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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