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Predicting Ixodes scapularis abundance on white-tailed deer using geographic information systems
G E Glass1, F P Amerasinghe, J M Morgan
1Johns Hopkins University School of Hygiene and Public Health, Baltimore, Maryland.
The American Journal of Tropical Medicine and Hygiene
|November 1, 1994
Summary
Environmental factors influence the abundance of blacklegged ticks (Ixodes scapularis) on white-tailed deer. Understanding these associations can help predict tick exposure risks in different geographic areas.
Area of Science:
- Veterinary Entomology
- Environmental Science
- Epidemiology
Background:
- Ixodes scapularis ticks are vectors for numerous pathogens affecting wildlife and humans.
- White-tailed deer serve as hosts for immature and adult Ixodes scapularis.
- Environmental conditions significantly influence tick survival and host-seeking behavior.
Purpose of the Study:
- To investigate the relationship between environmental variables and Ixodes scapularis abundance on white-tailed deer.
- To identify key environmental factors associated with tick infestation on deer.
- To assess the utility of environmental data for predicting tick exposure risk.
Main Methods:
- Collection of 1,410 Ixodes scapularis ticks from 139 white-tailed deer in Kent County, Maryland.
- Utilizing a geographic information system to extract 41 environmental variables.
- Employing stepwise linear regression to analyze the association between tick abundance and environmental data.
Main Results:
- A significant association (R = 0.69) was found between Ixodes scapularis abundance and seven environmental variables.
- Tick abundance was negatively correlated with urban land use, wetlands, and saturated soils.
- Tick abundance was positively correlated with well-drained, sandy soils and low water tables.
Conclusions:
- Geographically referenced environmental data can be valuable for predicting tick vector exposure.
- Environmental factors like soil type and land use patterns are critical in determining tick abundance on deer.
- This research provides a framework for anticipating tick-borne disease risk in specific regions.