+ Site Statistics
References:
54,258,434
Abstracts:
29,560,870
PMIDs:
28,072,757
+ Search Articles
+ PDF Full Text Service
How our service works
Request PDF Full Text
+ Follow Us
Follow on Facebook
Follow on Twitter
Follow on LinkedIn
+ Subscribe to Site Feeds
Most Shared
PDF Full Text
+ Translate
+ Recently Requested

Evaluating satellite sensor-derived indices for Lyme disease risk prediction



Evaluating satellite sensor-derived indices for Lyme disease risk prediction



Journal of Medical Entomology 43(2): 337-343



The wetness and greenness indices created using Landsat Thematic Mapper (TM) data from June 1995 and 1997 and July 2002 were tested for their ability to predict the location of sites with different levels of nymphal blacklegged tick, Ixodes scapularis Say, abundance in Rhode Island. In 1995, there were statistically significant differences in the mean of greenness and wetness indices between sites classified as low and moderate tick abundance areas (P = 0.005 and P = 0.041, respectively). In 1997, there also were statistically significant differences in the mean of the greenness and wetness indices, but these differences were between the grouping of low/moderate tick abundance and the high tick abundance category (P = 0.023 and P = 0.015, respectively). The same indices from the 2002 image were not significant predictors of tick abundance. It may be that Landsat TM-derived indices can be used to predict nymphal blacklegged tick abundance in years (e.g., 1995 and 1997) when tick abundance is lower than average but not in years when it is higher (e.g., 2002). Thus, it seems unlikely that these remotely sensed indices will be very useful for modeling nonperidomestic Lyme disease risk over a large region in Rhode Island.

Please choose payment method:






(PDF emailed within 0-6 h: $19.90)

Accession: 012786889

Download citation: RISBibTeXText

PMID: 16619620

DOI: 10.1603/0022-2585(2006)043[0337:essifl]2.0.co;2


Related references

Spectral band difference effects on vegetation indices derived from multiple satellite sensor data. Canadian Journal Of Remote Sensing: 3, 159-173, 2008

Landscape characterization of peridomestic risk for Lyme disease using satellite imagery. American Journal of Tropical Medicine and Hygiene 57(6): 687-692, 1998

Net reclassification indices for evaluating risk prediction instruments: a critical review. Epidemiology 25(1): 114-121, 2014

A multi-scale spatial approach for evaluating the impact of environmental change on Lyme disease risk. American Journal of Tropical Medicine & Hygiene 69(3 Supplement): 238-239, September, 2003

Satellite data and disease transmission by vectors: the creation of maps for risk prediction. Bulletin de la Societe de Pathologie Exotique 93(3): 207-207, 2000

Prediction of Culicoides-borne disease risk in Europe and North Africa using satellite imagery. Society for Veterinary Epidemiology and Preventive Medicine Proceedings of a meeting held at University of Warwick, England, 31st March 2nd April 2003: 253-264, 2003

Prediction of Lyme meningitis in children from a Lyme disease-endemic region: a logistic-regression model using history, physical, and laboratory findings. Pediatrics 117(1): E1-E7, 2006

Duration of tick attachment as a predictor of the risk of Lyme disease in an area in which Lyme disease is endemic. Journal of Infectious Diseases 175(4): 996-999, 1997

Geographical information systems and bootstrap aggregation (bagging) of tree-based classifiers for Lyme disease risk prediction in Trentino, Italian Alps. Journal of Medical Entomology 39(3): 485-492, 2002

Scales for evaluating the risk of interhospital transfer of critical patients: Severity indices or indices of the need for support. Medicina Intensiva 34(1): 79-80; Author Reply 80-1, 2010

Evaluating multiple indices from a canopy reflectance sensor to estimate corn N requirements. Agronomy Journal0: 6, 1553-1561, 2008

Classification and mapping of Varamin plain soils using satellite images derived from T.M. sensor. Iranian Journal of Natural Resources 56(3): 177-189, 2003

Surface phenology and satellite sensor-derived onset of greenness: An initial comparison. International Journal of Remote Sensing 20(17): 3451-3457, Nov 20, 1999

Evaluating the utility of satellite-based precipitation estimates for runoff prediction in ungauged basins. Regional hydrological impacts of climatic change: impact assessment and decision making: 273-282, 2005

Satellite-derived indices of stream discharge in Taylor Valley, Antarctica. Hydrological Processes 16(8): 1603-1616, 2002