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Table 2 Summary of validation statistics for the geostatistical models described in Table 1.

From: Baseline spatial distribution of malaria prior to an elimination programme in Vanuatu

Model AUC Mean Error# (% prevalence) Mean Absolute Error* (% prevalence)
Model of P. vivax with distance to coastline fixed effect 0.867 5.07 1.30
Model of P. vivax with elevation fixed effect 0.857 5.46 1.33
Model of P. falciparum with distance to coastline fixed effect 0.821 0.39 0.55
Model of P. falciparum with elevation fixed effect 0.856 0.34 0.50
  1. AUC between 0.5 and 0.7 indicates a poor discriminative capacity; 0.7-0.9 indicate a reasonable capacity; and >0.9 indicate a very good capacity.
  2. # Mean error is a measure of the bias of predictions (the overall tendency to over or under predict).
  3. * Mean absolute error is a measure of overall precision (the average magnitude of error in individual predictions).