Linked Life Data

17470917

Source:http://linkedlifedata.com/resource/pubmed/id/17470917

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2007-5-1
pubmed:abstractText
The appearance and spread of West Nile virus (WNv) in North America represent a recent example of how mosquito-borne diseases can develop in new settings. Understanding the epidemiological, biological, and geographical aspects of WNv is critical to developing a greater understanding of how newly emerging, migrating, or evolving vector-borne infectious disease can develop globally. To aid in the allocation of resources that mitigate future outbreaks and to better understand the geographic nature of WNv in the North American prairies, we employ spatial and nonspatial modeling methods to predict municipal-level risk of human WNv infection rates. We use data based on a combination of routinely collected electronic data sources. Our findings suggest general agreement between spatial and nonspatial approaches, and results are consistent with seroprevalence-based estimates. We suggest that spatial models based on administrative data can offer estimates of relative risk in human populations at less cost, and in a timelier manner than estimates based on serology specimens.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
0077-8923
pubmed:author
pubmed:issnType
Print
pubmed:volume
1102
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
135-48
pubmed:dateRevised
2007-11-15
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
West Nile virus: strategies for predicting municipal-level infection.
pubmed:affiliation
Public Health Surveillance, Alberta Health and Wellness, Edmonton, Alberta, Canada.
pubmed:publicationType
Journal Article, Review