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Policy options for endgame planning in tobacco control: a simulation modelling study
  1. Adam Skinner1,
  2. Pippy Walker1,2,3,
  3. Jo-An Atkinson1,2,4,
  4. Rebecca Whitehead5,
  5. Tim Roselli5,
  6. Mark West5,
  7. Margaret Bright5,
  8. Mark Heffernan6,
  9. Geoff McDonnell2,
  10. Lennert Veerman7,8,
  11. Ante Prodan1,9,
  12. David P Thomas10,
  13. Suzan Burton11
  1. 1Decision Analytics, Sax Institute, Sydney, New South Wales, Australia
  2. 2The Australian Prevention Partnership Centre, Sax Institute, Sydney, New South Wales, Australia
  3. 3Menzies Centre for Health Policy, University of Sydney, Sydney, New South Wales, Australia
  4. 4School of Medicine, University of Sydney, Sydney, New South Wales, Australia
  5. 5Preventive Health Branch, Department of Health, Brisbane, Queensland, Australia
  6. 6Dynamic Operations, Mona Vale, New South Wales, Australia
  7. 7Cancer Research Division, Cancer Council New South Wales, Sydney, New South Wales, Australia
  8. 8School of Medicine, Griffith University, Gold Coast, Queensland, Australia
  9. 9School of Computing, Engineering and Mathematics, Western Sydney University, Sydney, New South Wales, Australia
  10. 10Menzies School of Health Research, Darwin, Northern Territory, Australia
  11. 11School of Business, Western Sydney University, Sydney, New South Wales, Australia
  1. Correspondence to Dr Adam Skinner, The Sax Institute, Level 13 Building 10, 235 Jones Street, Ultimo, NSW 2007, Australia; Adam.Skinner{at}saxinstitute.org.au

Abstract

Objective To investigate the potential impacts of several tobacco control interventions on adult daily smoking prevalence in the Australian state of Queensland, using a system dynamics model codeveloped with local and national stakeholders.

Methods Eight intervention scenarios were simulated and compared with a reference scenario (business as usual), in which all tobacco control measures currently in place are maintained unchanged until the end of the simulation period (31 December 2037).

Findings Under the business as usual scenario, adult daily smoking prevalence is projected to decline from 11.8% in 2017 to 5.58% in 2037. A sustained 50% increase in antismoking advertising exposure from 2018 reduces projected prevalence in 2037 by 0.80 percentage points. Similar reductions are projected with the introduction of tobacco wholesaler and retailer licensing schemes that either permit or prohibit tobacco sales by alcohol-licensed venues (0.65 and 1.73 percentage points, respectively). Increasing the minimum age of legal supply of tobacco products substantially reduces adolescent initiation, but has minimal impact on smoking prevalence in the adult population over the simulation period. Sustained reductions in antismoking advertising exposure of 50% and 100% from 2018 increase projected adult daily smoking prevalence in 2037 by 0.88 and 1.98 percentage points, respectively.

Conclusions These results suggest that any prudent approach to endgame planning should seek to build on rather than replace existing tobacco control measures that have proved effective to date. Additional interventions that can promote cessation are expected to be more successful in reducing smoking prevalence than interventions focussing exclusively on preventing initiation.

  • cessation
  • end game
  • public policy
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Footnotes

  • Contributors RW, MW, J-AA, AS and PW conceived the study. PW, RW, MW and J-AA organised and ran the workshops. AS built the system dynamics model, performed the analyses and drafted the paper. TR and MB provided historical data used for model calibration. All authors contributed to model development and preparation of the final manuscript.

  • Funding This research was funded by the Queensland Department of Health.

  • Disclaimer The views expressed in this paper are those of the authors and do not represent the views of the Queensland Department of Health or Queensland Government policy.

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement All data relevant to the study are included in the article or uploaded as supplementary information.

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