The Global Diffusion of Tobacco Control

描述(申请人提供)：尽管全球许多地区的吸烟率有所下降，但全球估计仍有13亿吸烟者，烟草使用仍是全球可预防死亡的主要原因。为了应对持续存在的烟草使用问题，世卫组织成员国谈判并一致通过了《世卫组织烟草控制框架公约》(FCTC)，这是一项旨在减少烟草使用的国际条约。截至2011年4月，在世界卫生组织193个成员国中，约有87%批准了《烟草控制框架公约》(或其法律等价物)。了解个别国家何时、如何以及为什么批准《烟草控制框架公约》并随后制定履行条约义务的政策是一个关键的研究问题，它对理解网络效应、创新扩散的科学以及未来制定国际公共卫生法的前景具有影响。 这项研究建议汇编来自全球烟草倡导电子论坛GLOBALink的大量网络数据，以构建可用于在动态建模框架中估计网络影响的多个社会网络。我们研究了网络对《烟草控制框架公约》的传播和通过的影响，以及它在193个成员国中9年时间里的执行力度。我们还建议用一个广泛的国家属性数据库来扩充网络数据，这些国家属性包括：总人口；人口分布；面积；收入；收入分配；烟草生产；政府形式；地区；电力、通信和贸易支出；烟草控制非政府组织的存在等。这些属性将用于控制它们与《公约》批准和执行的可能关联，以确定这些特征是否与传染性或对《公约》扩散的敏感性有关。我们还获得了关于批准另外两项国际条约的数据，这两项条约在类似的时间跨度内扩散。这些条约将扮演“比较条约”的角色，我们不希望GLOBALINK的参与与它们的批准有关。与此同时，我们将获得其他国家间网络数据，以测试这些其他网络(贸易和通信)是否与比较条约有关，而不是与《公约》的通过有关。最终目标是将传统的扩散网络方法与新开发的面向参与者的MCMC方法相结合，以解决网络依赖问题。我们在R中建立了一个面向扩散网络随机参与者的(SIENA)平台来检验特定的动态网络影响假设。这一事件历史分析将能够在条约通过的108个月内测试网络影响，其中包括互惠、传递性、交替K-STAR等参数，以及RSIENA中内置的许多其他参数。这些步骤使得能够指定动态考虑网络和行为的协同进化的复杂网络效应。最后，我们将对GLOBALink用户之间交换的消息进行精选内容分析，以补充我们的分析。我们的总体目标是汇编一个丰富的数据集，说明三项条约的国际传播情况，预计这些条约将受到至少10个不同网络的不同影响。这项拟议研究的意义来自于解决一个重要的全球卫生主题，检索前所未有的丰富和粒度的数据，并采用复杂而新的综合建模方法。

DESCRIPTION (provided by applicant): Although smoking rates have decreased in many parts of the globe, there are still an estimated 1.3 billion smokers globally, and tobacco use is still the leading cause of preventable death worldwide. To combat the ongoing problem of tobacco use, the WHO Member States negotiated and unanimously adopted the WHO Framework Convention on Tobacco Control (FCTC) which is an international treaty aimed at reducing tobacco use. About 87% of the 193 WHO member countries have ratified the FCTC (or its legal equivalent) as of April 2011. Understanding when, how, and why individual countries ratified the FCTC and subsequently enacted policies implementing the treaty obligations is a critical research question that has implications for understanding network effects, the science of diffusion of innovations, as well as prospects for enacting future international public health law. This study proposes to compile extensive network data from GLOBALink, an electronic forum for global tobacco advocacy, to construct multiple social networks that can be used to estimate network effects in a dynamic modeling framework. We study network influences on the diffusion and adoption of the FCTC and the strength of its implementation among the 193 member countries over a 9-year period. We also propose to augment the network data with an extensive database of country attributes such as total population; population distribution; size (area); income; income distribution; tobacco production; governmental form; region; spending on power, communications, and trade; existence of tobacco control NGOs; and so on. These attributes will be used to control for their possible associations with FCTC ratification and implementation to determine whether these characteristics are associated with infectivity or susceptibility to FCTC diffusion. We have also acquired data on the ratification of two other international treaties which diffused over a similar time-span. These treaties will act as "comparison treaties" in which we do not expect GLOBALink participation to be associated with their ratification. At the same time, we will acquire other inter-country network data to test whether these other networks (trade and communication) were associated with the comparison treaties and not with FCTC adoption. The final aim combines the traditional diffusion network approach with the newly developed actor-oriented MCMC approach created to address network dependencies. We have built a diffusion network stochastic actor oriented (SIENA) platform in R to test specific dynamic network influence hypotheses. This event history analysis will enable the testing of network influences over the 108 months of treaty adoption that incorporates parameters for reciprocity, transitivity, alternating k-stars, and the many other parameters built into RSIENA. These procedures enable the specification of complex network effects that dynamically consider the coevolution of networks and behavior. Finally, we will supplement our analyses with selected content analysis of messages exchanged between GLOBALink users. Our overall goal is to compile a rich dataset on the international diffusion of three treaties expected to be differentially influenced by at least 10 different networks. The significance of thi proposed research is derived from addressing an important global health topic, retrieving data of unprecedented richness and granularity, and employing a sophisticated yet new comprehensive modeling approach.