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Table 3 Comparative ITS analysis model parametersa of population-standardized monthly notification rates of All Forms and bacteriologically-confirmed TB cases for a) intervention versus control districts; and b) employee ACF versus volunteer ACF

From: A comparative impact evaluation of two human resource models for community-based active tuberculosis case finding in Ho Chi Minh City, Viet Nam

 

Intervention versus Control

Employee ACF versus Volunteer ACF

IRRc

95% CI

p-valued

IRRc

95% CI

p-valued

All Forms TB

 Baseline rateb (β0)

14.931

[14.721, 15.144]

< 0.001

16.028

[15.643, 16.423]

< 0.001

 Pre-intervention trend, control (β1)

0.998

[0.998, 0.999]

< 0.001

0.997

[0.996, 0.998]

< 0.001

 Post-intervention step change, control (β2)

0.949

[0.921, 0.977]

< 0.001

1.011

[0.966, 1.059]

0.634

 Post-intervention trend, control (β3)

1.001

[0.999, 1.003]

0.432

1.002

[0.999, 1.004]

0.264

 Difference in baseline (β4)

0.987

[0.970, 1.006]

0.176

0.843

[0.814, 0.873]

< 0.001

 Difference in pre-intervention trends (β5)

0.999

[0.998, 1.000]

0.014

1.001

[1.000, 1.002]

0.174

 Difference in post-intervention step change (β6)

1.030

[0.992, 1.070]

0.123

0.953

[0.893, 1.018]

0.155

 Difference in post-intervention trends (β7)

1.004

[1.002, 1.006]

0.001

1.005

[1.001, 1.009]

0.021

Bacteriologically-confirmed TB

 Baseline rateb (β0)

8.793

[8.466, 9.133]

< 0.001

9.898

[9.559, 10.249]

< 0.001

 Pre-intervention trend, control (β1)

1.000

[0.999, 1.002]

0.968

0.996

[0.995, 0.998]

< 0.001

 Post-intervention step change, control (β2)

0.984

[0.920, 1.051]

0.628

0.996

[0.933, 1.064]

0.910

 Post-intervention trend, control (β3)

1.000

[0.996, 1.004]

0.892

1.010

[1.006, 1.014]

< 0.001

 Difference in baseline (β4)

1.023

[0.974, 1.074]

0.367

0.828

[0.787, 0.871]

< 0.001

 Difference in pre-intervention trends (β5)

0.997

[0.995, 0.999]

0.005

1.002

[1.000, 1.004]

0.034

 Difference in post-intervention step change (β6)

1.055

[0.969, 1.150]

0.218

1.098

[1.001, 1.204]

0.048

 Difference in post-intervention trends (β7)

1.008

[1.003, 1.014]

0.002

0.995

[0.989, 1.000]

0.069

  1. aThe parameters were obtained for a segmented regression model with the following structure: Yt = β0 + β1Tt + β2Xt + β3XtTt + β4Z + β5ZTt + β6ZXt + β6ZXtTt + ϵt. Here Yt is the outcome measure along time t; Tt is the monthly time counter; Xt indicates pre- and post-intervention periods, Z denotes the intervention cohort, and ZTt, ZXt, and ZXtTt are interaction terms. β0 to β3 relate to the control group as follows: β0, intercept; β1, pre-intervention trend; β2, post-intervention step change; β3, post-intervention trend. β4 to β7 represent differences between the control and intervention districts: β4, difference in baseline intercepts; β5, difference in pre-intervention trends; β6, difference in post-intervention step changes; β7, difference in post-intervention trend
  2. bThe baseline rate denotes case notification rates per month
  3. cIRR based on log-linear GEE Poisson regression with correlation structures determined by the Cumby-Huizinga test and Quasi-Information Criteria
  4. dWald test