Endemic Behaviour of SIS Epidemics with General Infectious Period Distributions

Epidemics with general generation interval distributions.

We study the spread of susceptible-infected-recovered (SIR) infectious diseases where an individual's infectiousness and probability of recovery depend on his/her "age" of infection. We focus first on early outbreak stages when stochastic effects dominate and show that epidemics tend to happen faster than deterministic calculations predict. If an outbreak is sufficiently large, stochastic effec...

in stochastic SIS epidemics

The impact of the infectious period on epidemics

The duration of the infectious period is crucial in determining the ability of an infectious disease to spread. We consider an epidemic model that is network-based and non-Markovian, containing classic KermackMcKendrick, pairwise, message passing and spatial models as special cases. For this model, we prove a monotonic relationship between the variability of the infectious period (with fixed me...

Modeling Simple Epidemics: SIS MODEL

This poster examines the question of how to model an epidemic. There are two standard modeling procedures: Deterministic model and Stochastic model. Deterministic modeling considers a structured mathematical framework, where one takes the actual number of new cases in a short interval of time to be proportional to the number of both susceptible and infectious individuals, as well as the length ...

SIS epidemics on Triadic Random Graphs

It has been shown in the past that many real-world networks exhibit community structures and non-trivial clustering which comes with the occurrence of a notable number of triangular connections. Yet the influence of such connection patterns on the dynamics of disease transmission is not fully understood. In order to study their role in the context of Susceptible-Infected-Susceptible (SIS) epide...