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The lack of medical treatments and vaccines upon the arrival of the SARS-CoV-2 virus has made non-pharmaceutical interventions the best allies in safeguarding human lives in the face of the COVID-19 pandemic. Here we propose a self-organized epidemic model with multi-scale control policies that are relaxed or strengthened depending on the extent of the epidemic outbreak. We show that optimizing the balance between the effects of epidemic control and the associated socio-economic cost is strongly linked to the stringency of control measures. We also show that non-pharmaceutical interventions acting at different spatial scales, from creating social bubbles at the household level to constraining mobility between different cities, are strongly interrelated. We find that policy functionality changes for better or worse depending on network connectivity, meaning that some populations may allow for less restrictive measures than others if both have the same resources to respond to the evolving epidemic. • A higher stringency of local measures facilitates epidemic control, resulting in a train of epidemic waves manageable from a health point of view. • More stringent measures provide less disruption to the socio-economic fabric than in the case of the implementation of lax measures. • Focusing on the different autonomous communities of Spain, we show that their different architectures drive the outcome of control measures. • Those most connected regions demand more stringent measures at the local level to achieve the desired epidemic control. [ABSTRACT FROM AUTHOR]