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Int J Public Health. 2018 May;63(4):537-546. doi: 10.1007/s00038-017-1041-y. Epub 2017 Oct 19.

Harnessing advances in computer simulation to inform policy and planning to reduce alcohol-related harms.

Author information

1
Decision Analytics, Sax Institute, Sydney, Australia. Jo-An.Atkinson@saxinstitute.org.au.
2
The Australian Prevention Partnership Centre, Sax Institute, Ultimo, NSW, Australia. Jo-An.Atkinson@saxinstitute.org.au.
3
Sydney Medical School, University of Sydney, Camperdown, Australia. Jo-An.Atkinson@saxinstitute.org.au.
4
The Australian Prevention Partnership Centre, Sax Institute, Ultimo, NSW, Australia.
5
Anthrodynamics Simulation Services, Saskatoon, Canada.
6
Hunter New England Population Health, Newcastle, NSW, Australia.
7
School of Medicine and Public Health, University of Newcastle, Callaghan, NSW, Australia.
8
Centre for Alcohol Policy Research, La Trobe University, Melbourne, Australia.
9
Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
10
Centre for Social Research on Alcohol and Drugs, Stockholm University, Sveaplan, Stockholm, Sweden.
11
Decision Analytics, Sax Institute, Sydney, Australia.
12
School of Computing, Engineering and Mathematics, Western Sydney University, Parramattu, Australia.
13
Centre for Health and Social Research, Australian Catholic University, Melbourne, Australia.
14
Sydney Medical School, University of Sydney, Camperdown, Australia.
15
Drug Health Services, Royal Prince Alfred Hospital, Sydney, Australia.
16
Faculty of Medicine, University of NSW, Sydney, Australia.
17
Alcohol and Drug Service, St Vincent's Hospital, Sydney, Australia.
18
Drug Health Western Sydney Local Health District, Sydney, Australia.
19
Liver Addiction Research Unit, Storr Liver Centre, Westmead Institute of Medical Research, Sydney, Australia.
20
Knowledge Translation and Health Outcomes, Epidemiology Section, ACT Health, Canberra, Australia.
21
School of Medicine Sydney, University of Notre Dame Australia, Sydney, Australia.
22
School of Public Health, University of Sydney, Camperdown, Australia.
23
Faculty of Health, Deakin Health Economics, Centre for Population Health Research, Deakin University, Burwood, Australia.
24
Menzies Centre for Health Policy, University of Sydney, Sydney, Australia.

Abstract

OBJECTIVES:

Alcohol misuse is a complex systemic problem. The aim of this study was to explore the feasibility of using a transparent and participatory agent-based modelling approach to develop a robust decision support tool to test alcohol policy scenarios before they are implemented in the real world.

METHODS:

A consortium of Australia's leading alcohol experts was engaged to collaboratively develop an agent-based model of alcohol consumption behaviour and related harms. As a case study, four policy scenarios were examined.

RESULTS:

A 19.5 ± 2.5% reduction in acute alcohol-related harms was estimated with the implementation of a 3 a.m. licensed venue closing time plus 1 a.m. lockout; and a 9 ± 2.6% reduction in incidence was estimated with expansion of treatment services to reach 20% of heavy drinkers. Combining the two scenarios produced a 33.3 ± 2.7% reduction in the incidence of acute alcohol-related harms, suggesting a synergistic effect.

CONCLUSIONS:

This study demonstrates the feasibility of participatory development of a contextually relevant computer simulation model of alcohol-related harms and highlights the value of the approach in identifying potential policy responses that best leverage limited resources.

KEYWORDS:

Agent-based modelling; Alcohol-related harm; Evidence synthesis; Prevention policy

PMID:
29051984
PMCID:
PMC5938302
DOI:
10.1007/s00038-017-1041-y
[Indexed for MEDLINE]
Free PMC Article

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