School of Public Health, Tel Aviv University, Tel Aviv, Israel.
Porter School of the Environment and Earth Sciences, Tel Aviv University, Tel Aviv, Israel.
J Travel Med. 2020 Aug 20;27(5). doi: 10.1093/jtm/taaa093.
Substantial limitations have been imposed on passenger air travel to reduce transmission of severe acute respiratory syndrome coronavirus 2 between regions and countries. However, as case numbers decrease, air travel will gradually resume. We considered a future scenario in which case numbers are low and air travel returns to normal. Under that scenario, there will be a risk of outbreaks in locations worldwide due to imported cases. We estimated the risk of different locations acting as sources of future coronavirus disease 2019 outbreaks elsewhere.
We use modelled global air travel data and population density estimates from locations worldwide to analyse the risk that 1364 airports are sources of future coronavirus disease 2019 outbreaks. We use a probabilistic, branching-process-based approach that considers the volume of air travelers between airports and the reproduction number at each location, accounting for local population density.
Under the scenario we model, we identify airports in East Asia as having the highest risk of acting as sources of future outbreaks. Moreover, we investigate the locations most likely to cause outbreaks due to air travel in regions that are large and potentially vulnerable to outbreaks: India, Brazil and Africa. We find that outbreaks in India and Brazil are most likely to be seeded by individuals travelling from within those regions. We find that this is also true for less vulnerable regions, such as the United States, Europe and China. However, outbreaks in Africa due to imported cases are instead most likely to be initiated by passengers travelling from outside the continent.
Variation in flight volumes and destination population densities creates a non-uniform distribution of the risk that different airports pose of acting as the source of an outbreak. Accurate quantification of the spatial distribution of outbreak risk can therefore facilitate optimal allocation of resources for effective targeting of public health interventions.
为了减少严重急性呼吸综合征冠状病毒 2 在地区和国家之间的传播，已经对旅客航空旅行施加了实质性限制。然而，随着病例数量的减少，航空旅行将逐渐恢复。我们考虑了一个病例数量较低且航空旅行恢复正常的未来情景。在这种情况下，由于输入病例，世界各地都有爆发的风险。我们估计了不同地点作为未来 2019 年冠状病毒病爆发源的风险。
我们使用全球航空旅行数据和世界各地地点的人口密度估计值来分析 1364 个机场成为未来 2019 年冠状病毒病爆发源的风险。我们使用一种基于概率的分支过程方法，该方法考虑了机场之间的航空旅客量和每个地点的繁殖数，同时考虑了当地的人口密度。
在我们模拟的情景下，我们确定东亚的机场具有作为未来爆发源的最高风险。此外，我们还研究了由于航空旅行在大而容易爆发的地区（印度、巴西和非洲）造成的爆发的最有可能的地点。我们发现，印度和巴西的爆发最有可能是由来自这些地区的旅行者引起的。我们发现，对于脆弱性较低的地区（如美国、欧洲和中国）也是如此。然而，由于输入病例而在非洲爆发的情况，最有可能是由来自非洲大陆以外的乘客引发的。
航班数量和目的地人口密度的变化导致不同机场作为爆发源的风险分布不均匀。因此，准确量化爆发风险的空间分布可以促进资源的最佳分配，从而有效地针对公共卫生干预措施。
