Certain methods for investigating epidemics and preventing the spread of viruses in self-organizing systems.

Investigation and control of epidemic phenomena, as well as introduction of methods for preventing the spread of viruses, are always up-to-date. In this context, the paper presents newer methods of modeling the dynamics of epidemics in self-organizing systems based on cellular automata. Methods and approaches for behavioral analysis of epidemic waves, also for statistical data processing, are promoted and validated in terms of obtained theoretical results. Recovery of causality in multilevel graphs simulating epidemic situations observed over time is given ac-cordingly. A multi-user software platform designed for the purpose enables collective observation and operation of dynamic processes. This also makes it possible to conduct comprehensive analysis of epidemiological procedures and dynamical prediction of target parameters. Cryptographic algorithms and data anonymization techniques of proven security have been suggested to protect personal information at all levels of data acquisition, storage, transfer and processing. A method for synthetic data generation enabling simulation and investigation of the spread of viruses has been introduced and estimated accordingly. [ABSTRACT FROM AUTHOR]