Predicting outbreaks: a spatial risk assessment of West Nile virus in British Columbia

Abstract Background West Nile virus (WNv) has recently emerged as a health threat to the North American population. After the initial disease outbreak in New York City in 1999, WNv has spread widely and quickly across North America to every contiguous American state and Canadian province, with the e...

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Main Authors: Tachiiri, Kaoru, Klinkenberg, Brian, Mak, Sunny, Kazmi, Jamil
Format: Other/Unknown Material
Language:English
Published: BioMed Central Ltd. 2006
Subjects:
Online Access:http://www.ij-healthgeographics.com/content/5/1/21
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spelling ftbiomed:oai:biomedcentral.com:1476-072X-5-21 2023-05-15T17:22:57+02:00 Predicting outbreaks: a spatial risk assessment of West Nile virus in British Columbia Tachiiri, Kaoru Klinkenberg, Brian Mak, Sunny Kazmi, Jamil 2006-05-16 http://www.ij-healthgeographics.com/content/5/1/21 en eng BioMed Central Ltd. http://www.ij-healthgeographics.com/content/5/1/21 Copyright 2006 Tachiiri et al; licensee BioMed Central Ltd. Research 2006 ftbiomed 2007-11-11T15:30:33Z Abstract Background West Nile virus (WNv) has recently emerged as a health threat to the North American population. After the initial disease outbreak in New York City in 1999, WNv has spread widely and quickly across North America to every contiguous American state and Canadian province, with the exceptions of British Columbia (BC), Prince Edward Island and Newfoundland. In this study we develop models of mosquito population dynamics for Culex tarsalis and C. pipiens , and create a spatial risk assessment of WNv prior to its arrival in BC by creating a raster-based mosquito abundance model using basic geographic and temperature data. Among the parameters included in the model are spatial factors determined from the locations of BC Centre for Disease Control mosquito traps ( e.g ., distance of the trap from the closest wetland or lake), while other parameters were obtained from the literature. Factors not considered in the current assessment but which could influence the results are also discussed. Results Since the model performs much better for C. tarsalis than for C. pipiens , the risk assessment is carried out using the output of C. tarsalis model. The result of the spatially-explicit mosquito abundance model indicates that the Okanagan Valley, the Thompson Region, Greater Vancouver, the Fraser Valley and southeastern Vancouver Island have the highest potential abundance of the mosquitoes. After including human population data, Greater Vancouver, due to its high population density, increases in significance relative to the other areas. Conclusion Creating a raster-based mosquito abundance map enabled us to quantitatively evaluate WNv risk throughout BC and to identify the areas of greatest potential risk, prior to WNv introduction. In producing the map important gaps in our knowledge related to mosquito ecology in BC were identified, as well, it became evident that increased efforts in bird and mosquito surveillance are required if more accurate models and maps are to be produced. Access to real time climatic data is the key for developing a real time early warning system for forecasting vector borne disease outbreaks, while including social factors is important when producing a detailed assessment in urban areas. Other/Unknown Material Newfoundland Prince Edward Island BioMed Central
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description Abstract Background West Nile virus (WNv) has recently emerged as a health threat to the North American population. After the initial disease outbreak in New York City in 1999, WNv has spread widely and quickly across North America to every contiguous American state and Canadian province, with the exceptions of British Columbia (BC), Prince Edward Island and Newfoundland. In this study we develop models of mosquito population dynamics for Culex tarsalis and C. pipiens , and create a spatial risk assessment of WNv prior to its arrival in BC by creating a raster-based mosquito abundance model using basic geographic and temperature data. Among the parameters included in the model are spatial factors determined from the locations of BC Centre for Disease Control mosquito traps ( e.g ., distance of the trap from the closest wetland or lake), while other parameters were obtained from the literature. Factors not considered in the current assessment but which could influence the results are also discussed. Results Since the model performs much better for C. tarsalis than for C. pipiens , the risk assessment is carried out using the output of C. tarsalis model. The result of the spatially-explicit mosquito abundance model indicates that the Okanagan Valley, the Thompson Region, Greater Vancouver, the Fraser Valley and southeastern Vancouver Island have the highest potential abundance of the mosquitoes. After including human population data, Greater Vancouver, due to its high population density, increases in significance relative to the other areas. Conclusion Creating a raster-based mosquito abundance map enabled us to quantitatively evaluate WNv risk throughout BC and to identify the areas of greatest potential risk, prior to WNv introduction. In producing the map important gaps in our knowledge related to mosquito ecology in BC were identified, as well, it became evident that increased efforts in bird and mosquito surveillance are required if more accurate models and maps are to be produced. Access to real time climatic data is the key for developing a real time early warning system for forecasting vector borne disease outbreaks, while including social factors is important when producing a detailed assessment in urban areas.
format Other/Unknown Material
author Tachiiri, Kaoru
Klinkenberg, Brian
Mak, Sunny
Kazmi, Jamil
spellingShingle Tachiiri, Kaoru
Klinkenberg, Brian
Mak, Sunny
Kazmi, Jamil
Predicting outbreaks: a spatial risk assessment of West Nile virus in British Columbia
author_facet Tachiiri, Kaoru
Klinkenberg, Brian
Mak, Sunny
Kazmi, Jamil
author_sort Tachiiri, Kaoru
title Predicting outbreaks: a spatial risk assessment of West Nile virus in British Columbia
title_short Predicting outbreaks: a spatial risk assessment of West Nile virus in British Columbia
title_full Predicting outbreaks: a spatial risk assessment of West Nile virus in British Columbia
title_fullStr Predicting outbreaks: a spatial risk assessment of West Nile virus in British Columbia
title_full_unstemmed Predicting outbreaks: a spatial risk assessment of West Nile virus in British Columbia
title_sort predicting outbreaks: a spatial risk assessment of west nile virus in british columbia
publisher BioMed Central Ltd.
publishDate 2006
url http://www.ij-healthgeographics.com/content/5/1/21
genre Newfoundland
Prince Edward Island
genre_facet Newfoundland
Prince Edward Island
op_relation http://www.ij-healthgeographics.com/content/5/1/21
op_rights Copyright 2006 Tachiiri et al; licensee BioMed Central Ltd.
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