Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
School of Mathematical Sciences, Faculty of Science, Queensland University Technology, Brisbane, Australia.
Sci Rep. 2022 Apr 28;12(1):6985. doi: 10.1038/s41598-022-10678-y.
During the COVID-19 pandemic, many countries implemented international travel restrictions that aimed to contain viral spread while still allowing necessary cross-border travel for social and economic reasons. The relative effectiveness of these approaches for controlling the pandemic has gone largely unstudied. Here we developed a flexible network meta-population model to compare the effectiveness of international travel policies, with a focus on evaluating the benefit of policy coordination. Because country-level epidemiological parameters are unknown, they need to be estimated from data; we accomplished this using approximate Bayesian computation, given the nature of our complex stochastic disease transmission model. Based on simulation and theoretical insights we find that, under our proposed policy, international airline travel may resume up to 58% of the pre-pandemic level with pandemic control comparable to that of a complete shutdown of all airline travel. Our results demonstrate that global coordination is necessary to allow for maximum travel with minimum effect on viral spread.
在 COVID-19 大流行期间,许多国家实施了国际旅行限制,旨在控制病毒传播,同时仍允许出于社会和经济原因进行必要的跨境旅行。这些方法在控制大流行方面的相对有效性在很大程度上尚未得到研究。在这里,我们开发了一个灵活的网络荟萃人群模型来比较国际旅行政策的有效性,重点评估政策协调的好处。由于国家层面的流行病学参数未知,因此需要根据我们复杂的随机疾病传播模型的性质,从数据中进行估计。基于模拟和理论见解,我们发现,根据我们提出的政策,国际航空旅行可能会恢复到大流行前水平的 58%,而大流行控制与全面停飞所有航空旅行相当。我们的结果表明,需要全球协调才能实现最大程度的旅行,同时对病毒传播的影响最小。