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The COVID‐19 pandemic in a population modelled as a network wherein infection can propagate both via intra‐ and inter‐group interactions is simulated. The results emphasize the importance of diminishing the inter‐group infections in the effort of substantial flattening/delaying of the epi(demiologic) curve with concomitant mitigation of disastrous economy and social consequences. To exemplify, splitting a population into  m  (say, 5 or 10) noninteracting groups while keeping intra‐group interaction unchanged yields a stretched epidemiological curve having the maximum number of daily infections reduced and postponed in time by the same factor  m  (5 or 10). More generally, the study suggests a practical approach to fight against SARS‐ CoV‐ 2 virus spread based on population splitting into groups and minimizing intermingling between them. This strategy can be pursued by large‐scale infrastructure reorganization of activity at different levels in big logistic units (e.g., large productive networks, factories, enterprises, warehouses, schools, (seasonal) harvest work). Importantly, unlike total lockdown, the proposed approach prevents economic ruin and keeps social life at a more bearable level than distancing everyone from anyone. The declaration for the first time in Europe that COVID‐19 epidemic ended in the two‐million population Slovenia may be taken as support for the strategy proposed here.

advanced theory and simulations

Suppression of Groups Intermingling as an Appealing Option for Flattening and Delaying the Epidemiological Curve While Allowing Economic and Social Life at a Bearable Level during the COVID‐19 Pandemic