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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)

Ï„2 (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%.