Emerging Infectious Disease ISSN: 1080-6059

Using Remotely Sensed Data To Identify Areas at Risk for Hantavirus Pulmonary Syndrome

Gregory E. Glass*

, James E. Cheek†, Jonathan A. Patz*, Timothy M. Shields*, Timothy J. Doyle‡, Douglas A. Thoroughman†, Darcy K. Hunt†, Russell E. Enscore§, Kenneth L. Gage§, Charles Irland†, C. J. Peters¶, and Ralph Bryan§

Author affiliations: *The Johns Hopkins School of Hygiene and Public Health, Baltimore, Maryland, USA; †Indian Health Service, Albuquerque, New Mexico, USA; ‡Centers for Disease Control and Prevention, Albuquerque, New Mexico, USA; §Centers for Disease Control and Prevention, Ft. Collins, Colorado, USA; and ¶Centers for Disease Control and Prevention, Atlanta, Georgia, USA

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Figure 2

Receiver Operator Characteristic (ROC) function of the logistic model for HPS risk in the training area (closed squares) and overall for 1992 (open diamonds) as the threshold for predicted case households was varied from p = 0.00 - 0.85 in 0.05 increments. The ROC for normalized difference vegetation index model (triangles) had p values of 0.00 to 0.40 and multiple points occurred together. The early rapid loss of sensitivity for the NDVI model was the result of poor model specification.

Figure 2. Receiver Operator Characteristic (ROC) function of the logistic model for HPS risk in the training area (closed squares) and overall for 1992 (open diamonds) as the threshold for predicted case households was varied from p = 0.00 - 0.85 in 0.05 increments. The ROC for normalized difference vegetation index model (triangles) had p values of 0.00 to 0.40 and multiple points occurred together. The early rapid loss of sensitivity for the NDVI model was the result of poor model specification.

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