This STEM Volume gathers a selection of research papers on COVID-19 using a complex systems approach。 Methods include agent-based models， cellular automata， networks， population dynamics， spatial-temporal patterns， risk management， analysis of fat-tails， data analysis and visualization。 A few examples are: （i） Discussions about policies and strategies against outbreaks in the context of uncertainty and incomplete information。 （ii） Analysis and proper understanding of probability and its role in decision-making against contagion outbreaks。 （iii） Different approaches to model the spread of a virus in a population using simulations。 （iv） Applications with observational data to include natural patterns of human behavior into modeling and decision-making frameworks。