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Table 2 Variables and regression results from the bivariate non-spatial, Bayesian bivariate and multiple spatial logistic models.

From: Spatial analysis and mapping of malaria risk in Malawi using point-referenced prevalence of infection data

Variable Bivariate non-spatial model Bivariate spatial model Multiple spatial model
  OR (95% CI) OR (95% CI) OR (95% CI)
Elevation       
β1(elev1: < 650 m) 1.33 (1.21, 1.46) 1.98 (1.29, 3.05) 1.42 (1.13, 1.99)
β2 (elev2: 650–1110 m) 0.82 (0.75, 0.91) 2.08 (1.53, 2.81) 1.89 (1.38, 2.59)
Reference (elev3 : > 1110 m) 1.00   1.00   1.00  
Max. Temperature       
β3 (Tmax1: < 27°C) 0.77 (0.71, 0.83) 1.88 (1.52, 2.34) 1.68 (1.45, 2.73)
β4 (Tmax2: 27–32°C) 0.63 (0.59, 0.68) 0.85 (0.69, 1.02) 0.88 (0.43, 1.08)
Reference (Tmax3: > 32°C) 1.00   1.00   1.00  
Rainfall       
β5 (Rain1: < 880 mm) 1.15 (1.00, 1.31) 0.81 (0.64, 1.14)   
β6 (Rain2: 880–1180 mm) 1.20 (1.11, 1.29) 0.76 (0.54, 2.07)   
Reference (Rain3: > 1180 mm) 1.00   1.00    
PET       
β7 (PET1: < 1370 mm) 0.72 (0.61, 0.84) 0.49 (0.33, 1.22) 0.69 (0.21, 2.34)
β8 (PET2: 1370–1510 mm) 0.61 (0.58, 0.65) 0.38 (0.17, 0.89) 0.41 (0.14, 0.97)
Reference (PET3: > 1510 mm) 1.00   1.00   1.00  
Range (φ)      0.54 (0.23, 0.96)
Variance (σ2)      13.74 (8.80,20.16)
  1. OR = Odds ratio
  2. CI = Credible interval
  3. PET = Potential evapotranspiration