Medicine and Health

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

M. T. Vrugt, J. Bickmann, et al.

Discover groundbreaking research by Michael te Vrugt, Jens Bickmann, and Raphael Wittkowski, focusing on a novel model that combines the SIR framework with dynamical density functional theory. Learn how social distancing and isolation can lead to significant reductions in disease spread, offering fresh perspectives on pandemic control strategies.

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Playback language: English

Index

Abstract

Social distancing and isolation of infected individuals are crucial for epidemic control. This paper presents an extended model for disease spread, combining a susceptible-infected-recovered (SIR) model with dynamical density functional theory (DDFT). The model explicitly accounts for social distancing and isolation, demonstrating transient phase separation linked to infection reduction and offering new insights into pandemic control.

Publisher

Nature Communications

Published On

Nov 04, 2020

Authors

Michael te Vrugt, Jens Bickmann, Raphael Wittkowski

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