The course objective is to acquire necessary knowledge for decision making in disaster and fire risk management process.

After passing the exam, students will be trained to identify and classify the system, analyze the risks at all stages of the disaster cycle and assess the circumstances and their influence on the outcome of the decision-making process in terms of both prevention and the realization of a catastrophic event.

Basics of probability theory (sample space and events, probability definitions, conditional probabilities, Bayes rule); Descriptive statistics (measures, graphical representations); Uncertainty modeling (random variables, stochastic processes and extreme values); Estimation, statistical tests and model building ( Parameter estimation, Statistical tests, Model building and evaluation); Bayesian decision analysis. System definition, Systems view of integrated disaster management, System formulation examples, Simulation, System dynamics simulation, System approach to Disaster risk management, Source of uncertainty, Conceptual risk definition, Probabilistic approach, Engineering decisions under uncertainty, Decision making and integrated risk management: Individual decision making, Decision making in organizations, Decision making in government, Implementation of system analysis to management of disasters, Human behaviour during disasters

The course is held via auditory lectures accompanied by slides and examples case studies of good practice which will encourage detailing and solving certain problems. Visits to enterprises and institutions are also planed, as well as the lectures provided by experts.