key: cord-0765925-hc54adkh authors: McLure, Angus; Lau, Colleen L; Furuya-Kanamori, Luis title: Has the effectiveness of Australia’s travel bans against China on the importation of COVID-19 been overestimated? date: 2020-10-10 journal: J Travel Med DOI: 10.1093/jtm/taaa191 sha: 090b3aff13b187292c0aa249b60f67d75954f6a5 doc_id: 765925 cord_uid: hc54adkh In our re-analysis with adjusted assumptions, we found that a previous study substantially oversestimated the effectiveness of Australia’s complete travel ban against China in the introduction of SARS-CoV-2 into Australia. We read with interest a model by Costantino et al., 1 which found that Australia's complete travel ban on China (during its epidemic peak) was highly effective in limiting the introduction of SARS-CoV-2 into Australia and reduced Australia's COVID-19 cases by 87%. The authors verified their model by predicting the number of cases in Australia by the 7 March; however, in the model all 57 predicted cases were due to importation from China or subsequent domestic transmission, whereas the majority of the reported 66 cases were actually linked with travel from countries other than China. 2 Their model consisted of four components: (i) the number of cases in China (using the World Health Organization data up to 23 February 2020 and forecasted cases thereafter); (ii) a constant ratio of reported versus actual cases; (iii) importation assuming that infection status and probability of travel to Australia were independent and (iv) transmission within Australia. We believe the assumptions used in the third component led to a substantial overestimate of the impact of Australia's early travel ban on China. Their model considered China as a single location, i.e. did not consider the severe lockdown of Hubei starting on the 23 January, the significantly lower incidence in other provinces or the population distribution. Though Hubei residents account for ∼ 4% of the Chinese population 3 and <3% of Chinese travellers to Australia in 2019, 4 85.2% of all Chinese cases reported between 1 February (the start of the travel ban) and 4 April were from this province. 5 Travel bans have been widely implemented during the pandemic. Their impact depends on incidence in the source country and likelihood of an infected person travelling to the destination country. 6 In the case of Australia's travel ban on China, even though incidence was high in Hubei, the likelihood of a Hubei resident travelling to Australia at that time was extremely low. We re-estimated the number of cases that would have been imported under each travel ban scenario. Mathematically, the only change was to component 1, for which we excluded all cases reported in Hubei after 23 January. This was equivalent to assuming that (i) Hubei residents were unable to travel to Australia after 23 January, regardless of travel ban scenarios and (ii) the volume of travellers to Australia from Hubei and the rest of China was population proportionate. 3 ,4 The full description of the model and the R code are presented in the supplementary material. With the adjusted assumptions, the number of infected Chinese travellers arriving in Australia between 26 January and 4 April without any travel ban (scenario 1), with ban followed by a full lift (scenario 2) and ban followed by a partial lift (scenario 3) were 84%, 69% and 57% lower than the original estimates ( Table 1 ). The revised estimates predict that between 1 February and 4 April, Australia's travel ban on China prevented the importation of ∼17 cases; whereas over the same time period, the large majority (>75%) of the 3174 overseasacquired cases were imported from Europe, the USA and cruise ships. 2 The effectiveness of full and partial travel bans against COVID-19 spread in Australia for travellers from China during and after the epidemic peak in China Coronavirus disease (COVID-19) Epidemiology Reports 2-6 Population at Year-end by Region International Market Performance Statistics Novel Coronavirus Situation Reports The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak Supplementary data are available at JTM online.