Literature DB >> 9430528

Landscape characterization of peridomestic risk for Lyme disease using satellite imagery.

S W Dister1, D Fish, S M Bros, D H Frank, B L Wood.   

Abstract

Remotely sensed characterizations of landscape composition were evaluated for Lyme disease exposure risk on 337 residential properties in two communities of suburban Westchester County, New York. Properties were categorized as no, low, or high risk based on seasonally adjusted densities of Ixodes scapularis nymphs, determined by drag sampling during June and July 1990. Spectral indices based on Landsat Thematic Mapper data provided relative measures of vegetation structure and moisture (wetness), as well as vegetation abundance (greenness). A geographic information system (GIS) was used to spatially quantify and relate the remotely sensed landscape variables to risk category. A comparison of the two communities showed that Chappaqua, which had more high-risk properties (P < 0.001), was significantly greener and wetter than Armonk (P < 0.001). Furthermore, within Chappaqua, high-risk properties were significantly greener and wetter than lower-risk properties in this community (P < 0.01). The high-risk properties appeared to contain a greater proportion of broadleaf trees, while lower-risk properties were interpreted as having a greater proportion of nonvegetative cover and/or open lawn. The ability to distinguish these fine scale differences among communities and individual properties illustrates the efficiency of a remote sensing/GIS-based approach for identifying peridomestic risk of Lyme disease over large geographic areas.

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Mesh:

Year:  1997        PMID: 9430528     DOI: 10.4269/ajtmh.1997.57.687

Source DB:  PubMed          Journal:  Am J Trop Med Hyg        ISSN: 0002-9637            Impact factor:   2.345


  34 in total

1.  Integrating spatial epidemiology into a decision model for evaluation of facial palsy in children.

Authors:  Andrew M Fine; John S Brownstein; Lise E Nigrovic; Amir A Kimia; Karen L Olson; Amy D Thompson; Kenneth D Mandl
Journal:  Arch Pediatr Adolesc Med       Date:  2011-01

2.  Human risk of infection with Borrelia burgdorferi, the Lyme disease agent, in eastern United States.

Authors:  Maria A Diuk-Wasser; Anne Gatewood Hoen; Paul Cislo; Robert Brinkerhoff; Sarah A Hamer; Michelle Rowland; Roberto Cortinas; Gwenaël Vourc'h; Forrest Melton; Graham J Hickling; Jean I Tsao; Jonas Bunikis; Alan G Barbour; Uriel Kitron; Joseph Piesman; Durland Fish
Journal:  Am J Trop Med Hyg       Date:  2012-02       Impact factor: 2.345

3.  An Examination of the Demographic and Environmental Variables Correlated with Lyme Disease Emergence in Virginia.

Authors:  Sara E Seukep; Korine N Kolivras; Yili Hong; Jie Li; Stephen P Prisley; James B Campbell; David N Gaines; Randel L Dymond
Journal:  Ecohealth       Date:  2015-07-11       Impact factor: 3.184

4.  Risk factors for lyme disease in Chester County, Pennsylvania.

Authors:  G Smith; E P Wileyto; R B Hopkins; B R Cherry; J P Maher
Journal:  Public Health Rep       Date:  2001       Impact factor: 2.792

5.  Forest fragmentation predicts local scale heterogeneity of Lyme disease risk.

Authors:  John S Brownstein; David K Skelly; Theodore R Holford; Durland Fish
Journal:  Oecologia       Date:  2005-10-27       Impact factor: 3.225

6.  Predictive risk mapping of West Nile virus (WNV) infection in Saskatchewan horses.

Authors:  Tasha Y Epp; Cheryl Waldner; Olaf Berke
Journal:  Can J Vet Res       Date:  2011-07       Impact factor: 1.310

7.  Predicting the risk of Lyme disease: habitat suitability for Ixodes scapularis in the north central United States.

Authors:  Marta Guerra; Edward Walker; Carl Jones; Susan Paskewitz; M Roberto Cortinas; Ashley Stancil; Louisa Beck; Matthew Bobo; Uriel Kitron
Journal:  Emerg Infect Dis       Date:  2002-03       Impact factor: 6.883

Review 8.  Spatial dynamics of lyme disease: a review.

Authors:  Mary E Killilea; Andrea Swei; Robert S Lane; Cheryl J Briggs; Richard S Ostfeld
Journal:  Ecohealth       Date:  2008-06-05       Impact factor: 3.184

9.  Critical Evaluation of the Linkage Between Tick-Based Risk Measures and the Occurrence of Lyme Disease Cases.

Authors:  Lars Eisen; Rebecca J Eisen
Journal:  J Med Entomol       Date:  2016-09-01       Impact factor: 2.278

10.  Effect of Climate Change on Lyme Disease Risk in North America.

Authors:  John S Brownstein; Theodore R Holford; Durland Fish
Journal:  Ecohealth       Date:  2005-03       Impact factor: 3.184

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