Abstract: Disease spreading are ubiquitous processes in social networks. The modelling of the propagation of an infectious agent depends not only on the basic reproduction number, which gives the average number of secondary cases in a susceptible population, but also on the pattern of contact between subjects. In this talk, we will discuss the modelling of epidemic processes in networks, including rumour and disease propagation. We will introduce a model of epidemic spreading with awareness, where the disease and information are propagated in different layers with different time scales. We will show that the time scale determines whether the information awareness is beneficial or not to the disease spreading. Finally, we will show how machine learning can be applied to predict the capacity of propagation of each node and quantify how network properties influence the propagation of the infectious agent. Zoom connection details: https://uwa.zoom.us/j/95532826920?pwd=WHp6UzhaWGVrV2RERzFwa0ZQM1c2QT09 Meeting ID: 955-3282-6920 Password: 967084 **Recordings of previous seminars can now be found here: https://sites.google.com/view/uwa-complex/home *** This seminar is organised by the system complex group - Western Australia