Linked Life Data

19706906

Source:http://linkedlifedata.com/resource/pubmed/id/19706906

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2009-8-26
pubmed:abstractText
Detailed knowledge of how local landscape patterns influence the distribution of Oncomelania hupensis, the intermediate host snail of Schistosoma japonicum, might facilitate more effective schistosomiasis control. We selected 12 villages in a mountainous area of Eryuan County, Yunnan Province, People's Republic of China, and developed Bayesian geostatistical models to explore heterogeneities of landscape composition in relation to distribution of O. hupensis. The best-fitting spatio-temporal model indicated that the snail density was significantly correlated with environmental factors. Specifically, snail density was positively correlated with wetness and inversely correlated with the normalized difference vegetation index and mollusciciding, and snail density decreased as landscape patterns became more uniform. However, the distribution of infected snails was not significantly correlated with any of the investigated environmental factors and landscape metrics. Our enhanced understanding of O. hupensis ecology is important for spatial targeting of schistosomiasis control interventions.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
AIM
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
1476-1645
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
81
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
416-23
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Landscape pattern analysis and Bayesian modeling for predicting Oncomelania hupensis distribution in Eryuan County, People's Republic of China.
pubmed:affiliation
Jiangsu Institute of Parasitic Diseases, Wuxi, People's Republic of China. jipdyk76@hotmail.com
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't