On-line platform for the short-term prediction of risk of expansion of epidemics

This paper proposes a novel approach for the prediction of the risk of expansion of local epidemics to 3rd regions or countries in the world through the air traffic network. The approach relies on the definition of a new indicator, the Imported Risk, which represents the overall risk of having infected individuals entering an airport from any other airport with connections. We performed a proof-of-concept of the proposed approach by using daily data of the air traffic movements on a global scale and of the evolution of the COVID-19 epidemic at the beginning of 2020. For that purpose, we developed a complex network model based on Tagged Graphs to calculate the Imported Risk indicator, together with other complementary indicators showing the centrality of the air traffic network weighted with the Imported Risk. We implemented our complex network model into an on-line platform which provides the daily risk of expansion of the epidemic to other regions or countries. The platform supports the identification of the components of the network (airports, routes…) that have a major impact on the risk of expansion. The paper also provides findings on how the short-term prediction of diseases’ expansion through the Imported Risk indicator allows the identification of effective measures to take control of the virus spread.