The Biosecurity Program, The Kirby Institute, UNSW Medicine, The University of New South Wales, Sydney, Australia.
The School of Public Health and Community Medicine, UNSW Medicine, The University of New South Wales, Sydney, Australia.
J Travel Med. 2020 Aug 20;27(5). doi: 10.1093/jtm/taaa081.
Australia implemented a travel ban on China on 1 February 2020, while COVID-19 was largely localized to China. We modelled three scenarios to test the impact of travel bans on epidemic control. Scenario one was no ban; scenario two and three were the current ban followed by a full or partial lifting (allow over 100 000 university students to enter Australia, but not tourists) from the 8th of March 2020.
We used disease incidence data from China and air travel passenger movements between China and Australia during and after the epidemic peak in China, derived from incoming passenger arrival cards. We used the estimated incidence of disease in China, using data on expected proportion of under-ascertainment of cases and an age-specific deterministic model to model the epidemic in each scenario.
The modelled epidemic with the full ban fitted the observed incidence of cases well, predicting 57 cases on March 6th in Australia, compared to 66 observed on this date; however, we did not account for imported cases from other countries. The modelled impact without a travel ban results in more than 2000 cases and about 400 deaths, if the epidemic remained localized to China and no importations from other countries occurred. The full travel ban reduced cases by about 86%, while the impact of a partial lifting of the ban is minimal and may be a policy option.
Travel restrictions were highly effective for containing the COVID-19 epidemic in Australia during the epidemic peak in China and averted a much larger epidemic at a time when COVID-19 was largely localized to China. This research demonstrates the effectiveness of travel bans applied to countries with high disease incidence. This research can inform decisions on placing or lifting travel bans as a control measure for the COVID-19 epidemic.
澳大利亚于 2020 年 2 月 1 日对中国实施旅行禁令,而当时新冠疫情主要局限于中国。我们构建了三种情景来测试旅行禁令对疫情控制的影响。情景一为不采取旅行禁令;情景二和三为目前的旅行禁令,之后于 2020 年 3 月 8 日完全或部分解除禁令(允许超过 10 万名大学生进入澳大利亚,但不允许游客入境)。
我们使用了来自中国的疾病发病率数据和疫情高峰期内及之后中国与澳大利亚之间的航空旅客流动数据,这些数据来源于入境旅客抵达卡。我们使用了中国的预期发病率估计值,利用病例漏报比例数据和特定年龄的确定性模型,对每种情景下的疫情进行建模。
全面禁止旅行的模拟疫情与实际病例数拟合较好,预测 3 月 6 日澳大利亚将有 57 例病例,而实际有 66 例;然而,我们没有考虑其他国家输入的病例。如果疫情继续局限于中国且没有其他国家的输入病例,没有旅行禁令的情况下,疫情将导致超过 2000 例病例和大约 400 例死亡。全面旅行禁令使病例减少了约 86%,而部分解除禁令的影响微不足道,可能是一种政策选择。
在疫情高峰期,旅行限制对控制澳大利亚的 COVID-19 疫情非常有效,避免了在当时 COVID-19 主要局限于中国时出现更大规模的疫情。本研究证明了针对高发病率国家实施旅行禁令的有效性。本研究可以为作为 COVID-19 疫情控制措施的旅行禁令的实施或解除提供决策依据。