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Models for estimating and projecting global, regional and national prevalence and disease burden of asthma: protocol for a systematic review
INTRODUCTION: Models that have so far been used to estimate and project the prevalence and disease burden of asthma are in most cases inadequately described and irreproducible. We aim systematically to describe and critique the existing models in relation to their strengths, limitations and reproduc...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Open
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5791547/ https://www.ncbi.nlm.nih.gov/pubmed/28515197 http://dx.doi.org/10.1136/bmjopen-2016-015441 |
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author | Bhuia, Mohammad Romel Nwaru, Bright I Weir, Christopher J Sheikh, Aziz |
author_facet | Bhuia, Mohammad Romel Nwaru, Bright I Weir, Christopher J Sheikh, Aziz |
author_sort | Bhuia, Mohammad Romel |
collection | PubMed |
description | INTRODUCTION: Models that have so far been used to estimate and project the prevalence and disease burden of asthma are in most cases inadequately described and irreproducible. We aim systematically to describe and critique the existing models in relation to their strengths, limitations and reproducibility, and to determine the appropriate models for estimating and projecting the prevalence and disease burden of asthma. METHODS: We will search the following electronic databases to identify relevant literature published from 1980 to 2017: Medline, Embase, WHO Library and Information Services and Web of Science Core Collection. We will identify additional studies by searching the reference list of all the retrieved papers and contacting experts. We will include observational studies that used models for estimating and/or projecting prevalence and disease burden of asthma regarding human population of any age and sex. Two independent reviewers will assess the studies for inclusion and extract data from included papers. Data items will include authors’ names, publication year, study aims, data source and time period, study population, asthma outcomes, study methodology, model type, model settings, study variables, methods of model derivation, methods of parameter estimation and/or projection, model fit information, key findings and identified research gaps. A detailed critical narrative synthesis of the models will be undertaken in relation to their strengths, limitations and reproducibility. A quality assessment checklist and scoring framework will be used to determine the appropriate models for estimating and projecting the prevalence anddiseaseburden of asthma. ETHICS AND DISSEMINATION: We will not collect any primary data for this review, and hence there is no need for formal National Health Services Research Ethics Committee approval. We will present our findings at scientific conferences and publish the findings in the peer-reviewed scientific journal. |
format | Online Article Text |
id | pubmed-5791547 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BMJ Open |
record_format | MEDLINE/PubMed |
spelling | pubmed-57915472018-02-02 Models for estimating and projecting global, regional and national prevalence and disease burden of asthma: protocol for a systematic review Bhuia, Mohammad Romel Nwaru, Bright I Weir, Christopher J Sheikh, Aziz BMJ Open Epidemiology INTRODUCTION: Models that have so far been used to estimate and project the prevalence and disease burden of asthma are in most cases inadequately described and irreproducible. We aim systematically to describe and critique the existing models in relation to their strengths, limitations and reproducibility, and to determine the appropriate models for estimating and projecting the prevalence and disease burden of asthma. METHODS: We will search the following electronic databases to identify relevant literature published from 1980 to 2017: Medline, Embase, WHO Library and Information Services and Web of Science Core Collection. We will identify additional studies by searching the reference list of all the retrieved papers and contacting experts. We will include observational studies that used models for estimating and/or projecting prevalence and disease burden of asthma regarding human population of any age and sex. Two independent reviewers will assess the studies for inclusion and extract data from included papers. Data items will include authors’ names, publication year, study aims, data source and time period, study population, asthma outcomes, study methodology, model type, model settings, study variables, methods of model derivation, methods of parameter estimation and/or projection, model fit information, key findings and identified research gaps. A detailed critical narrative synthesis of the models will be undertaken in relation to their strengths, limitations and reproducibility. A quality assessment checklist and scoring framework will be used to determine the appropriate models for estimating and projecting the prevalence anddiseaseburden of asthma. ETHICS AND DISSEMINATION: We will not collect any primary data for this review, and hence there is no need for formal National Health Services Research Ethics Committee approval. We will present our findings at scientific conferences and publish the findings in the peer-reviewed scientific journal. BMJ Open 2017-05-17 /pmc/articles/PMC5791547/ /pubmed/28515197 http://dx.doi.org/10.1136/bmjopen-2016-015441 Text en © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted. This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Epidemiology Bhuia, Mohammad Romel Nwaru, Bright I Weir, Christopher J Sheikh, Aziz Models for estimating and projecting global, regional and national prevalence and disease burden of asthma: protocol for a systematic review |
title | Models for estimating and projecting global, regional and national prevalence and disease burden of asthma: protocol for a systematic review |
title_full | Models for estimating and projecting global, regional and national prevalence and disease burden of asthma: protocol for a systematic review |
title_fullStr | Models for estimating and projecting global, regional and national prevalence and disease burden of asthma: protocol for a systematic review |
title_full_unstemmed | Models for estimating and projecting global, regional and national prevalence and disease burden of asthma: protocol for a systematic review |
title_short | Models for estimating and projecting global, regional and national prevalence and disease burden of asthma: protocol for a systematic review |
title_sort | models for estimating and projecting global, regional and national prevalence and disease burden of asthma: protocol for a systematic review |
topic | Epidemiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5791547/ https://www.ncbi.nlm.nih.gov/pubmed/28515197 http://dx.doi.org/10.1136/bmjopen-2016-015441 |
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