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Table 3 Malaria parasitaemia risk factors as identified from single infection bivariate non-spatial and Bayesian multivariate exchangeable and geostatistical models (N = 11,481)

From: Bayesian geostatistical modelling of malaria and lymphatic filariasis infections in Uganda: predictors of risk and geographical patterns of co-endemicity

Covariates Bivariate logistic regression model (non-spatial)
OR 95% CI
Bayesian logistic regression model (exchangeable)
OR 95% BCI*
Bayesian geostatistical model (spatial)
OR 95% BCI*
Age group (5 - 9 yrs) 1.00 1.00 1.00
   10 - 14 yrs 0.67 (0.60 - 0.73) 0.66 (0.60 - 0.73) 0.66 (0.60 - 0.72)
   15 - 19 yrs 0.55 (0.47 - 0.63) 0.55 (0.46 - 0.64) 0.54 (0.47 - 0.64)
Sex (female) 1.00 1.00 1.00
   Male 1.12 (1.03 - 1.21) 1.14 (1.05 - 1.23) 1.14 (1.05 - 1.23)
Season (dry) 1.00 1.00 1.00
   Wet 2.30 (1.54 - 3.44) 2.23 (1.43 - 3.23) 2.33 (1.50 - 3.53)
NDVI (wet season) 1.03 (1.01 - 1.04) 1.02 (1.00 - 1.05) 1.02 (1.00- 1.05)
Precipitation (wet season) 1.01 (1.00 - 1.02) 1.00 (0.99 - 1.01) 1.00 (0.99 - 1.01)
LST diurnal range (annual) 0.94 (0.88 - 0.99) 1.04 (0.95 - 1.14) 1.04 (0.95 - 1.15)
   Mean (95% BCI) Mean (95% BCI)
τ2 (non-spatial variance) - 2.00 (1.34 - 2.82)  
σ (spatial variance) -   0.53 (0.36 - 0.77)
Range (in km) -   0.08 (0.02 - 0.65)
  1. Results are presented as odds ratios (OR) with their respective confidence intervals (95% CI) or Bayesian credible intervals (95% BCI). NDVI, normalized difference vegetation index; LST, land surface temperature. Range indicates the distance at which spatial correlation is lower than 5%.