Accounting for model uncertainty in estimating global burden of disease | Zendy

David M. Vock | Zendy; Elizabeth A. Atchison | Zendy; Julie Legler | Zendy; David R. J. McClure | Zendy; Jamie C. Carlyle | Zendy; Elysia N Jeavons | Zendy; Anthony Burton | Zendy

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Accounting for model uncertainty in estimating global burden of disease

Author(s) -

David M. Vock,

Elizabeth A. Atchison,

Julie Legler,

David R. J. McClure,

Jamie C. Carlyle,

Elysia N Jeavons,

Anthony Burton

Publication year - 2011

Publication title -

bulletin of the world health organization

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.459

H-Index - 168

eISSN - 1564-0604

pISSN - 0042-9686

DOI - 10.2471/blt.09.073577

Subject(s) - covariate , confidence interval , credible interval , statistics , econometrics , bayesian probability , disease burden , sampling (signal processing) , bayes' theorem , bayesian hierarchical modeling , bayesian inference , medicine , population , environmental health , mathematics , computer science , filter (signal processing) , computer vision

To illustrate the effects of failing to account for model uncertainty when modelling is used to estimate the global burden of disease, with specific application to childhood deaths from rotavirus infection.

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