Kim Karl, Yamashita Eric, Ghimire Jiwnath
National Disaster Preparedness Training Center, Pacific Urban Resilience Lab, University of Hawaii, Honolulu, Hawaii.
National Disaster Preparedness Training Center, University of Hawaii System, Honolulu, Hawaii.
Transp Res Rec. 2023 Apr;2677(4):324-334. doi: 10.1177/03611981211058428. Epub 2021 Dec 4.
In the absence of a vaccine, nonpharmaceutical interventions such as social distancing and travel reductions were the only strategies for slowing the spread of the COVID-19 pandemic. Using survey data from Hawaii ( = 22,200) collected in March through May of 2020 at the onset of the pandemic, the differences between traveler spreaders who brought the disease into the state and community spreaders were investigated. In addition to describing the demographic attributes and comparing them with attributes of those who were vulnerable to COVID-19, logit models explaining travel behaviors were developed and tested. Traveler spreaders were likely to be male, younger, and returning students. Community spreaders were more likely to be male, essential workers, first responders, and medical personnel at the highest risk of exposure. Using spatial statistics, clusters and hotspot locations of high-risk individuals were mapped. As transportation researchers are in a position to combine their critical analytical capabilities and experience with relevant databases on mobility and the spread of infectious diseases, this analysis could support efforts to respond to and slow the spread of the pandemic.
在没有疫苗的情况下，社交距离和减少旅行等非药物干预措施是减缓新冠疫情传播的唯一策略。利用2020年3月至5月疫情初期在夏威夷收集的调查数据（n = 22200），对将疾病带入该州的旅行者传播者和社区传播者之间的差异进行了调查。除了描述人口统计学特征并将其与易感染新冠病毒者的特征进行比较外，还开发并测试了解释旅行行为的逻辑模型。旅行者传播者可能为男性、年轻人和返校学生。社区传播者更可能为男性、必要工作者、急救人员以及暴露风险最高的医务人员。利用空间统计方法，绘制了高风险个体的聚集区和热点位置。由于交通研究人员能够将其关键分析能力和经验与有关流动性和传染病传播的相关数据库相结合，该分析可为应对和减缓疫情传播的努力提供支持。
