Research on adaptive transmission and controls of COVID-19 on the basis of a complex network.

COVID-19 has caused massive disruption on the global economy and presents a considerable risk to human lives. Some countries have successfully controlled the pandemic by adopting strict measures, such as lockdown and travel restriction, but such methods are difficult to be applied widely due to their huge costs. To explore available and low-cost solutions, this study proposes an adaptive transmission model on the basis of a complex network, and gives control simulation method of COVID-19. The suggested model considers adaptive changes such as travel network and people's travel intention to form a three-level adaptive network transmission model among cities, communities, and people. The improved susceptible-exposed-infectious-recovered-dead transmission process is integrated into the network. Simulation experiments under high-, low-, and conventional-cost controls are performed. In these experiments, the travel restriction and closing cities are considered, and sensitivity analyses of the parameters are conducted to explore low-cost measures. Meanwhile, time duration and application conditions of different controls are discussed. Results show that lockdown is the most effective way, and the contact and infection rates are the two most important factors to control the pandemic. Low-cost combined control measures are feasible and effective for most countries. Finally, several suggestions are given for national and urban preventions and controls of COVID-19 and other infectious diseases in the future.