Quantitative Approaches Towards Evaluating the Global Burden of Mental Illness

Abstract

Mental disorders are a leading cause of morbidity and mortality, affecting over one billion people worldwide. This burden, across all levels of socioeconomic development, is rising, yet the majority of people living with a mental disorder do not have access to adequate mental health services, with many facing stigma and high out-of-pocket payments for their care. Moreover, new and emerging dangers such as climate change and the COVID-19 pandemic pose additional stressors that threaten to exacerbate this burden. This dissertation aims to contribute to a better understanding of the evolving burden and dynamics of global mental health. The three studies it presents take as their focus different quantitative aspects of how the global burden is measured and evaluated, how it may be changing in response to global challenges, and how novel data sources may help in characterizing these changes, particularly in the absence of robust, high-frequency epidemiological surveillance. In Chapter 1, we investigated the share of the global burden of disease attributable to mental disorders and its associated economic value. To capture premature mortality due to mental disorders, as well as disability from associated causes, we proposed a composite approach to estimation. Using the most recently available estimates from the Global Burden of Disease study, we found that the burden of mental disorders is likely much higher than previously estimated, encompassing 16% of disability-adjusted life years in 2019. The economic value of this mental health burden was estimated to exceed 4.7 trillion United States dollars using a value of a statistical life year approach, accounting for regional losses that range from 3.9% of gross domestic product in Eastern Sub-Saharan Africa to 7.9% in High-income North America. In Chapter 2, we focused on Madagascar—a low-income country that is among the most vulnerable to the health consequences of climate change—and examined how health system visits for mental disorders may be shifting in response to climate change exposures such as changes in temperature, soil moisture, and the duration of tropical storms and cyclones. Drawing on meteorologic, geospatial, and health system data reported by 3,413 facilities from 2010 to 2020, we conducted an ecological analysis using negative binomial regression. Our results indicated that warmer temperatures in the cooler central highlands were associated with a decrease in monthly reported visits for mental disorders, while higher soil moisture could lead to an increase in visits, particular in high flood-risk regions and after a three-month lag, indicating potential variation in the impact of climate change on mental health needs and system responses. In Chapter 3, I investigated how Google search data for mental health symptoms might provide insight into the state of mental health during the COVID-19 pandemic. Using an interrupted time series approach with search data from Australia, Ireland, New Zealand, Singapore, the United Kingdom, and the United States, I found that announcements of COVID-19 vaccine safety and efficacy data in November 2020 were associated with immediate and sustained declines in search density for anxiety and depression. These declines in searches, if taken as a reasonable proxy for population mental health, underscore the importance of timely and transparent public health communication and illustrate the potential application of high-frequency internet search data for population mental health surveillance. Taken together, these chapters highlight different facets of the global burden of mental disorder and contribute to a growing effort to generate a more comprehensive understanding of the challenges posed by this burden at local, regional, and global levels.