Methods

Data
We extracted modelled flight data for the final destination of passengers travelling from four Chinese cities (including domestic and international destinations) from the FLIRT database [12, 13]. FLIRT was designed to predict the flow and likely destination of infected travellers through the air travel network. It uses a database of flight schedules from over 800 airlines and displays direct flight connections in addition to a modelled end destination (three-letter IATA code for airports). Flight connection data and passenger numbers are based on the data collected since October 2014 [12]. We extracted the simulated passenger's data for each week for the period of 1 January to 31 January 2020 from four major Chinese cities: Wuhan, Beijing, Shanghai and Guangzhou. The simulation can process up to 20 000 passengers' information for a particular time frame from any city (including surrounding airports). We collected the reported 2019-nCoV case data from the WHO's daily situation update website [14].

Estimation of risk of transmission
To estimate the relative risk of 2019-nCoV transmission, we considered all infected passengers who travelled between 1 January and 31 January to possess a maximum risk of transmission 1 (and no infected passengers means no risk) and estimated the relative risk of each country based on the number of passengers who travelled from each of the four cities. Thus countries with a higher number of passengers travelling from any of these cities had a higher risk of transmission. We then weighted the risk estimated for each city with the number of reported infected people in each city by 31 January 2020 [14] and estimated the mean average risk of transmission termed as ‘Risk index’ which follows the equation below:where x is the destination country, Risk index (x) is the risk of infection importation in country x, P(x)n is the number of passengers to country x from city n, Pn is the total number of passengers who left city n, In is the number of infected people in city n and Cn is the population size of city n. The risk index denotes the risk of at least one case being imported into a country or territory where 1 means an absolute certainty and 0 means no risk at all. Our model assumed that there is no case outside China and thus ignored if any country already had imported case(s). In countries where 2019-nCoV is already detected, the risk index would explain the risk of importing additional infected individuals from China.
We performed a Pearson correlation coefficient test between the risk index of the country and the WHO's reported case number from the country. We grouped the countries in four quantiles based on the risk index where high-risk countries were grouped as the 4th (>75th percentiles) and the 3rd (>50th to ⩽75th percentiles) quantiles and low-risk countries were grouped as the 2nd (>25th to ⩽50th percentiles) and the 1st (⩽25th percentile) quantiles (Table 1).
Table 1. The list of countries or territories based on their risk index in different quantiles for 2019-nCoV (SARS-COV-2) transmission
4th Quantile risk index (highest risk) 3rd Quantile risk index 2nd Quantile risk index 1st Quantile risk index (lowest risk)
Sl/Rank Country Risk index Country Risk index Country Risk index Country Risk index
1 China 0.609603126 Sweden 0.000320248 Kenya 3.53  ×  10−05 Jamaica 3.84  ×  10−06
2 Thailand 0.099432816 Laos 0.000296262 Peru 3.18  ×  10−05 Serbia 3.22  ×  10−06
3 Cambodia 0.05294058 Brazil 0.00027186 Algeria 3.11  ×  10−05 Togo 2.73  ×  10−06
4 Malaysia 0.041899039 Denmark 0.000254904 French Polynesia 3.07  ×  10−05 Uganda 2.71  ×  10−06
5 Canada 0.02730388 Oman 0.000248884 Iceland 3.00  ×  10−05 Tonga 2.69  ×  10−06
6 USA 0.021169936 Israel 0.000221865 Samoa 2.74  ×  10−05 The Bahamas 2.39  ×  10−06
7 Japan 0.01479856 Ukraine 0.000209515 Tanzania 2.73  ×  10−05 Cote d'Ivoire 2.02  ×  10−06
8 India 0.010256629 Poland 0.0002 Palau 2.63  ×  10−05 Suriname 2.01  ×  10−06
9 UK 0.008786839 Brunei 0.000181028 Djibouti 2.45  ×  10−05 Vanuatu 1.99  ×  10−06
10 South Korea 0.008072566 Czech Republic 0.000179806 Belarus 2.40  ×  10−05 Albania 1.90  ×  10−06
11 Vietnam 0.007928803 Northern Mariana Islands 0.000177972 Bosnia and Herzegovina 2.40  ×  10−05 Malta 1.73  ×  10−06
12 Singapore 0.007784474 Belgium 0.000175566 Cook Islands 2.26  ×  10−05 Guinea 1.60  ×  10−06
13 Hong Kong 0.007636714 Maldives 0.000172453 Colombia 1.94  ×  10−05 Namibia 1.55  ×  10−06
14 Indonesia 0.007197131 Norway 0.000171441 Papua New Guinea 1.88  ×  10−05 Democratic Republic of Congo 1.41  ×  10−06
15 United Arab Emirates 0.007089607 Kuwait 0.000166929 Nigeria 1.85  ×  10−05 Rwanda 1.22  ×  10−06
16 France 0.006814962 Egypt 0.000139373 Jordan 1.83  ×  10−05 Honduras 1.02  ×  10−06
17 Turkey 0.00568808 Iran 0.000137181 Cuba 1.79  ×  10−05 Gabon 8.98  ×  10−07
18 Australia 0.005671745 Mongolia 0.000132319 Argentina 1.70  × 10−05 Republic of Congo 7.22  ×  10−07
19 Russia 0.005592859 Chile 0.000129975 Tunisia 1.65  ×  10−05 Bermuda 5.99  ×  10−07
20 Pakistan 0.004811284 North Korea 0.000128562 Ghana 1.61  ×  10−05 Antigua and Barbuda 3.52  ×  10−07
21 Qatar 0.004113225 Mauritius 0.000126679 Armenia 1.53  ×  10−05 Barbados 3.52  ×  10−07
22 Macau 0.003373727 Portugal 0.000113251 Dominican Republic 1.46  ×  10−05 Cape Verde 3.52  ×  10−07
23 Germany 0.003176858 Uzbekistan 9.67  ×  10−05 New Caledonia 1.34  ×  10−05 Guyana 3.52  ×  10−07
24 Italy 0.002753413 Hungary 8.97  ×  10−05 Cyprus 1.29  ×  10−05 Madagascar 2.99  ×  10−07
25 Philippines 0.002740638 Azerbaijan 8.64  ×  10−05 Bhutan 1.25  ×  10−05 Grenada 2.47  ×  10−07
26 Taiwan 0.002590034 Croatia 8.57  ×  10−05 Nepal 1.25  ×  10−05 Bolivia 1.76  ×  10−07
27 Belize 0.002009996 Tajikistan 8.50  ×  10−05 Slovenia 1.24  ×  10−05 Burkina Faso 1.76  ×  10−07
28 Ethiopia 0.001469205 Bahrain 6.31  ×  10−05 Moldova 1.22  ×  10−05 Cameroon 1.76  ×  10−07
29 Finland 0.001307074 Fiji 6.29  ×  10−05 Kosovo 1.21  ×  10−05 Chad 1.76  ×  10−07
30 Sri Lanka 0.001179859 Kyrgyzstan 6.22  ×  10−05 Zambia 1.20  ×  10−05 Mozambique 1.76  ×  10−07
31 The Netherlands 0.000980799 Afghanistan 6.16  ×  10−05 El Salvador 1.05  ×  10−05 Paraguay 1.76  ×  10−07
32 New Zealand 0.000971254 Panama 5.91  ×  10−05 Romania 7.56  ×  10−06 Solomon Islands 1.76  ×  10−07
33 Greece 0.000958209 Morocco 5.60  ×  10−05 Guatemala 6.92  ×  10−06 Syria 1.76  ×  10−07
34 Bangladesh 0.000831196 Iraq 5.54  ×  10−05 Angola 6.77  ×  10−06 Uruguay 1.76  ×  10−07
35 Myanmar 0.000803755 Bulgaria 5.07  ×  10−05 Costa Rica 6.41  ×  10−06 Venezuela 1.76  ×  10−07
36 Saudi Arabia 0.000750981 Lithuania 4.99  ×  10−05 Trinidad and Tobago 6.13  ×  10−06 Zimbabwe 1.76  ×  10−07
37 Spain 0.000564876 Seychelles 4.82  ×  10−05 Sudan 5.66  ×  10−06 Libya 1.23  ×  10−07
38 Switzerland 0.00056232 Lebanon 4.47  ×  10−05 Ecuador 5.56  ×  10−06 Macedonia 1.23  ×  10−07
39 Austria 0.000498664 Georgia 4.37  ×  10−05 Puerto Rico 4.68  ×  10−06 Saint Lucia 1.23  ×  10−07
40 South Africa 0.000468876 Latvia 4.06  ×  10−05 Turkmenistan 4.42  ×  10−06 Sierra Leone 1.23  ×  10−07
41 Kazakhstan 0.000443175 Luxembourg 3.80  ×  10−05 Mauritania 4.09  ×  10−06 Somalia 1.23  ×  10−07
42 Ireland 0.000371199 Estonia 3.69  ×  10−05 Timor-Leste 1.23  ×  10−07
43 Mexico 0.000322198
44
Number of countries/territories: 168 Africa: 2 Africa: 3 Africa: 11 Africa: 19
Asian: 22 Asian: 16 Asian: 4 Asian: 2
Pan-Europe:13 Pan-Europe: 18 Pan-Europe: 9 Pan-Europe: 4
North America: 4 North America: 0 North America: 3 North America: 7
Oceania: 2 Oceania: 2 Oceania: 6 Oceania: 3
South America: 0 South America: 3 South America: 8 South America: 7
Total: 43 Total: 42 Total: 41 Total: 42