Special Issue "Spatial Transmission Dynamics"
Deadline for manuscript submissions: closed (28 February 2021) | Viewed by 228
Interests: stochastic geometry; wireless networks; random geometric graphs; spatial statistics; stochastic modeling
Recent developments demonstrate that understanding the dynamics of spatial transmission phenomena, including the spread of infectious diseases, is vital. Traditional models such as the SIR (susceptible-infectious-recovered) model aim at capturing the temporal dynamics of a homogeneous population in which everybody has the same probability of infecting everybody else. Such models do not capture the proximity between agents, which is known to have a critical impact on propagation (viz. physical distancing), is ignored. Accordingly, a promising improvement is to incorporate a spatial (geometric) component in the model, where the transmission probabilities depend on the distances between the agents.
Quite analogously, the reliability of a transmission in wireless networks strongly depends on the link distance, i.e., the spatial spreading of a disease in a population and the propagation of information in a wireless network appear to be governed by similar mechanisms. As a result, the two traditionally separate fields of research may cross-fertilize new techniques that have the potential to lead to breakthroughs in the modeling and/or analysis.
The aim of this Issue is to bring together state-of-the-art research contributions that give new insights into the dynamics of spatial transmission phenomena.
The key areas for this Special Issue include but are not limited to the following:
spatial and spatiotemporal statistics; data-driven approaches; simulation techniques; stochastic geometry; percolation analyses; metapopulation models; continuum methods and PDE limits; epidemic trails; effect of physical distancing; effect of host or node mobility; effect of population heterogeneity
Prof. Dr. Martin Haenggi
Manuscript Submission Information
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- Spatial Epidemics
- Information Propagation
- Spread of Infectious Diseases
- Spread of Rumors
- Spatial Probabilistic Models.