Work

Effects of social distancing and isolation on epidemic spreading modeled via dynamical density functional theory

Year: 2020

Type: article

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.

Source: Nature Communications

DOI: 10.1038/s41467-020-19024-0

Authors: Michael te Vrugt, Jens Bickmann, Raphael Wittkowski

Institution: University of Münster

Language: English

Topic: Mathematical and Theoretical Epidemiology and Ecology Models

Subfield: Applied Mathematics

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $5,380