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Table 2 Posterior estimates of the Bayesian spatio-temporal model parameters§

From: Spatio-temporal analysis of the main dengue vector populations in Singapore

  

Ae. aegypti

  

Ae. albopictus

 

2.5th percentile

50th

percentile

97.5th percentile

2.5th percentile

50th

percentile

97.5th percentile

Forest cover (within 300 m radius buffer)

− 0.140

− 0.074

− 0.008

− 0.018

0.031

0.080

Water cover (within 300 m radius buffer)

− 0.009

0.059

0.128

− 0.006

0.046

0.098

Grass cover (within 300 m radius buffer)

− 0.135

− 0.065

0.005

− 0.075

− 0.022

0.031

Managed vegetation cover (within 300 m radius buffer)

0.072

0.144

0.215

0.037

0.091

0.146

Drain line density (within 300 m radius buffer)

− 0.152

− 0.064

0.023

− 0.235

− 0.167

− 0.100

Distance to waterway

− 0.242

− 0.165

− 0.088

− 0.068

− 0.010

0.048

Distance to water area

0.072

0.152

0.232

− 0.076

− 0.014

0.047

Building age

0.351

0.421

0.490

0.270

0.323

0.376

Max temperature lag 1

− 0.037

− 0.027

− 0.018

− 0.027

− 0.016

− 0.004

(Max temperature lag 1)2

− 0.008

− 0.004

0.000

− 0.010

− 0.005

− 0.001

Mean relative humidity lag 1

− 0.020

− 0.011

− 0.002

− 0.032

− 0.020

− 0.008

Precipitation lag 1

0.003

0.010

0.016

− 0.018

− 0.010

− 0.002

Max temperature lag 2

− 0.040

− 0.031

− 0.021

− 0.029

− 0.017

− 0.005

(Max temperature lag 2)2

− 0.008

− 0.005

− 0.001

− 0.010

− 0.005

0.000

Mean relative humidity lag 2

− 0.015

− 0.006

0.003

− 0.021

− 0.009

0.003

Precipitation lag 2

0.006

0.012

0.018

− 0.003

0.005

0.013

Max temperature lag 3

− 0.032

− 0.023

− 0.013

− 0.025

− 0.013

− 0.002

(Max temperature lag 3)2

− 0.009

− 0.006

− 0.002

− 0.010

− 0.005

0.000

Mean relative humidity lag 3

− 0.016

− 0.007

0.002

− 0.021

− 0.008

0.004

Precipitation lag 3

0.007

0.013

0.020

0.007

0.015

0.023

Unstructured spatial effect (site)*

0.603

0.642

0.686

0.443

0.475

0.508

Unstructured spatial effect (planning area)*

0.383

0.514

0.708

0.240

0.337

0.487

Temporally structured effect**

0.048

0.058

0.071

0.076

0.092

0.113

Negative binomial size parameter

6.681

6.863

7.049

12.877

13.679

14.597

  1. All the environmental and anthropogenic variables were standardized to zero mean and unit variance prior to model fitting, and a quadratic term for each of the standardized temperature variables was also created to introduce nonlinear effects. Estimates are posterior median and equal tailed 95% credible intervals
  2. *Refers to the posterior estimate of the standard deviation of the spatial random effect
  3. ** Refers to the posterior estimate of the standard deviation of the independent second-order increment in the temporally structured effect
  4. §Each regression parameter (i.e. intercept and the coefficients of the fixed effects) was assigned a normal prior \({\text{N}}\left( {0,5^{2} } \right)\). We assumed a \({\text{logGamma}}\left( {1, 0.01} \right)\) prior on the logarithm of the precision of the spatial random effects and independent second-order increment in the temporally structured effect. The default penalized complexity prior in R-INLA was specified for the logarithm of the negative binomial size parameter