Linked Life Data

18686234

Source:http://linkedlifedata.com/resource/pubmed/id/18686234

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2008-8-7
pubmed:abstractText
Political and health sector reforms, along with demographic, environmental and socio-economic transformations in the face of global warming, could cause the re-emergence of schistosomiasis in areas where transmission has been successfully interrupted and its emergence in previously non-endemic areas in China. In the present study, we used geographic information systems and remote sensing techniques to predict potential habitats of Oncomelania hupensis, the intermediate host snail of Schistosoma japonicum. Focussing on the Hongze, Baima and Gaoyou lakes in Jiangsu province in eastern China, we developed a model using the normalized difference vegetation index, a tasseled-cap transformed wetness index, and flooding areas to predict snail habitats at a small scale. Data were extracted from two Landsat images, one taken during a typical dry year and the other obtained three years later during a flooding event. An area of approximately 163.6 km2 was predicted as potential O. hupensis habitats around the three lakes, which accounts for 4.3% of the estimated snail habitats in China. In turn, these predicted snail habitats are risk areas for transmission of schistosomiasis, and hence illustrate the scale of the possible impact of climate change and other ecological transformations. The generated risk map can be used by health policy makers to guide mitigation policies targetting the possible spread of O. hupensis, and with the aim of containing the transmission of S. japonicum.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
1970-7096
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
1
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
85-92
pubmed:meshHeading
pubmed:year
2006
pubmed:articleTitle
Remote sensing for predicting potential habitats of Oncomelania hupensis in Hongze, Baima and Gaoyou lakes in Jiangsu province, China.
pubmed:affiliation
Jiangsu Institute of Parasitic Diseases, Wuxi 214064, People's Republic of China.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't