Bibliogr. s. 82-84

This chapter explores the dynamics of complex systems, focusing on suboptimization, contagion, and self-learning in the context of the COVID-19 pandemic. It examines how suboptimization within these systems influences contagion mechanisms, and explores the role of self-learning in managing widespread contagion events. The study integrates theoretical frameworks and empirical observations, particularly analysing China’s pandemic response and its global impact. By highlighting the interplay of centralization, decentralization, and adaptive learning in systemic responses to health crises, the chapter contributes to a deeper understanding of complex systems in global health management. It also refers to the problem of the role of COVID-19 in the amplification of Chinese structural problems, hence influencing its global position.