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. 2020 Mar 31;117(13):7504-7509.
doi: 10.1073/pnas.2002616117. Epub 2020 Mar 13.

Impact of international travel and border control measures on the global spread of the novel 2019 coronavirus outbreak

Chad R Wells  1 , Pratha Sah  1 , Seyed M Moghadas  2 , Abhishek Pandey  1 , Affan Shoukat  1 , Yaning Wang  3 , Zheng Wang  4 , Lauren A Meyers  5   6 , Burton H Singer  7 , Alison P Galvani  1
Affiliations

Impact of international travel and border control measures on the global spread of the novel 2019 coronavirus outbreak

Chad R Wells et al. Proc Natl Acad Sci U S A. .

Abstract

The novel coronavirus outbreak (COVID-19) in mainland China has rapidly spread across the globe. Within 2 mo since the outbreak was first reported on December 31, 2019, a total of 566 Severe Acute Respiratory Syndrome (SARS CoV-2) cases have been confirmed in 26 other countries. Travel restrictions and border control measures have been enforced in China and other countries to limit the spread of the outbreak. We estimate the impact of these control measures and investigate the role of the airport travel network on the global spread of the COVID-19 outbreak. Our results show that the daily risk of exporting at least a single SARS CoV-2 case from mainland China via international travel exceeded 95% on January 13, 2020. We found that 779 cases (95% CI: 632 to 967) would have been exported by February 15, 2020 without any border or travel restrictions and that the travel lockdowns enforced by the Chinese government averted 70.5% (95% CI: 68.8 to 72.0%) of these cases. In addition, during the first three and a half weeks of implementation, the travel restrictions decreased the daily rate of exportation by 81.3% (95% CI: 80.5 to 82.1%), on average. At this early stage of the epidemic, reduction in the rate of exportation could delay the importation of cases into cities unaffected by the COVID-19 outbreak, buying time to coordinate an appropriate public health response.

Keywords: COVID-19; SARS-CoV-2; disease importation; screening; surveillance.

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Conflict of interest statement

The authors declare no competing interest.

Figures

Fig. 1.
Fig. 1.
Exportation risk of SARS-CoV-2 cases from mainland China. (A) Daily risk, (B) cumulative risk of exportation of at least one case, and (C) risk of the initial exportation event from mainland China between December 6, 2019 and February 15, 2020. (D and E) Expected number of exported cases from mainland China traveling during the incubation period (blue) or symptomatic phase of the infection (yellow) (D) in the absence of travel lockdowns and (E) with travel lockdowns enforced. (F) Cases averted by the travel lockdowns. The colored band in A−C denotes the 95% credible interval. The vertical dashed lines indicate the start of two travel lockdowns in China: January 23, 2020 in Wuhan and January 25, 2020 for other cities in the Hubei province.
Fig. 2.
Fig. 2.
Country-level importation of SARS-CoV-2 cases. (A) International flight connections from mainland China. Color of the curves indicates the number of airports with flights to/from mainland China—lighter color are the routes to countries with the most airport connections. The blue circles indicate the number of international confirmed cases. Size of circles is proportional to the number of confirmed SARS-CoV-2 cases with travel history to China as of February, 15, 2020. (B) The risk of initial importation (yellow gradient) based on probability of an individual in mainland China to travel by flight (y axis), estimated each day between January 4, 2020 and January 31, 2020 (x axis). We found a statistically significant correlation (r = −0.43, P value = 0.05) between the reported arrival date of the initial case in 21 countries/regions and the airline weights proportional to the number of airports in the country with direct flights to and from mainland China. Vertical dashed lines indicate the travel bans that were enforced on January 23 in Wuhan and on January 25 for other cities in Hubei province.
Fig. 3.
Fig. 3.
Interventions to limit the impact of infected passengers in their incubation period. (A) Photograph of an alert in Delhi Indira Gandhi International Airport, India, educating passengers on the proper process if they develop symptoms. (B) The probability of identifying an infected individual traveling during their incubation period based on asking the time since their last exposure (infection) to a COVID-19 affected area. Colored band denotes the 95% credible interval. (C) The probability of an infected case traveling during their incubation period for varying lags in quarantine in mainland China following exposure (infection). Colored band denotes the 95% credible interval. (D) Estimated time between arrival of a case in the incubation period and symptom onset (yellow area) as well as first transmission event (red area). Time of symptom onset data for 30 imported cases worldwide is shown as dots—blue dots are the cases that displayed no symptoms upon arrival, and yellow dots are cases that were symptomatic upon arrival.
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