Cargando…

Global Distribution of Outbreaks of Water-Associated Infectious Diseases

BACKGROUND: Water plays an important role in the transmission of many infectious diseases, which pose a great burden on global public health. However, the global distribution of these water-associated infectious diseases and underlying factors remain largely unexplored. METHODS AND FINDINGS: Based o...

Descripción completa

Detalles Bibliográficos
Autores principales: Yang, Kun, LeJeune, Jeffrey, Alsdorf, Doug, Lu, Bo, Shum, C. K., Liang, Song
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3279334/
https://www.ncbi.nlm.nih.gov/pubmed/22348158
http://dx.doi.org/10.1371/journal.pntd.0001483
_version_ 1782223660639059968
author Yang, Kun
LeJeune, Jeffrey
Alsdorf, Doug
Lu, Bo
Shum, C. K.
Liang, Song
author_facet Yang, Kun
LeJeune, Jeffrey
Alsdorf, Doug
Lu, Bo
Shum, C. K.
Liang, Song
author_sort Yang, Kun
collection PubMed
description BACKGROUND: Water plays an important role in the transmission of many infectious diseases, which pose a great burden on global public health. However, the global distribution of these water-associated infectious diseases and underlying factors remain largely unexplored. METHODS AND FINDINGS: Based on the Global Infectious Disease and Epidemiology Network (GIDEON), a global database including water-associated pathogens and diseases was developed. In this study, reported outbreak events associated with corresponding water-associated infectious diseases from 1991 to 2008 were extracted from the database. The location of each reported outbreak event was identified and geocoded into a GIS database. Also collected in the GIS database included geo-referenced socio-environmental information including population density (2000), annual accumulated temperature, surface water area, and average annual precipitation. Poisson models with Bayesian inference were developed to explore the association between these socio-environmental factors and distribution of the reported outbreak events. Based on model predictions a global relative risk map was generated. A total of 1,428 reported outbreak events were retrieved from the database. The analysis suggested that outbreaks of water-associated diseases are significantly correlated with socio-environmental factors. Population density is a significant risk factor for all categories of reported outbreaks of water-associated diseases; water-related diseases (e.g., vector-borne diseases) are associated with accumulated temperature; water-washed diseases (e.g., conjunctivitis) are inversely related to surface water area; both water-borne and water-related diseases are inversely related to average annual rainfall. Based on the model predictions, “hotspots” of risks for all categories of water-associated diseases were explored. CONCLUSIONS: At the global scale, water-associated infectious diseases are significantly correlated with socio-environmental factors, impacting all regions which are affected disproportionately by different categories of water-associated infectious diseases.
format Online
Article
Text
id pubmed-3279334
institution National Center for Biotechnology Information
language English
publishDate 2012
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-32793342012-02-17 Global Distribution of Outbreaks of Water-Associated Infectious Diseases Yang, Kun LeJeune, Jeffrey Alsdorf, Doug Lu, Bo Shum, C. K. Liang, Song PLoS Negl Trop Dis Research Article BACKGROUND: Water plays an important role in the transmission of many infectious diseases, which pose a great burden on global public health. However, the global distribution of these water-associated infectious diseases and underlying factors remain largely unexplored. METHODS AND FINDINGS: Based on the Global Infectious Disease and Epidemiology Network (GIDEON), a global database including water-associated pathogens and diseases was developed. In this study, reported outbreak events associated with corresponding water-associated infectious diseases from 1991 to 2008 were extracted from the database. The location of each reported outbreak event was identified and geocoded into a GIS database. Also collected in the GIS database included geo-referenced socio-environmental information including population density (2000), annual accumulated temperature, surface water area, and average annual precipitation. Poisson models with Bayesian inference were developed to explore the association between these socio-environmental factors and distribution of the reported outbreak events. Based on model predictions a global relative risk map was generated. A total of 1,428 reported outbreak events were retrieved from the database. The analysis suggested that outbreaks of water-associated diseases are significantly correlated with socio-environmental factors. Population density is a significant risk factor for all categories of reported outbreaks of water-associated diseases; water-related diseases (e.g., vector-borne diseases) are associated with accumulated temperature; water-washed diseases (e.g., conjunctivitis) are inversely related to surface water area; both water-borne and water-related diseases are inversely related to average annual rainfall. Based on the model predictions, “hotspots” of risks for all categories of water-associated diseases were explored. CONCLUSIONS: At the global scale, water-associated infectious diseases are significantly correlated with socio-environmental factors, impacting all regions which are affected disproportionately by different categories of water-associated infectious diseases. Public Library of Science 2012-02-14 /pmc/articles/PMC3279334/ /pubmed/22348158 http://dx.doi.org/10.1371/journal.pntd.0001483 Text en Yang 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
Yang, Kun
LeJeune, Jeffrey
Alsdorf, Doug
Lu, Bo
Shum, C. K.
Liang, Song
Global Distribution of Outbreaks of Water-Associated Infectious Diseases
title Global Distribution of Outbreaks of Water-Associated Infectious Diseases
title_full Global Distribution of Outbreaks of Water-Associated Infectious Diseases
title_fullStr Global Distribution of Outbreaks of Water-Associated Infectious Diseases
title_full_unstemmed Global Distribution of Outbreaks of Water-Associated Infectious Diseases
title_short Global Distribution of Outbreaks of Water-Associated Infectious Diseases
title_sort global distribution of outbreaks of water-associated infectious diseases
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3279334/
https://www.ncbi.nlm.nih.gov/pubmed/22348158
http://dx.doi.org/10.1371/journal.pntd.0001483
work_keys_str_mv AT yangkun globaldistributionofoutbreaksofwaterassociatedinfectiousdiseases
AT lejeunejeffrey globaldistributionofoutbreaksofwaterassociatedinfectiousdiseases
AT alsdorfdoug globaldistributionofoutbreaksofwaterassociatedinfectiousdiseases
AT lubo globaldistributionofoutbreaksofwaterassociatedinfectiousdiseases
AT shumck globaldistributionofoutbreaksofwaterassociatedinfectiousdiseases
AT liangsong globaldistributionofoutbreaksofwaterassociatedinfectiousdiseases