Abstract
This publication describes the global spread of COVID-19 in mathematical terms from its beginning in Wuhan, China. Using the techniques of graph theory and matrix algebra, the airports servicing Seoul and London are identified as most in need of passenger screening to prevent the global spread of infectious disease by air travelers during a pandemic. Furthermore, it is the trace of powers of the adjacency matrix – which is the matrix that characterizes the network of flights connecting cities on a regional or global scale – that is proportional to the infection risk of any given network of flights. It will be demonstrated that relatively small network changes can result in a significant reduction of infection risk, with a minimal reduction of passenger throughput. The infection risk posed by population migration is more difficult to characterize than that posed by air travel, although the two are related. However, chaos theory suggests that once the infectiousness of a disease (as measured by the reproduction number, the number of people that each sick person can infect in a fully susceptible population) exceeds a threshold of about 4, the future number of active cases becomes difficult to predict; a phenomenon that is exacerbated by extreme sensitivity to initial conditions. That is to say, individual cases can make large changes in the future course of a pandemic, making accurate long-term prediction impossible.