| Risk Assessment and Management Solutions for Arthropod-borne and Infectious Diseases |
Culex tarsalis and West Nile virus disease in the Front Range: Spatial risk
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We used Geographic Information System (GIS)-based data and mosquito abundance data from 13 sites sampled in 2006 to create a predictive model for abundance of Culex tarsalis in the Larimer-Boulder-Jefferson area |
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| a NS no significant relationship; * P < 0.05; ** P < 0.01; *** P< 0.001 | |
| b Cooling degree days = no. degree days exceeding a baseline of 65 °F | |
From: Winters, Eisen, Pape et al. 2008. Combining mosquito vector and human disease data for improved assessment
of spatial West Nile virus disease risk. American Journal of Tropical Medicine and Hygiene 78: 654-665.
| Abundance of Culex tarsalis was best explained by this equation: ln Cx. tarsalis per trap night = -3.2485 + (0.0122*cumulative June-August CDD) We then created a GIS-based model for projected entomological risk of exposure to Culex tarsalis in the Larimer-Boulder-Jefferson area of the northern Colorado Front Range based on the equation above and where non-irrigated areas located more than 500 m from perceived larval habitat are included in the lowest abundance category for the adult mosquitoes From: Winters, Eisen, Pape et al. 2008. Combining mosquito vector and human disease data for improved assessment of spatial West Nile virus disease risk. American Journal of Tropical Medicine and Hygiene 78: 654-665. |
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| The entomological risk map (left map) was then compared to a risk map for West Nile virus disease from 2002–2006 (right map) at the census tract scale. Most of the spatial patterns are similar but the disease risk map exaggerates risk in the western mountainous parts of the counties. This is because some census tracts are large and range across elevation gradients. The differences between these maps shows the importance of considering both human disease and where mosquito vectors are present and abudant when asessing risk for exposure to West Nile virus. From: Winters, Eisen, Pape et al. 2008. Combining mosquito vector and human disease data for improved assessment of spatial West Nile virus disease risk. American Journal of Tropical Medicine and Hygiene 78: 654-665. |
There are different strengths and weaknesses for risk maps based on human disease cases (which demonstrates pathogen exposure but are not informative in areas lacking a population base such as Rocky Mountain National Park) and risk of vector exposure (which is accurate regardless of the human population base but do not account for degree of human-vector contact which of course is a key factor for disease to occur). |
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| From: Winters, Eisen, Pape et al. 2008. Combining mosquito vector and human disease data for improved assessment of spatial West Nile virus disease risk. American Journal of Tropical Medicine and Hygiene 78: 664-665. | |||||||||||||||||||||||||||||||||
The entomological risk model performed well when applied to the western, mountainous part of Colorado and validated against epidemiologic data (see map). |
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| From: Winters, Eisen, Pape et al. 2008. Combining mosquito vector and human disease data for improved assessment of spatial West Nile virus disease risk. American Journal of Tropical Medicine and Hygiene 78: 654-665. | |
For the Larimer-Boulder-Weld area, incidence of reported WNV disease by census tract during 2003 and 2007 was positively associated with percentage of coverage by irrigated agricultural land within a census tract and negatively associated with distance to irrigated agricultural land. This incriminates irrigated agricultural land as a risk factor for exposure to mosquito vectors and WNV. |
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| From: Eisen, Barker, Moore et al. 2010. Irrigated agriculture is an important risk factor for West Nile virus disease in the hyperendemic Larimer-Boulder-Weld area of north-central Colorado. Journal of Medical Entomology 47: 939-951 |