Project 3: Tobacco Town Policy Modeling

项目3：烟草小镇：项目摘要/摘要 烟草使用仍然是美国可预防的死亡和疾病的最大原因， 在许多社区和人口中，社会经济差距依然存在。新的和 专注于零售环境的创新烟草控制干预措施正在取得进展， 旨在减少烟草产品的普及率，消除差距，主要是 通过三种机制之一：地点(例如，降低烟草零售商密度)、价格(例如， 限制折扣)或产品可获得性(例如，限制加味烟草产品)。然而， 支持这些策略有效性的证据才刚刚出现。发展强大的 零售烟草控制的证据基础是从业者的优先事项。虽然前景看好 评估这些干预措施的实验研究即使不是不可能，也很难进行， 计算建模正准备帮助填补证据空白。拟议研究的目标是 开发基于计算代理的模型，以检查和比较 不同社区背景下的各种零售烟草控制战略。这项研究已经 三个主要目标。1)开发烟草城，这是一种基于代理的模式，代表了 社区环境与个人、当前和潜在的烟草使用者。该模型将 结合现实的地理和商业空间、个人烟草使用行为(例如， 启动、停止、购买)和零售商实践(例如，定价和产品供应)。2) 将该模型用作模拟实验室来实施创新策略，以更好地理解 每一个都可能如何影响与吸烟相关的行为。我们还将从以下几个方面考虑这些战略 弱势群体，特别是种族/族裔和性少数群体和低收入群体 居民。3)裁缝烟草小镇代表10-12个大城市的不同社区- 在美国郊区考察不同干预措施的潜在特定背景影响。 在帮助建立创新烟草控制战略的证据基础的同时，烟草 城镇模型也将通过模拟不同的 不同背景下的干预措施。最后，该模型及其计算结果将会进一步推广应用 烟草控制和减少烟草使用的计算方法，以及公共卫生更多 大体上说。

Project 3 Tobacco Town: Project Summary/Abstract Tobacco use continues to be the greatest cause of preventable death and disease in the US, and socioeconomic disparities persist in many communities and populations. New and innovative tobacco control interventions focused on the retail environment are gaining ground, and aim to reduce the pervasiveness of tobacco products and eliminate disparities, chiefly through one of three mechanisms: place (e.g., lowering tobacco retailer density), price (e.g., curbing discounts), or product availability (e.g., limiting flavored tobacco products). However, the evidence supporting the effectiveness of these strategies is just emerging. Developing a strong evidence base for retail tobacco control is a priority for practitioners. While prospective experimental studies to assess these interventions are difficult, if not impossible, to conduct, computational modeling is poised to help fill the evidence gap. The goal of the proposed study is to develop a computational agent-based model to examine and compare the potential impact of various retail tobacco control strategies across different community contexts. The study has three primary aims. 1) Develop Tobacco Town, an agent-based model that represents community environments with individual current and potential tobacco users. The model will incorporate realistic geographic and commercial spaces, individual tobacco use behaviors (e.g., initiation, cessation, purchase), and retailer practices (e.g., pricing and product availability). 2) Use the model as a simulated laboratory to implement innovative strategies to better understand how each might impact smoking-related behaviors. We will also consider the strategies in terms of vulnerable populations, specifically racial/ethnic and sexual minorities and low-income residents. 3) Tailor Tobacco Town to represent diverse neighborhoods in 10-12 large urban- suburban areas in the US to examine potential context-specific effects of different interventions. While helping to build the evidence base for innovative tobacco control strategies, the Tobacco Town model will also enhance the relevance of this evidence through simulating various interventions in different contexts. Finally, the model and its results will advance the use of computational approaches to tobacco control and reducing tobacco use, and public health more broadly.