Information spreading analysis is an important problem in the scientific community and is widely studied today using different techniques, from the data analysis to the agent-based modelling. For some extreme situations, like fire or flood, there is little or no reliable information about users’ activity available. That is why an efficient simulation of the urgent scenarios is very important, because analysis of the simulated data can help to provide fast and accurate reaction and save human lives. In this paper, we present a multi-layer agent-based network model for the information diffusion simulation in the urgent scenarios, which allows to investigate agents’ behavior in a variety of situations in the absence of the real data. This model can be used for the urban scenarios simulation in the integration with other agent-based human interaction models. Experimental: results demonstrate good results in comparison with existing works in this area and give a number of insights regarding the further model development. © 2017 Elsevier B.V.