National Renewable Energy Laboratory, Mobility, Behavior, and Advanced Powertrains Department, Denver, CO 80401, USA.
Epstein Department of Industrial and Systems Engineering, University of Southern California, Los Angeles, CA 90089, USA.
Int J Environ Res Public Health. 2024 May 18;21(5):643. doi: 10.3390/ijerph21050643.
Human travel plays a crucial role in the spread of infectious disease between regions. Travel of infected individuals from one region to another can transport a virus to places that were previously unaffected or may accelerate the spread of disease in places where the disease is not yet well established. We develop and apply models and metrics to analyze the role of inter-regional travel relative to the spread of disease, drawing from data on COVID-19 in the United States. To better understand how transportation affects disease transmission, we established a multi-regional time-varying compartmental disease model with spatial interaction. The compartmental model was integrated with statistical estimates of travel between regions. From the integrated model, we derived a transmission import index to assess the risk of COVID-19 transmission between states. Based on the index, we determined states with high risk for disease spreading to other states at the scale of months, and we analyzed how the index changed over time during 2020. Our model provides a tool for policymakers to evaluate the influence of travel between regions on disease transmission in support of strategies for epidemic control.
人类旅行在区域间传染病传播中起着至关重要的作用。受感染个体从一个地区到另一个地区的旅行可以将病毒传播到以前未受影响的地方,或者可能加速疾病在尚未广泛传播的地方的传播。我们开发并应用模型和指标来分析跨区域旅行相对于疾病传播的作用,这些模型和指标是基于美国 COVID-19 数据得出的。为了更好地了解交通对疾病传播的影响,我们建立了一个具有空间相互作用的多区域时变隔室疾病模型。该隔室模型与区域间旅行的统计估计相结合。从综合模型中,我们得出了一个传输进口指数,以评估各州之间 COVID-19 传播的风险。基于该指数,我们确定了在数月的时间尺度上疾病向其他州传播风险较高的州,并分析了该指数在 2020 年期间随时间的变化。我们的模型为政策制定者提供了一种工具,用于评估区域间旅行对疾病传播的影响,以支持传染病控制策略。