Abstract:This research delves into the intricate domain of Cost of Illness (COI) studies, also known as Burden of Disease (BOD), with a specific focus on depressive disorders. Employing a bottom-up approach, the study meticulously scrutinizes the economic implications of depression at various levels, emphasizing direct and indirect costs. The analysis integrates a detailed exploration of diverse discounting methods, including Net Present Value (NPV) and Discounted Cash Flow (DCF), with a particular emphasis on the Indian context to comprehend unique socio-economic factors.Methodologically, the study systematically reviews scientific literature over the past decade, utilizing databases such as Web of Science and Google Scholar. The inclusion criteria prioritize patient-based studies related to the cost of illness associated with depression. The research adopts a comprehensive approach, considering various methodologies and discounting techniques to enhance the understanding of economic implications.The comparative analysis of the total cost of illness across diverse countries unravels significant variations, highlighting the intricate nature of healthcare expenditures and economic structures. Specific breakdowns for each country consider factors suchas currency exchange rates, inflation, and Purchasing Power Parity (PPP) adjustments, shedding light on the complexities involved.The study across five countries highlights significant variations in depression-related costs. Direct medical costs have a mean of $42,668 (SD=16,940) with a high t-statistic of 27.83 (p-value 0.001), emphasizing substantial differences. Direct non-medicalcosts average $27,171 (SD=13,220) with a t-statistic of 14.07 (p-value 0.001), indicating a notable economic burden beyond medical expenses. Indirect costs related to depression stand at a mean of $63,816 (SD=25,230), with a t-statistic of 35.30 (p-value 0.001), highlighting significant impacts on productivity and societal costs. The total cost of illness, encompassing both direct and indirect costs, averages $113,590 (SD=43,990), with a t-statistic of 49.49 (p-value 0.001), reflecting the extensive economic implications of depression across these diverse nations.In conclusion, this comprehensive analysis contributes depth to our understanding of the economic impact of depressive disorders, providing valuable insights for policymakers, healthcare providers, and researchers. The research underscores the multifacetednature of the economic burden of depression, emphasizing variations across countries and advocating for comprehensive, context-specific approaches in assessing and addressing global implications. Acknowledging challenges with discounting methods, the paper identifies opportunities for refining methodologies and improving economic evaluations in the future, emphasizing the importance of nuanced insights for effective policymaking and healthcare strategies on a global scale.