Skip to main content

Table 1 Model-estimated coefficients for fixed effects and their standard errors

From: A population-level analysis of armed conflict and diphtheria at the subnational level in the WHO African Region 2017–2024

Model name (dependent variable)

Predictor

variable

Coefficients

Std. error

z value

p value

ΔAIC

Vaccine (vaccine coverage)

Intercept

1.28

0.12

10.83

 < 0.001

 

log (conflict-fatalities per 100 k + 1)

 − 0.07

0.03

 − 2.48

0.013

 

Crude (diphtheria status)

Intercept

 − 3.03

0.26

 − 11.5

 < 0.001

 

Log (conflict-fatalities per 100 k + 1)

0.34

0.09

3.66

 < 0.001

 

RMCV-L (diphtheria status)

Intercept

 − 41.03

2.34

 − 17.55

 < 0.001

138.0

 

Vaccine coverage

0.14

0.01

12.80

 < 0.001

 
 

log(conflict-fatalities per 100 k + 1)

3.316

0.13

25.26

 < 0.001

 

RMCV-Q (diphtheria status)

Intercept

 − 30.15

2.32

 − 13.00

 < 0.001

0

 

Vaccine coverage rescaled

 − 2.44

0.65

 − 3.79

 < 0.001

 
 

Vaccine coverage^2 rescaled

 − 2.49

0.37

 − 6.69

 < 0.001

 
 

Log (conflict-fatalities per 100 k + 1)

3.41

0.13

25.46

 < 0.001

 

RMCV-C (diphtheria status)

Intercept

 − 71.79

3.78

 − 19.01

 < 0.001

287.7

 

Vaccine coverage: Med (50–80%)

45.67

3.35

13.62

 < 0.001

 
 

Vaccine coverage: Low (< 50%)

44.35

3.37

13.16

 < 0.001

 
 

Log (conflict-fatalities per 100 k + 1)

2.72

0.11

23.77

 < 0.001

 
  1. The vaccine model has DTP3 vaccination coverage as the outcome variable and uses a beta regression mixed-effects model with a logit link. All other models have diphtheria status (present or absent) as the outcome and use binomial fixed- or mixed-effects models with a logit link