Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: 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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
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
_version_ 1782375991334666240
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
work_keys_str_mv AT pigottdavidm prioritisinginfectiousdiseasemapping
AT howesrosalinde prioritisinginfectiousdiseasemapping
AT wiebeantoinette prioritisinginfectiousdiseasemapping
AT battlekatherinee prioritisinginfectiousdiseasemapping
AT goldingnick prioritisinginfectiousdiseasemapping
AT gethingpeterw prioritisinginfectiousdiseasemapping
AT dowellscottf prioritisinginfectiousdiseasemapping
AT faragtamerh prioritisinginfectiousdiseasemapping
AT garciaandresj prioritisinginfectiousdiseasemapping
AT kimballannm prioritisinginfectiousdiseasemapping
AT krauselkendall prioritisinginfectiousdiseasemapping
AT smithcraigh prioritisinginfectiousdiseasemapping
AT brookersimonj prioritisinginfectiousdiseasemapping
AT kyuhmweh prioritisinginfectiousdiseasemapping
AT vostheo prioritisinginfectiousdiseasemapping
AT murraychristopherjl prioritisinginfectiousdiseasemapping
AT moyescatherinel prioritisinginfectiousdiseasemapping
AT haysimoni prioritisinginfectiousdiseasemapping