CNH-L: Coupled Dynamics of Tourism and Mosquito-Borne Disease Transmission in the Americas

该研究项目将以美洲为重点，研究蚊子传播疾病的传播、对疾病风险的看法和人类旅行之间的关系。受感染人群的流动有可能引发鲜为人知的蚊媒疾病的全球流行，类似于分别在2013年和2015年首次检测到基孔肯雅和寨卡病毒后在美洲发生的那种疾病。研究人员将调查人类运动模式对蚊子与人类相互作用以及蚊媒病毒跨地区传播(从当地到大陆距离)的贡献。该项目将寻求了解传染病暴发如何影响个人旅行决定以及旅游企业的营销战略。该小组还将研究应对疫情和营销活动中人类流动性的变化可能如何改变疫情传播途径。该项目将为美国的本科生、研究生和博士后研究人员提供疾病生态学、数学和地理信息科学方面的跨学科教育和培训机会，从而造福社会。与公共卫生和旅游业利益相关者举行的参与式研讨会将寻求制定管理战略和行动，以应对蚊子传播的疾病威胁。作为该项目的一部分开发的数据集将通过公共储存库以及在线和面对面的教育讲习班提供。该项目将使用流行病学建模和数据科学技术，利用丰富的信息源(如移动电话和社交媒体数据)，从半球到局部空间尺度模拟人类活动及其对蚊媒疾病(即基孔肯雅病和寨卡病毒)暴发的影响。特别是，研究人员将评估真实人类流动网络(即网络主干)作为蚊媒病毒潜在传播路径的重要性，并评估重要网络节点(例如连接最多的城市和国家)的理论指标在最近寨卡和基孔肯雅热爆发期间预测高传播超级传播枢纽的能力。这项研究将把人的流动性作为一个参数纳入蚊媒疾病风险预测模型。这些结果将与社会科学的混合方法研究方法相结合，以展示传染病的爆发以及相关的旅行警告和旅游营销的变化如何影响个人旅行者的旅行选择，以及这些选择如何扩大以改变流行病的传播轨迹。将蚊媒疾病的出现和国际国内旅游作为一个自然-人类耦合系统来考虑，将使研究人员能够评估抑制传播的不同干预策略的有效性，蚊子控制措施的知识对旅行者和旅游公司健康风险认知的影响，以及因应疾病风险认知而改变旅行模式影响流行病时空轨迹的可能性。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Focusing on the Americas, this research project will examine the relationships among the spread of mosquito-transmitted diseases, perceptions of disease risk, and human travel. The movement of infected humans has the potential to spark global epidemics of poorly-known mosquito-borne diseases, similar to those that occurred in the Americas following the first detection of chikungunya and Zika viruses in 2013 and 2015, respectively. The researchers will investigate the contribution of human movement patterns to mosquito-human interactions and to the spread of mosquito-borne viruses across regions (from local to continental distances). The project will seek to understand how infectious disease outbreaks influence the decisions of individuals to travel as well as marketing strategies of tourism businesses. The team will also look at how changes in human mobility in response to outbreaks and marketing might alter outbreak paths. The project will benefit society by offering interdisciplinary education and training opportunities in disease ecology, mathematics, and geographic information science for undergraduates, graduate students, and post-doctoral researchers in the U.S. Participatory workshops with public health and tourism stakeholders will seek to develop management strategies and actions to address mosquito-borne disease threats. The data sets developed as part of the project will be made available through public repositories accompanied by online and face-to-face educational workshops.The project will use epidemiological modeling and data science techniques to model human movements and their impact on outbreaks of mosquito-borne diseases (i.e., chikungunya and Zika viruses), from hemispheric to local spatial scales using a rich stream of information sources (e.g., mobile phone and social media data). In particular, the researchers will evaluate the significance of the most traveled routes of real human mobility networks (i.e., the network backbone) as potential dispersal pathways for mosquito-borne viruses, and assess the ability of theoretical indicators of vital network nodes (e.g., most connected cities and countries) to predict the occurrence of super-spreading hubs of high transmission during the recent outbreaks of Zika and chikungunya. This research will incorporate human mobility as a parameter in predictive models for mosquito-borne disease risk. The results will be integrated with a social science mixed methods research approach to represent how outbreaks of infectious disease, together with associated travel warnings and changes in tourism marketing, influence individual travelers' movement choices and how these choices scale up to alter the trajectory of epidemics. The consideration of mosquito-borne disease emergence and international and domestic tourism as a coupled natural-human system will allow the researchers to assess the efficacy of different intervention strategies to inhibit transmission, the impacts of knowledge of mosquito control efforts on the health risk perceptions of travelers and tourism companies, and the potential for altered travel patterns in response to disease risk perceptions to influence the spatio-temporal trajectory of an epidemic.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.