The Tobacco Control Policy (TCP) tool

• This repository is used to run the Smoking History Generator (SHG) Policy Module and generate results for the TCP tool
• The TCP tool is a web-based user interface for a tobacco policy microsimulation model developed by the Cancer Intervention and Surveillance Modeling Network (CISNET) Lung consortium.

Requirements

• R version 3.2.3
• python version 2.7.12
• smoking-history-generator v.6.3.3
• shg-policy-module v0.1.2

Setup

The code in this repository is currently set up to run policy scenarios in parallel across 20 cores, with error and log files for each. Total run-time varies depending on the number of individuals generated per birth cohort (~1 min to simulate 200,000 individuals from a single birth cohort). There are 300 birth cohorts simulated per scenario, except for MLA which simulates 380 birth cohorts. When spread across 20 cores, this dramatically reduces the total amount of time needed to generate a full set of results. Because of the large number of files generated that need to be organized, the directory structure on your machine must be set up accordingly.

• Create directories one level above this repository to store each set of results:

  • airlaws_results, taxes_results, tcexp_results, mla_results to store each policy's results
  • source_data for state-level and US data
  • shg-policy-module-parallel as a copy of shg-policy-module v0.1.2. To run the model across 20 cores, create 20 copies of shg-policy-module-parallel directory with python wrapper.py.

• Make necessary changes to the file paths referenced in these python and R scripts:

  • scenarios_airlaws.py, scenarios_taxes.py, scenarios_tcexp.py, scenarios_mla.py, tcptool_airlaws_data.py,tcptool_taxes_data.py, tcptool_tcexp_data.py, tcptool_mla_data.py, and check_files_for_errors.R

Overview

1) Choose one tobacco control policy to simulate results for

• airlaws: implement and enforce smoke-free air laws up to three venues (1080 possible scenarios / runtime ~14 days)
• taxes: raise the price of a pack of cigarettes via taxes (635 possible scenarios)
• tcexp: increase the level of tobacco control program expenditures (280 possible scenarios)
• mla: raise the minimum age of legal access to tobacco (225 possible scenarios)

2) Run the policy module python policy_shg.py

• change cohortsize to reflect number of individuals simulated per birth cohort (500000 or 50 for test runs)
• change lastcohort to reflect the final birth cohort of individuals to simulate (2060 or 2100)
• this step is the time-limiting step, so be sure your machine has sufficient cores to run all scenarios
• the screen command is helpful for avoiding interruptions to this command when you are away from the machine.

3) Generate national and state-level results under every scenario Rscript tcptool_airlaws_data.R

• be sure that prevfiles point to the correct directory where your scenarios from step 2 were generated
• be sure that mainDir points to a new source_data directory where you want your final dataset to be located
• change cohortsize to reflect number of individuals simulated per birth cohort (500000 or 200000)
• smoking prevalence (results_w1_r1_b1_pacw0.00_pacr0.00_pacb0.00.csv)
• premature deaths avoided (deaths_w1_r1_b1_pacw0.00_pacr0.00_pacb0.00.csv)
• life-years gained (lyg_w1_r1_b1_pacw0.00_pacr0.00_pacb0.00.csv)

4) Check for errors in the results files Rscript check_files_for_errors.R

• missing policy scenarios
• missing rows of data
• negative sum of deaths avoided across all cohorts
• ratio of deaths avoided between men and women is greater than 2

5) Check for errors across the results files

• run Rscript check_files_for_errors.R to check results in the source_data directory for missing policy scenarios, missing rows of data, negative sum of deaths avoided across all cohorts, and whether the ratio of deaths avoided between men and women is greater than 2

Help

• Contact jamietam@umich.edu with questions
• Contact shg-distrib@lung.cisnet-group.org to request copies of the smoking-history-generator v.6.3.3 and shg-policy-module v0.1.2

Policy parameters

• airlaws:

  • workplaces? 0 (no) or 1 (yes)
  • restaurants? 0 or 1
  • bars? 0 or 1
  • percent of workplaces already covered by smoke-free air laws? 0%, 25%, 50%, 75%, or 100%
  • percent of restaurants already covered by smoke-free air laws? 0%, 25%, 50%, 75%, or 100%
  • percent of bars already covered by smoke-free air laws? 0%, 25%, 50%, 75%, or 100%

• taxes:

  • initial price per pack? $6.00, $6,50, $7.00, $7.50, $8.00, $8.50, $9.00, $9.50, $10.00, $10.50
  • tax increase? $1.00, $1.50, $2.00, $2.50, $3.00, $3.50, $4.00, $4.50

• tcexp:

  • existing level of expenditures (as % of CDC recommendations)? 0%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, or 100%
  • policy level of expenditures? 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, or 100%

• mla:

  • minimum age? 19, 21, or 25
  • percent of population already covered by MLA 19? 0%, 25%, 50%, 75%, or 100%
  • percent of population already covered by MLA 21? 0%, 25%, 50%, 75%, or 100%
  • percent of population already covered by MLA 21? 0%, 25%, 50%, 75%, or 100%