Table 3.

Implemented INLA models with the corresponding estimates for the study of nephropathia epidemica outbreaks in Western Europe (2004–2012).

Model	DIC	WAIC	Precision	Recall	Accuracy
Fixed effects	22,414 (22,296; 22,531)	57,700 (56,168; 59,231)	0.17 (0.16, 0.18)	0.76 (0.73, 0.79)	0.81 (0.80, 0.82)
Random effects	16,226 (16,200; 16,253)	17,367 (17,202; 17,531)	0.52 (0.50, 0.55)	0.54 (0.51, 0.57)	0.95 (0.95, 0.96)
Spatial (250)	14,895 (14,877; 14,913)	15,992 (15,898; 16,086)	0.49 (0.45, 0.53)	0.61 (0.60, 0.62)	0.95 (0.95, 0.95)
Spatial (500)	15,001 (14,983; 15,019)	16,068 (15,976; 16,160)	0.48 (0.45, 0.52)	0.61 (0.60, 0.62)	0.95 (0.95, 0.95)
Spatial (750)	15,090 (15,067; 15,113)	16,105 (16,012; 16,199)	0.47 (0.43, 0.51)	0.61 (0.60, 0.62)	0.95 (0.95, 0.95)
Spatiotemporal (250)	13,890 (13,838; 13,941)	13,731 (13,468; 13,994)	0.55 (0.54, 0.56)	0.62 (0.61, 0.63)	0.96 (0.96, 0.96)
Spatiotemporal (500)	14,020 (14,006; 14,035)	13,873 (13,821; 13,924)	0.56 (0.54, 0.57)	0.61 (0.60, 0.62)	0.96 (0.96, 0.96)
Spatiotemporal (750)	14,121 (14,076; 14,166)	14,061 (13,989; 14,134)	0.54 (0.53, 0.56)	0.61 (0.60, 0.62)	0.96 (0.96, 0.96)

Note: The deviance information criterion (DIC) and Watanabe–Akaike information criterion (WAIC) were calculated for integrated nested Laplace approximation (INLA) model comparison. Precision, recall, and accuracy were calculated to evaluate the predictive performance of each model. We report the mean estimate (as well as the 95% confidence interval) for ten replicates. Three mesh configurations with ranges of $250\mathrm{km}$, $500\mathrm{km}$, and $750\mathrm{km}$ (Figure S2B–D) were evaluated to assess their impact on the model prediction performance of the spatial and spatiotemporal models.