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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.