Incorporating dynamic flight network in SEIR to model mobility between populations.

Incorporating dynamic flight network in SEIR to model mobility between populations.
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DOI:
10.1007/s41109-021-00378-3
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发表时间:
2021
影响因子:
2.2
通讯作者:
Rabbany R
Rabbany R
中科院分区:
其他
文献类型:
--
作者:
Ding X;Huang S;Leung A;Rabbany R

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目前的新冠肺炎建模工作往往是基于标准的划分模型,如SEIR及其变体。由于无症状和无症状病例可通过旅行在人群之间传播疾病,因此重要的是将人群间的流动性纳入流行病学模型。在这项工作中,我们建议修正常用的SEIR模型来考虑动态飞行网络,根据空中交通量和检测阳性率来估计输入案例。我们根据在加拿大发现的数据进行了一项案例研究,以展示这种名为Flight-Seir的修改如何潜在地实现(1)早期发现因输入的无症状和无症状病例而引起的疫情,(2)更准确地估计复制数量,以及(3)评估旅行限制的影响和取消这些措施的影响。考虑到我们的世界变得多么相互关联,拟议中的Flight-Seir对于驾驭这场大流行和下一次大流行至关重要。
Current efforts of modelling COVID-19 are often based on the standard compartmental models such as SEIR and their variations. As pre-symptomatic and asymptomatic cases can spread the disease between populations through travel, it is important to incorporate mobility between populations into the epidemiological modelling. In this work, we propose to modify the commonly-used SEIR model to account for the dynamic flight network, by estimating the imported cases based on the air traffic volume and the test positive rate. We conduct a case study based on data found in Canada to demonstrate how this modification, called Flight-SEIR, can potentially enable (1) early detection of outbreaks due to imported pre-symptomatic and asymptomatic cases, (2) more accurate estimation of the reproduction number and (3) evaluation of the impact of travel restrictions and the implications of lifting these measures. The proposed Flight-SEIR is essential in navigating through this pandemic and the next ones, given how interconnected our world has become.
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