The study presents updated projections of global mortality and burden of disease from 2002 to 2030, using a modified version of the original Global Burden of Disease (GBD) methodology. The updated projections use regression models based on more data, updated covariates, and enhanced methodologies. Three scenarios—baseline, pessimistic, and optimistic—are developed, reflecting different assumptions about future trends in socio-economic variables such as income, education, and tobacco use. The projections consider ten major cause clusters, including communicable, maternal, perinatal, and nutritional conditions (Group I), and non-communicable diseases (Group II), with diabetes and chronic respiratory diseases treated as separate categories. The regression equations used include variables such as income per capita, human capital, time, and tobacco use, with the elasticity of mortality rates with respect to GDP per capita and human capital being constant. The models also account for non-linear relationships between these variables and mortality rates. For low-income countries, separate projections are made based on observed relationships in a low-income dataset. The study also addresses the impact of diabetes and chronic respiratory diseases, using relative risk models to project mortality rates based on BMI trends. For chronic respiratory diseases, the study considers the impact of smoking and uses projections of smoking impact to estimate future mortality trends. Projections for income per capita, human capital, smoking impact, and technological change are developed, with income per capita estimated using GDP data and human capital measured by average years of schooling. Smoking impact is calculated based on lung cancer mortality rates and adjusted for regional differences. Technological change is measured using calendar year as a proxy. The study also addresses the impact of HIV/AIDS and tuberculosis, using different scenarios for treatment scale-up and coverage. Projections for tuberculosis consider the interaction between HIV and tuberculosis, with different scenarios based on the Global Plan to Stop TB. The study highlights the importance of considering regional differences and the impact of socioeconomic factors on mortality trends. Overall, the projections show that mortality rates for many causes are expected to decline with economic development, although some causes, such as injuries and HIV/AIDS, may see more stable or increasing trends depending on the scenario.The study presents updated projections of global mortality and burden of disease from 2002 to 2030, using a modified version of the original Global Burden of Disease (GBD) methodology. The updated projections use regression models based on more data, updated covariates, and enhanced methodologies. Three scenarios—baseline, pessimistic, and optimistic—are developed, reflecting different assumptions about future trends in socio-economic variables such as income, education, and tobacco use. The projections consider ten major cause clusters, including communicable, maternal, perinatal, and nutritional conditions (Group I), and non-communicable diseases (Group II), with diabetes and chronic respiratory diseases treated as separate categories. The regression equations used include variables such as income per capita, human capital, time, and tobacco use, with the elasticity of mortality rates with respect to GDP per capita and human capital being constant. The models also account for non-linear relationships between these variables and mortality rates. For low-income countries, separate projections are made based on observed relationships in a low-income dataset. The study also addresses the impact of diabetes and chronic respiratory diseases, using relative risk models to project mortality rates based on BMI trends. For chronic respiratory diseases, the study considers the impact of smoking and uses projections of smoking impact to estimate future mortality trends. Projections for income per capita, human capital, smoking impact, and technological change are developed, with income per capita estimated using GDP data and human capital measured by average years of schooling. Smoking impact is calculated based on lung cancer mortality rates and adjusted for regional differences. Technological change is measured using calendar year as a proxy. The study also addresses the impact of HIV/AIDS and tuberculosis, using different scenarios for treatment scale-up and coverage. Projections for tuberculosis consider the interaction between HIV and tuberculosis, with different scenarios based on the Global Plan to Stop TB. The study highlights the importance of considering regional differences and the impact of socioeconomic factors on mortality trends. Overall, the projections show that mortality rates for many causes are expected to decline with economic development, although some causes, such as injuries and HIV/AIDS, may see more stable or increasing trends depending on the scenario.