Moorthie, S; Blencowe, H; W Darlison, M; Lawn, JE; Mastroiacovo, P; Morris, JK; Modell, B; Congenital Disorders Expert Group
(2018)
An overview of concepts and approaches used in estimating the burden of congenital disorders globally.
J Community Genet, 9 (4).
pp. 347-362.
ISSN 1868-310X
https://doi.org/10.1007/s12687-017-0335-3
SGUL Authors: Morris, Joan Katherine
Abstract
Congenital disorders are an important cause of pregnancy loss, premature death and life-long disability. A range of interventions can greatly reduce their burden, but the absence of local epidemiological data on their prevalence and the impact of interventions impede policy and service development in many countries. In an attempt to overcome these deficiencies, we have developed a tool-The Modell Global Database of Congenital Disorders (MGDb) that combines general biological principles and available observational data with demographic data, to generate estimates of the birth prevalence and effects of interventions on mortality and disability due to congenital disorders. MGDb aims to support policy development by generating country, regional and global epidemiological estimates. Here we provide an overview of the concepts and methodological approach used to develop MGDb.
Item Type: |
Article
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Additional Information: |
© The Author(s) 2017
Open Access
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
Keywords: |
Congenital disorders, Epidemiology, Policy, Public health, Congenital Disorders Expert Group, 0604 Genetics |
SGUL Research Institute / Research Centre: |
Academic Structure > Population Health Research Institute (INPH) |
Journal or Publication Title: |
J Community Genet |
ISSN: |
1868-310X |
Language: |
eng |
Dates: |
Date | Event |
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October 2018 | Published | 11 October 2017 | Published Online | 30 June 2017 | Accepted |
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Publisher License: |
Creative Commons: Attribution 4.0 |
PubMed ID: |
29022220 |
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Go to PubMed abstract |
URI: |
https://openaccess.sgul.ac.uk/id/eprint/110345 |
Publisher's version: |
https://doi.org/10.1007/s12687-017-0335-3 |
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