Ecological niche modeling of Cryptococcus gattii in British Columbia, Canada.
Background: Cryptococcus gattii emerged on Vancouver Island, British Columbia (BC), Canada, in 1999, causing human and animal illness. Environmental sampling for C. gattii in southwestern BC has isolated the fungal organism from native vegetation, soil, air, and water. Objectives: Our aim was to hel...
| Publicado en: | Environmental Health Perspectives Vol. 118; no. 5; pp. 653 - 659 |
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| Autores principales: | , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
National Institute of Environmental Health Sciences
May2010
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=105068536&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105068536 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00916765 3B5 jtl: Environmental Health Perspectives issn: 00916765 maglogo: N pubinfo: dt: May2010 vid: 118 iid: 5 pid: 56539 pub: National Institute of Environmental Health Sciences place: Research Triangle Park, North Carolina artinfo: ui: 105068536 2010731744 10.1289/ehp.0901448 NLM20439176 PMC2866681 105068536 ppf: 653 ppct: 6 formats: fmt: @attributes: type: P tig: atl: Ecological niche modeling of Cryptococcus gattii in British Columbia, Canada. aug: au: Mak S Klinkenberg B Bartlett K Fyfe M affil: Epidemiology Services, British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada sug: subj: Cryptococcus Disease Surveillance Forecasting Algorithms British Columbia Ecology Funding Source Maps Models, Theoretical Software ab: Background: Cryptococcus gattii emerged on Vancouver Island, British Columbia (BC), Canada, in 1999, causing human and animal illness. Environmental sampling for C. gattii in southwestern BC has isolated the fungal organism from native vegetation, soil, air, and water. Objectives: Our aim was to help public health officials in BC delineate where C. gattii is currently established and forecast areas that could support C. gattii in the future. We also examined the utility of ecological niche modeling (ENM) based on human and animal C. gattii disease surveillance data. Methods: We performed ENM using the Genetic Algorithm for Rule-set Prediction (GARP) to predict the optimal and potential ecological niche areas of C. gattii in BC. Human and animal surveillance and environmental sampling data were used to build and test the models based on 15 predictor environmental data layers. Results: ENM provided very accurate predictions (> 98% accuracy, p-value < 0.001) for C. gattii in BC. The models identified optimal C. gattii ecological niche areas along the central and south eastern coast of Vancouver Island and within the Vancouver Lower Mainland. Elevation, biogeoclimatic zone, and January temperature were good predictors for identifying the ecological niche of C. gattii in BC. Conclusions: The use of human and animal case data for ENM proved useful and effective in identifying the ecological niche of C. gattii in BC. These results are shared with public health to increase public and physician awareness of cryptococcal disease in regions at risk of environmental colonization of C. gattii. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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