A stochastic SIS infection model incorporating indirect transmission

A Stochastic Sis Infection Model Incorporating Indirect Transmission

We describe a stochastic susceptible–infective–susceptible (SIS) model for transmission of infectious disease through a population, incorporating both direct host–host transmission and indirect transmission via free-living infectious stages (e.g. environmental bacteria). Existence of a quasi-stationary distribution conditional upon nonextinction of infection is established. A bivariate Ornstein...

A model for ovine brucellosis incorporating direct and indirect transmission.

In this work, we construct and analyse an ovine brucellosis mathematical model. In this model, the population is divided into susceptible and infected subclasses. Susceptible individuals can contract the disease in two ways: (i) direct mode - caused by contact with infected individuals; (ii) indirect mode - related to the presence of virulent organisms in the environment. We derive a net reprod...

A Stochastic Model for Indirect Condition Monitoring Using Proportional Covariate Model

This paper introduces a model to make decision on the maintenance of a mechanical component subject to condition monitoring. A stochastic model is used to determine what maintenance action should be taken at a monitoring check and the follow up inspection times. The condition of component has a stochastic relation with measurements. A new state space model is developed and used, to predict the ...

A Multi-Year Scenario-Based Transmission Expansion Planning Model Incorporating Available Transfer Capability

This paper presents a multi-year scenario-based methodology for transmission expansion planning (TEP) in order to enhance the available transfer capability (ATC). The ATC is an important factor for all players of electricity market who participate in power transaction activities and can support the competition and nondiscriminatory access to transmission lines among all market participants. The...

in stochastic SIS epidemics