Global distribution of outbreaks of water-associated infectious diseases.
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.Based on the Global Infectious Disease and...
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doaj-c5e7f8079bd14e5190b4565c935b63fb2020-11-25T02:04:38ZengPublic Library of Science (PLoS)PLoS Neglected Tropical Diseases1935-27271935-27352012-01-0162e148310.1371/journal.pntd.0001483Global distribution of outbreaks of water-associated infectious diseases.Kun YangJeffrey LeJeuneDoug AlsdorfBo LuC K ShumSong LiangWater 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.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.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.http://europepmc.org/articles/PMC3279334?pdf=render |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Kun Yang Jeffrey LeJeune Doug Alsdorf Bo Lu C K Shum Song Liang |
spellingShingle |
Kun Yang Jeffrey LeJeune Doug Alsdorf Bo Lu C K Shum Song Liang Global distribution of outbreaks of water-associated infectious diseases. PLoS Neglected Tropical Diseases |
author_facet |
Kun Yang Jeffrey LeJeune Doug Alsdorf Bo Lu C K Shum Song Liang |
author_sort |
Kun Yang |
title |
Global distribution of outbreaks of water-associated infectious diseases. |
title_short |
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_sort |
global distribution of outbreaks of water-associated infectious diseases. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS Neglected Tropical Diseases |
issn |
1935-2727 1935-2735 |
publishDate |
2012-01-01 |
description |
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.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.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. |
url |
http://europepmc.org/articles/PMC3279334?pdf=render |
work_keys_str_mv |
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