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Table 4 Parameter estimates of non-spatial bivariate and Bayesian geostatistical logistic models with environmental and socio-economic predictors

From: Modelling the geographical distribution of soil-transmitted helminth infections in Bolivia

  Bivariate non-spatial Geostatistical model
  OR 95% CI OR 95% BCI
A. lumbricoides infection     
Survey period     
 Before 1995 1.00   1.00  
 1995 onwards 0.26 (0.24; 0.29)* 0.94 (0.64; 1.42)
Precipitation wettest quarter (mm)     
 <350 1.00   1.00  
 350-400 1.42 (1.23; 1.66)* 1.32 (0.56; 2.81)
 ≥400 12.25 (10.95; 13.70)* 12.52 (5.05; 25.56)*
    Median 95% BCI
σ 2 sp    1.11 (0.72; 2.00)
Range (km)    9.2 (1.3; 63.0)
T. trichiura infection     
Survey period     
 Before 1995 1.00   1.00  
 1995 onwards 0.33 (0.29; 0.37)* 0.85 (0.55; 1.30)
Altitude 0.33 (0.31; 0.36)* 0.37 (0.26; 0.56)*
    Median 95% BCI
σ 2 sp    1.29 (0.77; 2.23)
Range (km)    28.7 (3.2; 80.2)
Hookworm infection     
Survey period     
 Before 1995 1.00   1.00  
 1995 onwards 0.45 (0.41; 0.50) * 0.72 (0.12; 4.19)
Minimum temperature coldest month 6.25 (5.81; 6.72)* 11.35 (5.00; 22.20) *
    Median 95% BCI
σ 2 sp    3.07 (1.50; 7.44)
Range (km)    128.4 (39.8; 387.5)
  1. OR: odds ratio; 95% CI: lower and upper bound of a 95% confidence interval; 95% BCI: lower and upper bound of a 95% Bayesian credible interval.
  2. *Significant based on 95% CI or 95% BCI.