Predicting the risk of Lyme disease: habitat suitability for Ixodes scapularis in the north central United States.
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 derived 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.
Guerra
Marta
M
College of Veterinary Medicine, University of Illinois, 2001 S. Lincoln Avenue MC-002, Urbana, IL 61802, USA.
Walker
Edward
E
Jones
Carl
C
Paskewitz
Susan
S
Cortinas
M Roberto
MR
Stancil
Ashley
A
Beck
Louisa
L
Bobo
Matthew
M
Kitron
Uriel
U
D000818:Animals; D004777:Environment; D006801:Humans; D007087:Illinois; D018884:Ixodes; D016015:Logistic Models; D008193:Lyme Disease / Q000635:transmission*; D008824:Michigan; D011237:Predictive Value of Tests; D012307:Risk Factors; D012987:Soil; D014922:Wisconsin
D012987:Soil