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).