Identifying Environmental Risk Factors of Cholera in a Coastal Area with Geospatial Technologies

Satellites contribute significantly to environmental quality and public health. Environmental factors are important indicators for the prediction of disease outbreaks. This study reveals the environmental factors associated with cholera in Zhejiang, a coastal province of China, using both Remote Se...
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Autor*in:	Min Xu [verfasserIn] Chunxiang Cao [verfasserIn] Duochun Wang [verfasserIn] Biao Kan [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2014

Schlagwörter:	cholera environmental factors remote sensing geographic information system (GIS) spatial analysis

Übergeordnetes Werk:	In: International Journal of Environmental Research and Public Health - MDPI AG, 2005, 12(2014), 1, Seite 354-370
Übergeordnetes Werk:	volume:12 ; year:2014 ; number:1 ; pages:354-370

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/ijerph120100354

Katalog-ID:	DOAJ048416908

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520			\|a Satellites contribute significantly to environmental quality and public health. Environmental factors are important indicators for the prediction of disease outbreaks. This study reveals the environmental factors associated with cholera in Zhejiang, a coastal province of China, using both Remote Sensing (RS) and Geographic information System (GIS). The analysis validated the correlation between the indirect satellite measurements of sea surface temperature (SST), sea surface height (SSH) and ocean chlorophyll concentration (OCC) and the local cholera magnitude based on a ten-year monthly data from the year 1999 to 2008. Cholera magnitude has been strongly affected by the concurrent variables of SST and SSH, while OCC has a one-month time lag effect. A cholera prediction model has been established based on the sea environmental factors. The results of hot spot analysis showed the local cholera magnitude in counties significantly associated with the estuaries and rivers.
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spelling	10.3390/ijerph120100354 doi (DE-627)DOAJ048416908 (DE-599)DOAJ691f3ac164b14490a324675d0621c77a DE-627 ger DE-627 rakwb eng Min Xu verfasserin aut Identifying Environmental Risk Factors of Cholera in a Coastal Area with Geospatial Technologies 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Satellites contribute significantly to environmental quality and public health. Environmental factors are important indicators for the prediction of disease outbreaks. This study reveals the environmental factors associated with cholera in Zhejiang, a coastal province of China, using both Remote Sensing (RS) and Geographic information System (GIS). The analysis validated the correlation between the indirect satellite measurements of sea surface temperature (SST), sea surface height (SSH) and ocean chlorophyll concentration (OCC) and the local cholera magnitude based on a ten-year monthly data from the year 1999 to 2008. Cholera magnitude has been strongly affected by the concurrent variables of SST and SSH, while OCC has a one-month time lag effect. A cholera prediction model has been established based on the sea environmental factors. The results of hot spot analysis showed the local cholera magnitude in counties significantly associated with the estuaries and rivers. cholera environmental factors remote sensing geographic information system (GIS) spatial analysis Medicine R Chunxiang Cao verfasserin aut Duochun Wang verfasserin aut Biao Kan verfasserin aut In International Journal of Environmental Research and Public Health MDPI AG, 2005 12(2014), 1, Seite 354-370 (DE-627)477992463 (DE-600)2175195-X 16604601 nnns volume:12 year:2014 number:1 pages:354-370 https://doi.org/10.3390/ijerph120100354 kostenfrei https://doaj.org/article/691f3ac164b14490a324675d0621c77a kostenfrei http://www.mdpi.com/1660-4601/12/1/354 kostenfrei https://doaj.org/toc/1660-4601 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2153 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2014 1 354-370
allfields_unstemmed	10.3390/ijerph120100354 doi (DE-627)DOAJ048416908 (DE-599)DOAJ691f3ac164b14490a324675d0621c77a DE-627 ger DE-627 rakwb eng Min Xu verfasserin aut Identifying Environmental Risk Factors of Cholera in a Coastal Area with Geospatial Technologies 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Satellites contribute significantly to environmental quality and public health. Environmental factors are important indicators for the prediction of disease outbreaks. This study reveals the environmental factors associated with cholera in Zhejiang, a coastal province of China, using both Remote Sensing (RS) and Geographic information System (GIS). The analysis validated the correlation between the indirect satellite measurements of sea surface temperature (SST), sea surface height (SSH) and ocean chlorophyll concentration (OCC) and the local cholera magnitude based on a ten-year monthly data from the year 1999 to 2008. Cholera magnitude has been strongly affected by the concurrent variables of SST and SSH, while OCC has a one-month time lag effect. A cholera prediction model has been established based on the sea environmental factors. The results of hot spot analysis showed the local cholera magnitude in counties significantly associated with the estuaries and rivers. cholera environmental factors remote sensing geographic information system (GIS) spatial analysis Medicine R Chunxiang Cao verfasserin aut Duochun Wang verfasserin aut Biao Kan verfasserin aut In International Journal of Environmental Research and Public Health MDPI AG, 2005 12(2014), 1, Seite 354-370 (DE-627)477992463 (DE-600)2175195-X 16604601 nnns volume:12 year:2014 number:1 pages:354-370 https://doi.org/10.3390/ijerph120100354 kostenfrei https://doaj.org/article/691f3ac164b14490a324675d0621c77a kostenfrei http://www.mdpi.com/1660-4601/12/1/354 kostenfrei https://doaj.org/toc/1660-4601 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2153 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2014 1 354-370
allfieldsGer	10.3390/ijerph120100354 doi (DE-627)DOAJ048416908 (DE-599)DOAJ691f3ac164b14490a324675d0621c77a DE-627 ger DE-627 rakwb eng Min Xu verfasserin aut Identifying Environmental Risk Factors of Cholera in a Coastal Area with Geospatial Technologies 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Satellites contribute significantly to environmental quality and public health. Environmental factors are important indicators for the prediction of disease outbreaks. This study reveals the environmental factors associated with cholera in Zhejiang, a coastal province of China, using both Remote Sensing (RS) and Geographic information System (GIS). The analysis validated the correlation between the indirect satellite measurements of sea surface temperature (SST), sea surface height (SSH) and ocean chlorophyll concentration (OCC) and the local cholera magnitude based on a ten-year monthly data from the year 1999 to 2008. Cholera magnitude has been strongly affected by the concurrent variables of SST and SSH, while OCC has a one-month time lag effect. A cholera prediction model has been established based on the sea environmental factors. The results of hot spot analysis showed the local cholera magnitude in counties significantly associated with the estuaries and rivers. cholera environmental factors remote sensing geographic information system (GIS) spatial analysis Medicine R Chunxiang Cao verfasserin aut Duochun Wang verfasserin aut Biao Kan verfasserin aut In International Journal of Environmental Research and Public Health MDPI AG, 2005 12(2014), 1, Seite 354-370 (DE-627)477992463 (DE-600)2175195-X 16604601 nnns volume:12 year:2014 number:1 pages:354-370 https://doi.org/10.3390/ijerph120100354 kostenfrei https://doaj.org/article/691f3ac164b14490a324675d0621c77a kostenfrei http://www.mdpi.com/1660-4601/12/1/354 kostenfrei https://doaj.org/toc/1660-4601 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2153 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2014 1 354-370
allfieldsSound	10.3390/ijerph120100354 doi (DE-627)DOAJ048416908 (DE-599)DOAJ691f3ac164b14490a324675d0621c77a DE-627 ger DE-627 rakwb eng Min Xu verfasserin aut Identifying Environmental Risk Factors of Cholera in a Coastal Area with Geospatial Technologies 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Satellites contribute significantly to environmental quality and public health. Environmental factors are important indicators for the prediction of disease outbreaks. This study reveals the environmental factors associated with cholera in Zhejiang, a coastal province of China, using both Remote Sensing (RS) and Geographic information System (GIS). The analysis validated the correlation between the indirect satellite measurements of sea surface temperature (SST), sea surface height (SSH) and ocean chlorophyll concentration (OCC) and the local cholera magnitude based on a ten-year monthly data from the year 1999 to 2008. Cholera magnitude has been strongly affected by the concurrent variables of SST and SSH, while OCC has a one-month time lag effect. A cholera prediction model has been established based on the sea environmental factors. The results of hot spot analysis showed the local cholera magnitude in counties significantly associated with the estuaries and rivers. cholera environmental factors remote sensing geographic information system (GIS) spatial analysis Medicine R Chunxiang Cao verfasserin aut Duochun Wang verfasserin aut Biao Kan verfasserin aut In International Journal of Environmental Research and Public Health MDPI AG, 2005 12(2014), 1, Seite 354-370 (DE-627)477992463 (DE-600)2175195-X 16604601 nnns volume:12 year:2014 number:1 pages:354-370 https://doi.org/10.3390/ijerph120100354 kostenfrei https://doaj.org/article/691f3ac164b14490a324675d0621c77a kostenfrei http://www.mdpi.com/1660-4601/12/1/354 kostenfrei https://doaj.org/toc/1660-4601 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2153 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2014 1 354-370
language	English
source	In International Journal of Environmental Research and Public Health 12(2014), 1, Seite 354-370 volume:12 year:2014 number:1 pages:354-370
sourceStr	In International Journal of Environmental Research and Public Health 12(2014), 1, Seite 354-370 volume:12 year:2014 number:1 pages:354-370
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institution	findex.gbv.de
topic_facet	cholera environmental factors remote sensing geographic information system (GIS) spatial analysis Medicine R
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authorswithroles_txt_mv	Min Xu @@aut@@ Chunxiang Cao @@aut@@ Duochun Wang @@aut@@ Biao Kan @@aut@@
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author	Min Xu
spellingShingle	Min Xu misc cholera misc environmental factors misc remote sensing misc geographic information system (GIS) misc spatial analysis misc Medicine misc R Identifying Environmental Risk Factors of Cholera in a Coastal Area with Geospatial Technologies
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topic_title	Identifying Environmental Risk Factors of Cholera in a Coastal Area with Geospatial Technologies cholera environmental factors remote sensing geographic information system (GIS) spatial analysis
topic	misc cholera misc environmental factors misc remote sensing misc geographic information system (GIS) misc spatial analysis misc Medicine misc R
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title	Identifying Environmental Risk Factors of Cholera in a Coastal Area with Geospatial Technologies
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title_sort	identifying environmental risk factors of cholera in a coastal area with geospatial technologies
title_auth	Identifying Environmental Risk Factors of Cholera in a Coastal Area with Geospatial Technologies
abstract	Satellites contribute significantly to environmental quality and public health. Environmental factors are important indicators for the prediction of disease outbreaks. This study reveals the environmental factors associated with cholera in Zhejiang, a coastal province of China, using both Remote Sensing (RS) and Geographic information System (GIS). The analysis validated the correlation between the indirect satellite measurements of sea surface temperature (SST), sea surface height (SSH) and ocean chlorophyll concentration (OCC) and the local cholera magnitude based on a ten-year monthly data from the year 1999 to 2008. Cholera magnitude has been strongly affected by the concurrent variables of SST and SSH, while OCC has a one-month time lag effect. A cholera prediction model has been established based on the sea environmental factors. The results of hot spot analysis showed the local cholera magnitude in counties significantly associated with the estuaries and rivers.
abstractGer	Satellites contribute significantly to environmental quality and public health. Environmental factors are important indicators for the prediction of disease outbreaks. This study reveals the environmental factors associated with cholera in Zhejiang, a coastal province of China, using both Remote Sensing (RS) and Geographic information System (GIS). The analysis validated the correlation between the indirect satellite measurements of sea surface temperature (SST), sea surface height (SSH) and ocean chlorophyll concentration (OCC) and the local cholera magnitude based on a ten-year monthly data from the year 1999 to 2008. Cholera magnitude has been strongly affected by the concurrent variables of SST and SSH, while OCC has a one-month time lag effect. A cholera prediction model has been established based on the sea environmental factors. The results of hot spot analysis showed the local cholera magnitude in counties significantly associated with the estuaries and rivers.
abstract_unstemmed	Satellites contribute significantly to environmental quality and public health. Environmental factors are important indicators for the prediction of disease outbreaks. This study reveals the environmental factors associated with cholera in Zhejiang, a coastal province of China, using both Remote Sensing (RS) and Geographic information System (GIS). The analysis validated the correlation between the indirect satellite measurements of sea surface temperature (SST), sea surface height (SSH) and ocean chlorophyll concentration (OCC) and the local cholera magnitude based on a ten-year monthly data from the year 1999 to 2008. Cholera magnitude has been strongly affected by the concurrent variables of SST and SSH, while OCC has a one-month time lag effect. A cholera prediction model has been established based on the sea environmental factors. The results of hot spot analysis showed the local cholera magnitude in counties significantly associated with the estuaries and rivers.
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title_short	Identifying Environmental Risk Factors of Cholera in a Coastal Area with Geospatial Technologies
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