What Can We Conclude from Death Registration? Improved Methods for Evaluating Completeness

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What Can We Conclude from Death Registration? Improved Methods for Evaluating Completeness

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Title: What Can We Conclude from Death Registration? Improved Methods for Evaluating Completeness
Author: Rajaratnam, Julie Knoll; Marcus, Jacob; Lopez, Alan D.; Murray, Christopher; Laakso, Thomas Andrew

Note: Order does not necessarily reflect citation order of authors.

Citation: Murray, Christopher J. L., Julie Knoll Rajaratnam, Jacob Marcus, Thomas Laakso, and Alan D. Lopez. 2010. What Can We Conclude from Death Registration? Improved Methods for Evaluating Completeness. PLoS Medicine 7: e1000262.
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Abstract: Background: One of the fundamental building blocks for determining the burden of disease in populations is to reliably
measure the level and pattern of mortality by age and sex. Where well-functioning registration systems exist, this task is
relatively straightforward. Results from many civil registration systems, however, remain uncertain because of a lack of
confidence in the completeness of death registration. Incomplete registration systems mean not all deaths are counted, and
resulting estimates of death rates for the population are then underestimated. Death distribution methods (DDMs) are a
suite of demographic methods that attempt to estimate the fraction of deaths that are registered and counted by the civil
registration system. Although widely applied and used, the methods have at least three types of limitations. First, a wide
range of variants of these methods has been applied in practice with little scientific literature to guide their selection.
Second, the methods have not been extensively validated in real population conditions where violations of the assumptions
of the methods most certainly occur. Third, DDMs do not generate uncertainty intervals.
Methods and Findings: In this paper, we systematically evaluate the performance of 234 variants of DDM methods in three
different validation environments where we know or have strong beliefs about the true level of completeness of death
registration. Using these datasets, we identify three variants of the DDMs that generally perform the best. We also find that
even these improved methods yield uncertainty intervals of roughly 6 one-quarter of the estimate. Finally, we demonstrate
the application of the optimal variants in eight countries.
Conclusions: There continues to be a role for partial vital registration data in measuring adult mortality levels and trends,
but such results should only be interpreted alongside all other data sources on adult mortality and the uncertainty of the
resulting levels, trends, and age-patterns of adult death considered.
Published Version: doi:10.1371/journal.pmed.1000262
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2854130/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:11181059
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