An Integrative Metaregression Framework for Descriptive Epidemiology |
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| Editor:
| Flaxman, Abraham D.
Vos, Theo
Murray, Christopher J. L. |
| Series title: | Publications on Global Health, Institute for Health Metrics and Evaluation Ser. |
| ISBN: | 978-0-295-80430-9 |
| Publication Date: | Oct 2015 |
| Publisher: | University of Washington Press
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| Book Format: | Ebook |
| List Price: | USD $25.00 |
Book Description:
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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 more than 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. ...
More Description
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 more than 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.
An Integrative Metaregression 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 modeling 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 all available relevant data. Practical applications of the model to meta-analysis of several different diseases complement the theoretical foundations of what the editors call the integrative systems modeling 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.