An Integrative Metaregression Framework for Descriptive Epidemiology

To provide the tools and knowledge needed in efforts to improve the health of the world's populations, researchers collaborated on the Global Burden of Diseases, Injuries, and Risk Factors Study 2010. The study produced comprehensive estimates of over 200 diseases and health risk factors in 187 coun [...]
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To provide the tools and knowledge needed in efforts to improve the health of the world's populations, researchers collaborated on the Global Burden of Diseases, Injuries, and Risk Factors Study 2010. The study produced comprehensive estimates of over 200 diseases and health risk factors in 187 countries over two decades, results that will be used by governments and non-governmental agencies to inform priorities for global health research, policies, and funding. Integrated Meta-Regression Framework for Descriptive Epidemiology is the first book-length treatment of model-based meta-analytic methods for descriptive epidemiology used in the Global Burden of Disease Study 2010. In addition to collecting the prior work on compartmental modelling of disease, this book significantly extends the model, by formally connecting the system dynamics model of disease progression to a statistical model of epidemiological rates and demonstrates how the two models were combined to allow researchers to integrate relevant data.Practical applications of the model to meta-analysis of more than a dozen different diseases complement the theoretical foundations of the integrative systems modelling of disease in populations. The book concludes with a detailed description of the future directions for research in model-based meta-analysis of descriptive epidemiological data. Abraham Flaxman is assistant professor of global health in the Institute for Health Metrics and Evaluation at the University of Washington.