 impact indicators, specifically daily SARS-CoV-2 infection rates and reductions in human mobility, were associated with increased prevalence of major depressive disorder (regression coefficient [ B ] 0·9 [95% uncertainty interval 0·1 to 1·8; p=0·029] for human mobility, 18·1 [7·9 to 28·3; p=0·0005] for daily SARS-CoV-2 infection) and anxiety disorders (0·9 [0·1 to 1·7; p=0·022] and 13·8 [10·7 to 17·0; p<0·0001]. Females were affected more by the pandemic than males ( B 0·1 [0·1 to 0·2; p=0·0001] for major depressive disorder, 0·1 [0·1 to 0·2; p=0·0001] for anxiety disorders) and younger age groups were more affected than older age groups (−0·007 [–0·009 to −0·006; p=0·0001] for major depressive disorder, −0·003 [–0·005 to −0·002; p=0·0001] for anxiety disorders). We estimated that the locations hit hardest by the pandemic in 2020, as measured with decreased human mobility and daily SARS-CoV-2 infection rate, had the greatest increases in prevalence of major depressive disorder and anxiety disorders. We estimated an additional 53·2 million (44·8 to 62·9) cases of major depressive disorder globally (an increase of 27·6% [25·1 to 30·3]) due to the COVID-19 pandemic, such that the total prevalence was 3152·9 cases (2722·5 to 3654·5) per 100 000 population. We also estimated an additional 76·2 million (64·3 to 90·6) cases of anxiety disorders globally (an increase of 25·6% [23·2 to 28·0]), such that the total prevalence was 4802·4 cases (4108·2 to 5588·6) per 100 000 population. Altogether, major depressive disorder caused 49·4 million (33·6 to 68·7) DALYs and anxiety disorders caused 44·5 million (30·2 to 62·5) DALYs globally in 2020. Interpretation This pandemic has created an increased urgency to strengthen mental health systems in most countries. Mitigation strategies could incorporate ways to promote mental wellbeing and target determinants of poor mental health and interventions to treat those with a mental disorder. Taking no action to address the burden of major depressive disorder and anxiety disorders should not be an option. Funding Queensland Health, National Health and Medical Research Council, and the Bill and Melinda Gates Foundation.
Evidence suggests that adverse experiences in childhood are associated with psychosis. To examine the association between childhood adversity and trauma (sexual abuse, physical abuse, emotional/psychological abuse, neglect, parental death, and bullying) and psychosis outcome, MEDLINE, EMBASE, PsychINFO, and Web of Science were searched from January 1980 through November 2011. We included prospective cohort studies, large-scale cross-sectional studies investigating the association between childhood adversity and psychotic symptoms or illness, case-control studies comparing the prevalence of adverse events between psychotic patients and controls using dichotomous or continuous measures, and case-control studies comparing the prevalence of psychotic symptoms between exposed and nonexposed subjects using dichotomous or continuous measures of adversity and psychosis. The analysis included 18 case-control studies (n = 2048 psychotic patients and 1856 nonpsychiatric controls), 10 prospective and quasi-prospective studies (n = 41 803) and 8 population-based cross-sectional studies (n = 35 546). There were significant associations between adversity and psychosis across all research designs, with an overall effect of OR = 2.78 (95% CI = 2.34–3.31). The integration of the case-control studies indicated that patients with psychosis were 2.72 times more likely to have been exposed to childhood adversity than controls (95% CI = 1.90–3.88). The association between childhood adversity and psychosis was also significant in population-based cross-sectional studies (OR = 2.99 [95% CI = 2.12–4.20]) as well as in prospective and quasi-prospective studies (OR = 2.75 [95% CI = 2.17–3.47]). The estimated population attributable risk was 33% (16%–47%). These findings indicate that childhood adversity is strongly associated with increased risk for psychosis.
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