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      Predicting the Risk of Lyme Disease: Habitat Suitability for Ixodes scapularis in the North Central United States

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          Abstract

          The distribution and abundance of Ixodes scapularis were studied in Wisconsin, northern Illinois, and portions of the Upper Peninsula of Michigan by inspecting small mammals for ticks and by collecting questing ticks at 138 locations in state parks and natural areas. Environmental data were gathered at a local level (i.e., micro and meso levels), and a geographic information system (GIS) was used with several digitized coverages of environmental data to create a habitat profile for each site and a grid map for Wisconsin and Illinois. Results showed that the presence and abundance of I. scapularis varied, even when the host population was adequate. Tick presence was positively associated with deciduous, dry to mesic forests and alfisol-type soils of sandy or loam-sand textures overlying sedimentary rock. Tick absence was associated with grasslands, conifer forests, wet to wet/mesic forests, acidic soils of low fertility and a clay soil texture, and Precambrian bedrock. We performed a discriminant analysis to determine environmental differences between positive and negative tick sites and a regression equation to examine the probability of I. scapularis presence per grid. Both analyses indicated that soil order and land cover were the dominant contributors to tick presence. We then constructed a risk map indicating suitable habitats within areas where I. scapularis is already established. The risk map also shows areas of high probability the tick will become established if introduced. Thus, this risk analysis has both explanatory power and predictive capability.

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          Most cited references38

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          Ecology of Ixodes dammini-borne human babesiosis and Lyme disease.

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            Lyme borreliosis: relation of its causative agent to its vectors and hosts in North America and Europe.

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              Environmental risk factors for Lyme disease identified with geographic information systems.

              A geographic information system was used to identify and locate residential environmental risk factors for Lyme disease. Data were obtained for 53 environmental variables at the residences of Lyme disease case patients in Baltimore County from 1989 through 1990 and compared with data for randomly selected addresses. A risk model was generated combining the geographic information system with logistic regression analysis. The model was validated by comparing the distribution of cases in 1991 with another group of randomly selected addresses. In crude analyses, 11 environmental variables were associated with Lyme disease. In adjusted analyses, residence in forested areas (odds ratio [OR] = 3.7, 95% confidence interval [CI] = 1.2, 11.8), on specific soils (OR = 2.1, 95% CI = 1.0, 4.4), and in two regions of the county (OR = 3.5, 95% CI = 1.6, 7.4) (OR = 2.8, 95% CI = 1.0, 7.7) was associated with elevated risk of getting Lyme disease. Residence in highly developed regions was protective (OR = 0.3, 95% CI = 0.1, 1.0). The risk of Lyme disease in 1991 increased with risk categories defined from the 1989 through 1990 data. Combining a geographic information system with epidemiologic methods can be used to rapidly identify risk factors of zoonotic disease over large areas.
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                Author and article information

                Journal
                Emerg Infect Dis
                Emerging Infect. Dis
                EID
                Emerging Infectious Diseases
                Centers for Disease Control and Prevention
                1080-6040
                1080-6059
                March 2002
                : 8
                : 3
                : 289-297
                Affiliations
                [* ]University of Illinois College of Veterinary Medicine, Urbana, Illinois, USA
                []Michigan State University, East Lansing, Michigan, USA
                []University of Wisconsin, Madison, Wisconsin, USA
                [§ ]NASA Ames Research Center, Moffett Field, California
                Author notes
                Address for correspondence: Uriel Kitron, College of Veterinary Medicine, University of Illinois, 2001 S. Lincoln Ave MC-002, Urbana, IL 61802, USA; fax: 217-244-7421; e-mail: u-kitron@ 123456uiuc.edu
                Article
                01-0166
                10.3201/eid0803.010166
                2732460
                11927027
                061c6948-1227-4f95-adf9-120807d554fa
                History
                Categories
                Research

                Infectious disease & Microbiology
                lyme disease,ixodes scapularis,risk map,borrelia burgdorferi,geographic information systems (gis),north-central united states

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