Alternative BAU: Immediate recovery upon cessation¶
We now consider the case where cessation of smoking results in immediate recovery, rather than taking 20 years for the tobacco-associated relative risks to decrease back to 1.0. The purpose here is to highlight how our assumptions about the BAU scenario can affect the predicted impact of an intervention.
The only changes that we need to make to the simulation definition are:
To use a different data artifact for these simulations, where the initial prevalence of tobacco use is only defined for 3 exposure levels: never smoked, current smoker, and former smoker; and
Set the recovery delay to 0 years.
Note
We could have used the same data artifact as in previous simulations, but then the tobacco component would have to manipulate the input data into the appropriate form. We instead choose to perform all input data manipulation before generating the data artifacts.
configuration:
input_data:
# Change this to "mslt_tobacco_maori_data_0-years.hdf" for the Maori
# population.
artifact_path: artifacts/mslt_tobacco_non-maori_0-years.hdf
# Other configuration settings ...
tobacco:
delay: 0
These simulations are already defined in the following files:
Tobacco eradication:
mslt_tobacco_maori_0-years_decreasing_erad.yamlmslt_tobacco_non-maori_0-years_decreasing_erad.yaml
Tobacco tax:
mslt_tobacco_maori_0-years_decreasing_tax.yamlmslt_tobacco_non-maori_0-years_decreasing_tax.yaml
Tobacco-free generation:
mslt_tobacco_maori_0-years_decreasing_tfg.yamlmslt_tobacco_non-maori_0-years_decreasing_tfg.yaml
Intervention comparison¶
If you run all of these simulations, you can then compare their effects (and how these differ to those obtained with the original BAU scenario), using the data analysis software of your choice.
As an example, here are some of the results obtained for non-Maori males aged 50-54 in 2011, for the tobacco eradication intervention:
Year of birth |
Sex |
Age |
Year |
Survivors |
BAU Survivors |
Population |
BAU Population |
ACMR |
BAU ACMR |
Probability of death |
BAU Probability of death |
Deaths |
BAU Deaths |
YLD rate |
BAU YLD rate |
Person years |
BAU Person years |
HALYs |
BAU HALYs |
LE |
BAU LE |
HALE |
BAU HALE |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
… |
|||||||||||||||||||||||
1959 |
male |
52 |
2011 |
129,460.4 |
129,460.4 |
129,850.0 |
129,850.0 |
0.003 |
0.003 |
0.003 |
0.003 |
389.6 |
389.6 |
0.1122 |
0.1122 |
129,655.2 |
129,655.2 |
115,103.4 |
115,103.4 |
33.6 |
33.1 |
26.5 |
26.0 |
1959 |
male |
53 |
2012 |
129,054.2 |
129,047.0 |
129,460.4 |
129,460.4 |
0.0031 |
0.0032 |
0.0031 |
0.0032 |
406.3 |
413.5 |
0.112 |
0.1122 |
129,257.3 |
129,253.7 |
114,775.6 |
114,746.9 |
32.7 |
32.2 |
25.7 |
25.2 |
1959 |
male |
54 |
2013 |
128,631.8 |
128,607.5 |
129,054.2 |
129,047.0 |
0.0033 |
0.0034 |
0.0033 |
0.0034 |
422.4 |
439.5 |
0.1117 |
0.1122 |
128,843.0 |
128,827.2 |
114,450.3 |
114,368.3 |
31.8 |
31.3 |
24.9 |
24.4 |
… |
|||||||||||||||||||||||
1959 |
male |
108 |
2067 |
151.4 |
136.4 |
244.5 |
220.7 |
0.4793 |
0.4811 |
0.3808 |
0.3819 |
93.1 |
84.3 |
0.3551 |
0.3578 |
198.0 |
178.6 |
127.7 |
114.7 |
1.6 |
1.6 |
1.0 |
1.0 |
1959 |
male |
109 |
2068 |
93.7 |
84.3 |
151.4 |
136.4 |
0.4794 |
0.4811 |
0.3809 |
0.3819 |
57.7 |
52.1 |
0.3553 |
0.3578 |
122.6 |
110.4 |
79.0 |
70.9 |
1.3 |
1.3 |
0.8 |
0.8 |
1959 |
male |
110 |
2069 |
58.0 |
52.1 |
93.7 |
84.3 |
0.4796 |
0.4812 |
0.381 |
0.382 |
35.7 |
32.2 |
0.3554 |
0.3578 |
75.9 |
68.2 |
48.9 |
43.8 |
0.8 |
0.8 |
0.5 |
0.5 |
… |
Note that these results differ to those obtained with the original BAU scenario.