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For preventing the spread of epidemics such as the coronavirus disease COVID-19, social distancing and the isolation of infected persons are crucial. However, existing reaction-diffusion equations for epidemic spreading are incapable of describing these effects. In this work, we present an extended model for disease spread based on combining a susceptible-infected-recovered model with a dynamical density functional theory where social distancing and isolation of infected persons are explicitly taken into account. We show that the model exhibits interesting transient phase separation associated with a reduction of the number of infections, and allows for new insights into the control of pandemics.
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10.1038/s41467-020-19024-0
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document_parses/pdf_json/dfb4983573a826a08cffb7d0c64a1e6b146227d8.json; document_parses/pdf_json/b2416a8b9c1acdb56dcde277ef0b6480e8e35cb3.json
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document_parses/pmc_json/PMC7643184.xml.json
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Effects of social distancing and isolation on epidemic spreading modeled via dynamical density functional theory
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