Effects of social distancing and isolation on epidemic spreading modeled via dynamical density functional theory
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Abstract 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.
2021 ◽
Vol 236
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pp. 116513
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2019 ◽
Vol 21
(44)
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pp. 24478-24488
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1998 ◽