A key strategy to prevent a local outbreak during the COVID-19 pandemic is to restrict incoming travel. Once a region has successfully contained the disease, it becomes critical to decide when and how to reopen the borders. Here we explore the impact of border reopening for the example of Newfoundland and Labrador, a Canadian province that has enjoyed no new cases since late April, 2020. We combine a network epidemiology model with machine learning to infer parameters and predict the COVID-19 dynamics upon partial and total airport reopening, with perfect and imperfect quarantine conditions. Our study suggests that upon full reopening, every other day, a new COVID-19 case would enter the province. Under the current conditions, banning air travel from outside Canada is more efficient in managing the pandemic than fully reopening and quarantining 95% of the incoming population. Our study provides quantitative insights of the efficacy of travel restrictions and can inform political decision making in the controversy of reopening.

中文翻译：

---

解除 COVID-19 旅行禁令是否安全？纽芬兰的故事

在 COVID-19 大流行期间防止局部爆发的一项关键策略是限制入境旅行。一旦一个地区成功遏制了这种疾病，决定何时以及如何重新开放边界就变得至关重要。在这里，我们以加拿大纽芬兰和拉布拉多省为例探讨重新开放边境的影响，该省自 2020 年 4 月下旬以来没有出现新病例。我们将网络流行病学模型与机器学习相结合，以推断参数并预测 COVID-19 动态在部分和全部机场重新开放时，隔离条件完善和不完善。我们的研究表明，在全面重新开放后，每隔一天就会有一个新的 COVID-19 病例进入该省。在目前的条件下，与完全重新开放和隔离 95% 的入境人口相比，禁止来自加拿大境外的航空旅行在管理大流行方面更有效。我们的研究提供了旅行限制有效性的定量见解，并可以为重新开放争议中的政治决策提供信息。