Project
Shape Theorems for Infection Spreading in Random Graphs
Project Heads
Wolfgang König, Benedikt Jahnel
Project Members
Alexander Hinsen
Cooperation Partner
Project Duration
Part of MATH+ Project EF4-1: Influence of mobility on connectivity (01.01.2019 – 31.12.2021)
Located at
Weierstrass Institute Berlin, Research group 5
Description
The analysis and prediction of the spread of infections such as the coronavirus are characterized by numerous uncertainties, for example, regarding spatial clustering or the individual transmission rate of individuals. Researchers of the group Interacting Random Systems at Weierstrass Institute Berlin are investigating corresponding stochastic epidemic models on random networks. The approach is based on the theory of marked spatial point processes and interacting Markov processes with strong links to the theory of continuum percolation and random tessellations. The research enables, among other things, predictions about the speed of propagation, the form of infected clusters and possible decentralized countermeasures. The methods were initially developed in the context of malware propagation in ad hoc telecommunication networks and are now being further developed also for epidemiological applications.
Keywords
random graphs, stochastic growth models, interacting particle systems
More Information
A. Hinsen, B. Jahnel, E. Cali, J.-P. Wary, Phase transitions for chase-escape models on Poisson-Gilbert graphs, Electron. Commun. Probab., 25:25 (2020), https://projecteuclid.org/euclid.ecp/1585188174
Project Type
MATH+ project
Project Funding
MATH+