Results
In this analysis, a total number of 187,755 flights were simulated across 24 airports and ten countries estimating around 33.9 million passenger seats. The importation risk indices of the individual countries for various airports estimated are shown in Fig. 1. As evident from Fig. 1 the Middle Eastern countries posed the highest risk indices followed by UK, Italy, and USA. It is important here to note that the current simulation does not take an account of transit passenger; for example, a passenger originating from JFK arriving in BOM via DXB, would be assigned as a passenger from DXB and not from JFK. The estimated importation risk index is consistent with observed data obtained from various government sources that 7 airports from middle east brought in the maximum number of 2019-nCoV infected passengers (~300) in India until the international flights were suspended. It is important to note that Emirates Airlines, a Dubai based airlines, operates 172 flights per week to India serving nine destinations (Emirates and India; partners in economic growth 2018), which is by far highest number of flights and destination by any other foreign airlines. Further, in 2017-18 Emirates has reported 87% of the seat factor and assuming that 50% of them are transit passengers arriving from Europe and USA, thus by far, it is an extremely fair and valid assumption that Dubai airport (and other transit airport) could be a potential hotspot in future for infection during a disease outbreak. As shown in Fig. 2 the importation risk index for various countries (airports clubbed together) clearly showing the middle east having the highest risk index. A certain amount of risk, although significantly lower than middle east airports, was also posed by passengers originating at LHR and taking the direct flights to India. As expected, the third highest importation risk was posed by Italy, which was one of the worst affected countries during our study window. It is also to be noted that Indian Government has operated special flights to bring back the stranded citizen from Italy. Surprisingly and contrary to expectation the direct travelers from China posed the lowest risk (Fig. 2), this could be due to potentially much lower numbers of passenger exchange with China as compared to other countries. While importation risk index does not directly represent the number of infected passengers imported in a country it is important to have the robust validation of the methodology. For this purpose, a scatter plot between number of confirmed imported cases from various countries and importation risk index is shown in Fig. 3. As evident from the figure a correlation (R 2=0.99) clearly indicates the strong agreement between number of passengers imported from a specific country and corresponding importation risk index. There is approximately factor of 6 difference between highest number of passengers (from middle east; ~300 passengers) and second highest from United Kingdome (~50 passenger). To avoid any bias in the representation of correlation we have also plotted the scatter plot between all the countries (excluding middle east) and importation risk index (show in inset in Fig. 3) and observed the strong relation (R 2=0.91).