Researchers from the Brown School at Washington University in St. Louis used an agent-based computer model to project the potential effects of strategies to reduce the density of retailers that sell tobacco in various locations. They found that the impact may depend on setting and timing.
The team of scientists built the model, called Tobacco Town, to represent a hypothetical town populated by cigarette smokers who travel between home and other destinations making choices along the way about whether to buy cigarettes and what to buy. The model simulates changes driven by different retail policies and their impact on purchase decisions and costs.
The study varied retailer density across wide ranges, in different town-type settings. Researchers found that when retailers were relatively abundant, small or moderate density reduction had minimal impact on cost to consumers. But when retailers were scarce, those reductions had dramatic impacts. They also found less cost impact from density reduction in poor urban and suburban areas than in high-income areas.
“Retail-focused interventions are quickly becoming a priority for tobacco control programs across the US,” Ross Hammond, the study’s lead author and Betty Bofinger Brown Associate Professor at the Brown School.
“Tobacco Town is intended to serve as a policy laboratory for retail tobacco interventions. Future work will include expansion of the model to consider geographical data-driven settings, retailer dynamics, tobacco initiation and cessation, and underage tobacco use, and to further expand the exploration of behavioral decision rules begun here.”
The paper was published online Dec. 20 in Health & Place.