Nonuniform Temporally Stochastic Cellular Automata as Model of Contagious Disease Spread

In this paper, we introduce a new cellular automaton (CA) variant called the nonuniform temporally stochastic CA (NTSCA), where an NTSCA contains a sequence of temporally stochastic cellular automata (TSCAs). Different TSCAs are used for different time frames during the evolution of the model to simulate the propagation of contagious viruses. We also propose the idea of a distant neighbor to depict the spread of viruses that occurs when asymptotic carriers are transported large distances. The essence of this spread is embodied by a specific set of features. These features are included in the NTSCA by utilizing information propagation, information cooking and partial blocking of information. Based on these parameters, the required rules are identified and used in the applied TSCAs. The dynamical changes of TSCAs during evolution make the system chaotic and enable imitating the propagation of diseases. We successfully imitate the spread of two such contagious diseases borne by viruses, COVID-19 (in India) and SARS 2003 (in China) and compare the results with real-time data.