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Prioritising Infectious Disease Mapping
BACKGROUND: Increasing volumes of data and computational capacity afford unprecedented opportunities to scale up infectious disease (ID) mapping for public health uses. Whilst a large number of IDs show global spatial variation, comprehensive knowledge of these geographic patterns is poor. Here we u...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4464526/ https://www.ncbi.nlm.nih.gov/pubmed/26061527 http://dx.doi.org/10.1371/journal.pntd.0003756 |
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author | Pigott, David M. Howes, Rosalind E. Wiebe, Antoinette Battle, Katherine E. Golding, Nick Gething, Peter W. Dowell, Scott F. Farag, Tamer H. Garcia, Andres J. Kimball, Ann M. Krause, L. Kendall Smith, Craig H. Brooker, Simon J. Kyu, Hmwe H. Vos, Theo Murray, Christopher J. L. Moyes, Catherine L. Hay, Simon I. |
author_facet | Pigott, David M. Howes, Rosalind E. Wiebe, Antoinette Battle, Katherine E. Golding, Nick Gething, Peter W. Dowell, Scott F. Farag, Tamer H. Garcia, Andres J. Kimball, Ann M. Krause, L. Kendall Smith, Craig H. Brooker, Simon J. Kyu, Hmwe H. Vos, Theo Murray, Christopher J. L. Moyes, Catherine L. Hay, Simon I. |
author_sort | Pigott, David M. |
collection | PubMed |
description | BACKGROUND: Increasing volumes of data and computational capacity afford unprecedented opportunities to scale up infectious disease (ID) mapping for public health uses. Whilst a large number of IDs show global spatial variation, comprehensive knowledge of these geographic patterns is poor. Here we use an objective method to prioritise mapping efforts to begin to address the large deficit in global disease maps currently available. METHODOLOGY/PRINCIPAL FINDINGS: Automation of ID mapping requires bespoke methodological adjustments tailored to the epidemiological characteristics of different types of diseases. Diseases were therefore grouped into 33 clusters based upon taxonomic divisions and shared epidemiological characteristics. Disability-adjusted life years, derived from the Global Burden of Disease 2013 study, were used as a globally consistent metric of disease burden. A review of global health stakeholders, existing literature and national health priorities was undertaken to assess relative interest in the diseases. The clusters were ranked by combining both metrics, which identified 44 diseases of main concern within 15 principle clusters. Whilst malaria, HIV and tuberculosis were the highest priority due to their considerable burden, the high priority clusters were dominated by neglected tropical diseases and vector-borne parasites. CONCLUSIONS/SIGNIFICANCE: A quantitative, easily-updated and flexible framework for prioritising diseases is presented here. The study identifies a possible future strategy for those diseases where significant knowledge gaps remain, as well as recognising those where global mapping programs have already made significant progress. For many conditions, potential shared epidemiological information has yet to be exploited. |
format | Online Article Text |
id | pubmed-4464526 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-44645262015-06-25 Prioritising Infectious Disease Mapping Pigott, David M. Howes, Rosalind E. Wiebe, Antoinette Battle, Katherine E. Golding, Nick Gething, Peter W. Dowell, Scott F. Farag, Tamer H. Garcia, Andres J. Kimball, Ann M. Krause, L. Kendall Smith, Craig H. Brooker, Simon J. Kyu, Hmwe H. Vos, Theo Murray, Christopher J. L. Moyes, Catherine L. Hay, Simon I. PLoS Negl Trop Dis Research Article BACKGROUND: Increasing volumes of data and computational capacity afford unprecedented opportunities to scale up infectious disease (ID) mapping for public health uses. Whilst a large number of IDs show global spatial variation, comprehensive knowledge of these geographic patterns is poor. Here we use an objective method to prioritise mapping efforts to begin to address the large deficit in global disease maps currently available. METHODOLOGY/PRINCIPAL FINDINGS: Automation of ID mapping requires bespoke methodological adjustments tailored to the epidemiological characteristics of different types of diseases. Diseases were therefore grouped into 33 clusters based upon taxonomic divisions and shared epidemiological characteristics. Disability-adjusted life years, derived from the Global Burden of Disease 2013 study, were used as a globally consistent metric of disease burden. A review of global health stakeholders, existing literature and national health priorities was undertaken to assess relative interest in the diseases. The clusters were ranked by combining both metrics, which identified 44 diseases of main concern within 15 principle clusters. Whilst malaria, HIV and tuberculosis were the highest priority due to their considerable burden, the high priority clusters were dominated by neglected tropical diseases and vector-borne parasites. CONCLUSIONS/SIGNIFICANCE: A quantitative, easily-updated and flexible framework for prioritising diseases is presented here. The study identifies a possible future strategy for those diseases where significant knowledge gaps remain, as well as recognising those where global mapping programs have already made significant progress. For many conditions, potential shared epidemiological information has yet to be exploited. Public Library of Science 2015-06-10 /pmc/articles/PMC4464526/ /pubmed/26061527 http://dx.doi.org/10.1371/journal.pntd.0003756 Text en © 2015 Pigott et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Pigott, David M. Howes, Rosalind E. Wiebe, Antoinette Battle, Katherine E. Golding, Nick Gething, Peter W. Dowell, Scott F. Farag, Tamer H. Garcia, Andres J. Kimball, Ann M. Krause, L. Kendall Smith, Craig H. Brooker, Simon J. Kyu, Hmwe H. Vos, Theo Murray, Christopher J. L. Moyes, Catherine L. Hay, Simon I. Prioritising Infectious Disease Mapping |
title | Prioritising Infectious Disease Mapping |
title_full | Prioritising Infectious Disease Mapping |
title_fullStr | Prioritising Infectious Disease Mapping |
title_full_unstemmed | Prioritising Infectious Disease Mapping |
title_short | Prioritising Infectious Disease Mapping |
title_sort | prioritising infectious disease mapping |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4464526/ https://www.ncbi.nlm.nih.gov/pubmed/26061527 http://dx.doi.org/10.1371/journal.pntd.0003756 |
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