Literature DB >> 24772672

Modeling Culex tarsalis abundance on the northern Colorado front range using a landscape-level approach.

Jessica A Schurich, Sunil Kumar, Lars Eisen, Chester G Moore.   

Abstract

Remote sensing and Geographic Information System (GIS) data can be used to identify larval mosquito habitats and predict species distribution and abundance across a landscape. An understanding of the landscape features that impact abundance and dispersal can then be applied operationally in mosquito control efforts to reduce the transmission of mosquito-borne pathogens. In an effort to better understand the effects of landscape heterogeneity on the abundance of the West Nile virus (WNV) vector Culex tarsalis, we determined associations between GIS-based environmental data at multiple spatial extents and monthly abundance of adult Cx. tarsalis in Larimer County and Weld County, CO. Mosquito data were collected from Centers for Disease Control and Prevention miniature light traps operated as part of local WNV surveillance efforts. Multiple regression models were developed for prediction of monthly Cx. tarsalis abundance for June, July, and August using 4 years of data collected over 2007-10. The models explained monthly adult mosquito abundance with accuracies ranging from 51-61% in Fort Collins and 57-88% in Loveland-Johnstown. Models derived using landscape-level predictors indicated that adult Cx. tarsalis abundance is negatively correlated with elevation. In this case, low-elevation areas likely more abundantly include habitats for Cx. tarsalis. Model output indicated that the perimeter of larval sites is a significant predictor of Cx. tarsalis abundance at a spatial extent of 500 m in Loveland-Johnstown in all months examined. The contribution of irrigated crops at a spatial extent of 500 m improved model fit in August in both Fort Collins and Loveland-Johnstown. These results emphasize the significance of irrigation and the manual control of water across the landscape to provide viable larval habitats for Cx. tarsalis in the study area. Results from multiple regression models can be applied operationally to identify areas of larval Cx. tarsalis production (irrigated crops lands and standing water) and assign priority in larval treatments to areas with a high density of larval sites at relevant spatial extents around urban locations.

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Year:  2014        PMID: 24772672     DOI: 10.2987/13-6373.1

Source DB:  PubMed          Journal:  J Am Mosq Control Assoc        ISSN: 8756-971X            Impact factor:   0.917


  9 in total

1.  Projection of Climate Change Influences on U.S. West Nile Virus Vectors.

Authors:  Heidi E Brown; Alex Young; Joceline Lega; Theodore G Andreadis; Jessica Schurich; Andrew Comrie
Journal:  Earth Interact       Date:  2015-12-10       Impact factor: 2.769

Review 2.  Risk factors for West Nile virus infection and disease in populations and individuals.

Authors:  Ruth R Montgomery; Kristy O Murray
Journal:  Expert Rev Anti Infect Ther       Date:  2015-01-30       Impact factor: 5.091

3.  Temporal and Spatial Variability of Entomological Risk Indices for West Nile Virus Infection in Northern Colorado: 2006-2013.

Authors:  Joseph R Fauver; Lauren Pecher; Jessica A Schurich; Bethany G Bolling; Mike Calhoon; Nathan D Grubaugh; Kristen L Burkhalter; Lars Eisen; Barbara G Andre; Roger S Nasci; Adrienne LeBailly; Gregory D Ebel; Chester G Moore
Journal:  J Med Entomol       Date:  2016-03       Impact factor: 2.278

4.  Increased Human Incidence of West Nile Virus Disease near Rice Fields in California but Not in Southern United States.

Authors:  Tony J Kovach; A Marm Kilpatrick
Journal:  Am J Trop Med Hyg       Date:  2018-04-19       Impact factor: 2.345

5.  A comparison of least squares regression and geographically weighted regression modeling of West Nile virus risk based on environmental parameters.

Authors:  Abhishek K Kala; Chetan Tiwari; Armin R Mikler; Samuel F Atkinson
Journal:  PeerJ       Date:  2017-03-28       Impact factor: 2.984

6.  Modeling the abundance of two Rhagoletis fly (Diptera: Tephritidae) pests in Washington State, U.S.A.

Authors:  Tewodros T Wakie; Wee L Yee; Lisa G Neven; Sunil Kumar
Journal:  PLoS One       Date:  2019-06-03       Impact factor: 3.240

7.  Long-term surveillance defines spatial and temporal patterns implicating Culex tarsalis as the primary vector of West Nile virus.

Authors:  Brendan M Dunphy; Kristofer B Kovach; Ella J Gehrke; Eleanor N Field; Wayne A Rowley; Lyric C Bartholomay; Ryan C Smith
Journal:  Sci Rep       Date:  2019-04-29       Impact factor: 4.379

8.  Updated distribution maps of predominant Culex mosquitoes across the Americas.

Authors:  Morgan E Gorris; Andrew W Bartlow; Seth D Temple; Daniel Romero-Alvarez; Deborah P Shutt; Jeanne M Fair; Kimberly A Kaufeld; Sara Y Del Valle; Carrie A Manore
Journal:  Parasit Vectors       Date:  2021-10-23       Impact factor: 3.876

9.  Multi-Scale Clustering of Lyme Disease Risk at the Expanding Leading Edge of the Range of Ixodes scapularis in Canada.

Authors:  Marion Ripoche; Leslie Robbin Lindsay; Antoinette Ludwig; Nicholas H Ogden; Karine Thivierge; Patrick A Leighton
Journal:  Int J Environ Res Public Health       Date:  2018-03-27       Impact factor: 3.390

  9 in total

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