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Volume 10, Number 4—April 2004

Research

Predicting Geographic Variation in Cutaneous Leishmaniasis, Colombia

Raymond J. King*Comments to Author , Diarmid H. Campbell-Lendrum†, and Clive R. Davies†
Author affiliations: *Centers for Disease Control and Prevention, Atlanta, Georgia, USA; †London School of Hygiene and Tropical Medicine, London, United Kingdom

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Table 3

Diagnostic statistics of predictive models for presence/absence of ACL transmissiona,b

Type of model Predictors used Accuracy measures
AUC Maximum κ Sensitivity (%) Specificity (%) PPV (%) NPV (%)
Single model for whole country
Elevation
0.66
0.23
59.9
65.8
41.3
80.3
Land cover
0.70
0.28
53.4
75.7
46.9
80.2
All
0.72
0.34
55.3
79.3
51.8
81.6
Combination of zonal models
Elevation
0.70
0.28
53.7
75.2
46.5
80.2
Land cover
0.82
0.46
67.0
80.6
58.1
85.9
All 0.84 0.54 62.8 89.1 69.8 85.6

aACL, American cutaneous leishmaniasis; AUC, area under receiver-operator curve; PPV, positive predictive value; NPV, negative predictive value. Sensitivity, specificity, PPV, and NPV are calculated at the probability threshold that gives the highest value of kappa.
bFor all comparisons of observations against predictions, χ2 > 79.2, df =1, p < 0.0001. κ values are given by (proportion correct – Proportion expected)/(1- proportion expected), where proportion correct = (a + d)/n, and proportion expected = (a + b) x (a + c) + (c + d) x (b + d)/n2. a = true positive predictions, b = false positive, c = false negative, d = true negative, n = total.

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