The spreading time in SIS epidemics on networks

2018 ◽  
Vol 494 ◽  
pp. 317-330 ◽  
Author(s):  
Zhidong He ◽  
Piet Van Mieghem
Keyword(s):  
Spreading Time ◽  
Sis Epidemics

Spreading Time of Impacting Nanodroplets

2021 ◽  
Author(s):  
Yi-Bo Wang ◽  
Yi-Feng Wang ◽  
Yan-Ru Yang ◽  
Xiao-Dong Wang ◽  
Min Chen
Keyword(s):  
Spreading Time

scholarly journals Endemic Behaviour of SIS Epidemics with General Infectious Period Distributions

2014 ◽  
Vol 46 (01) ◽  
pp. 241-255 ◽  
Author(s):  
Peter Neal
Keyword(s):  
Epidemic Model ◽  
Branching Process ◽  
Endemic Equilibrium ◽  
Infectious Period ◽  
Sis Epidemic Model ◽  
Branching Process With Immigration ◽  
Sis Epidemic ◽  
Sis Epidemics ◽  
Surprising Observation

We study the endemic behaviour of a homogeneously mixing SIS epidemic in a population of size N with a general infectious period, Q, by introducing a novel subcritical branching process with immigration approximation. This provides a simple but useful approximation of the quasistationary distribution of the SIS epidemic for finite N and the asymptotic Gaussian limit for the endemic equilibrium as N → ∞. A surprising observation is that the quasistationary distribution of the SIS epidemic model depends on Q only through

scholarly journals The End Time of SIS Epidemics Driven by Random Walks on Edge-Transitive Graphs

2020 ◽  
Vol 179 (3) ◽  
pp. 651-671
Author(s):  
Daniel Figueiredo ◽  
Giulio Iacobelli ◽  
Seva Shneer
Keyword(s):  
Random Walks ◽  
Edge Transitive ◽  
Transitive Graphs ◽  
Sis Epidemics

scholarly journals Approximations: replacing random variables with their means

2014 ◽  
Vol 51 (A) ◽  
pp. 57-62
Author(s):  
Joe Gani
Keyword(s):  
Stochastic Process ◽  
Markov Chain ◽  
Continuous Time ◽  
Random Variables ◽  
Original Form ◽  
Continuous Time Markov Chain ◽  
Standard Methods ◽  
Sis Epidemics

One of the standard methods for approximating a bivariate continuous-time Markov chain {X(t), Y(t): t ≥ 0}, which proves too difficult to solve in its original form, is to replace one of its variables by its mean, This leads to a simplified stochastic process for the remaining variable which can usually be solved, although the technique is not always optimal. In this note we consider two cases where the method is successful for carrier infections and mutating bacteria, and one case where it is somewhat less so for the SIS epidemics.

The Collision Behavior of Droplets Splitted from a Droplet that Rebounded on Super-Hydrophobic Surface

2015 ◽  
Vol 723 ◽  
pp. 968-971 ◽  
Author(s):  
Zheng Yong Huang ◽  
Jian Li ◽  
Fei Peng Wang ◽  
Huan Huan Xia ◽  
Mao Chang Li
Keyword(s):  
Contact Time ◽  
Hydrophobic Surface ◽  
Reynolds Numbers ◽  
Elastic Collision ◽  
Water Droplets ◽  
Water Contact ◽  
Ice Accumulation ◽  
Pollution Flashover ◽  
Water Accumulation ◽  
Spreading Time

Droplet rebounding on super-hydrophobic surfaces is critical to suppress pollution flashover (i.e. enhancement of pollution flashover-voltage) and to reduce ice accumulation on insulators. This paper presents a novel way to reduce water accumulation on surface via the elastic collision between droplets splitted from a droplet that has rebounded from super-hydrophobic surface. The water-mass that contacted with surface will be reduced resultantly. The influence of hydrophobicity of the surface on contact time and spreading time of water droplets are discussed. The collision behavior between the splitted droplets is indicated by the surface charge that was induced by the rebounding droplets on super-hydrophobic surface. Experimental results show that the super-hydrophobic surface endows water droplets with shorter contact time, spreading time than those values obtained on a bare glass. Specific Web and Reynolds numbers can lead to the elastic rebounding between water droplets, delaying the water contact with the super-hydrophobic surface. The contact electrification between the rebounded droplet and the super-hydrophobic surface renders the droplet charged, thus determines the collision behavior of the splitted droplets that born from the rebounded droplet.

scholarly journals Bi-Virus SIS Epidemics over Networks: Qualitative Analysis

2015 ◽  
Vol 2 (1) ◽  
pp. 17-29 ◽  
Author(s):  
Augusto Santos ◽  
Jose M. F. Moura ◽  
Joao M. F. Xavier
Keyword(s):  
Qualitative Analysis ◽  
Sis Epidemics
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