Cellular automaton approach for the urban planning influence estmation on the social and economic indicators while a disease spreading

The aim was to investigate how does a city configuration influence on a lethal disease spread. For this purpose, several configurations for subareas with high and low population density are considered. The spread was simulated via a stochastic cellular automata approach, with the main indicators being determined as average over a set of runnings. Since the automaton was based on a SIRS model, as an economic indicator we used the simultaneous sick number, as a social – cumulative dead number. In addition, we considered Manshift losses as a cost loss parameter. The simulation results yield that for the minimal dead number and economic losses it is preferable to use a regular grid of square-shaped low-density subareas. Despite the model suggested indicates that the city planning is important for the pandemic damage minimization which can be reduced due to smart urban development policy.