Skip to main content

Table 3 Performance metrics for the snail and environmental data models

From: Open-source environmental data as an alternative to snail surveys to assess schistosomiasis risk in areas approaching elimination

Performance metrics

Snail survey data models

Open-source environmental data models

 

Model 1

Model 2

Model 3

Model 1

Model 2

Model 3

AUC

0.852

0.849

0.843

0.800

0.784

0.798

Accuracy

0.845

0.859

0.845

0.887

0.887

0.887

Accuracy 95% CI

0.74–0.92

0.76–0.93

0.74–0.92

0.79–0.95

0.79–0.95

0.79–0.95

NIRa

0.859

0.859

0.859

0.859

0.859

0.859

P-Value (Accuracy > NIR)

0.706

0.583

0.706

0.316

0.316

0.316

Kappab

0.332

0.365

0.332

0.492

0.492

0.492

Sensitivity

0.400

0.400

0.400

0.500

0.500

0.500

Specificity

0.918

0.934

0.918

0.951

0.951

0.951

Pos Pred Value

0.444

0.500

0.444

0.625

0.625

0.625

Neg Pred Value

0.903

0.905

0.903

0.921

0.921

0.921

  1. aNo Information Rate
  2. bDue to the high degree of imbalance between the outcome classes across the study period, the Cohen’s kappa statistic is a useful metric for our models, as it helps to correct bias that results when rewarding the prediction of the majority class. The benchmark values outlined by Landis & Koch (1977) are useful here for determining the relative strength of the predictive models: < 0.00 = Poor; 0.00–0.20 = Slight; 0.21–0.40 = Fair; 0.41–0.60 = Moderate; 0.61–0.81 = Substantial; 0.81–1.0 = Almost Perfect