Probabilistic and mean-field model of COVID-19 epidemics with user mobility and contact tracing

2020/09/11 by Marianne Akian, M. Akian, L. Ganassali +9
Computer Science · Mathematics · Medicine · #COVID-19 Digital Contact Tracing #COVID-19 epidemiological studies #Data-Driven Disease Surveillance #msc:62P10 #msc:92-10 #stat.AP #stat.ME

paper · pdf · doi:10.48550/arxiv.2009.05304

23 pages, 5 figures

arxiv created 2020/09/11 · arxiv updated 2020/09/14

Abstract

We propose a detailed discrete-time model of COVID-19 epidemics coming in two flavours, mean-field and probabilistic. The main contribution lies in several extensions of the basic model that capture i) user mobility - distinguishing routing, i.e. change of residence, from commuting, i.e. daily mobility - and ii) contact tracing procedures. We confront this model to public data on daily hospitalizations, and discuss its application as well as underlying estimation procedures.

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