Forecast of the Development of COVID-19 Based on the Small-World Network

Abstract

This world has faced a severe challenge since the breakout of the novel Coronavirus-2019 (COVID-19) has started for more than one year. With the mutation of the virus, the measures of epidemic prevention are keeping upgrading. Various vaccines have been created and brought into operation. To accurately describe and predict the spread of COVID-19, we improve the traditional Susceptible-Exposed-Infected-Removed-Dead model(SEIRD), forecast the development of COVID-19 based on small-world network. A small-world network is a type of mathematical graph in which most nodes are not neighbors of one another, but the neighbors of any given node are likely to be neighbors of each other, and most nodes can be reached from every other node by a small number of hops or steps. We introduce new parameters, Vaccination(V) and Quarantine(Q), into this model. Based on this, through regressing and analyzing the epidemic in the UK, we get the simulation that fits well with the observed data in other countries.