The cells usually represent real spaces in various sizes ranging from atomic structure of matter to urban texture components or even larger. The transition function calculates the state of each cell based on the state of its neighbors where, these simple local interactions and computations between cells, form a complex global behavior. Ī CA consists of a collection of cells arranged in a multi-dimensional space and a dynamical rule (transition function) which updates their configuration synchronously. The successful applications of CA shows its high potential for simulating and analyzing how changes spread locally over time. Models can be developed, tested and adapted for different applications, especially when data on events that occurred over a wide range of time and space are available.Ĭellular Automata (CA) are a family of spatiotemporal mathematical and computational tools employed in a variety of modeling and simulation contexts such as epidemic, growth, flow, propagation, evacuation and transport dynamics, ,, ,, ,.
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Modeling devices, as a result of knowledge representation, offer several advantages by their representational, computational and analytical potentials. The large amounts of data and information generated due to the spread and longevity of viruses and infectious diseases provide an opportunity for scientists to extract the knowledge needed for making decisions in similar situations, ,, ,, ,, as well as control measure issues,. Our experiments using the proposed model verify that the proposed model is capable of formulating different ways of virus transmission, including long-distance transmission, and supports high-precision simulation of the pandemic. Finally, we simulate the coronavirus outbreak in the five study areas including three states and two countries. Furthermore, we characterize the capabilities of the proposed modeling tool in simulation of the virus spread, and estimating the risk control during the movement restrictions and related health protocols. Then, we generalize the concept of CA by providing a symbiosis between the neighborhood relationship of cells and the transmission channels represented by a dynamic weighted multigraph.
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In this paper, we first present some patterns that show the local interaction between CA cells is not sufficient for virus spread modeling, especially at large spatial scales.
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A CA consists of a topological combination of units called cells as well as a transition function that propagates the configuration of cells locally and step by step. Cellular Automata (CA) are a family of spatiotemporal computational models frequently employed in analysis of biomedical systems. Simulation and analysis of such a situation requires the development of models that support long distance transmission of viruses. The pattern of coronavirus spread at different geographical scales verifies that travel or shipment by air, sea or road are potential to transmit viruses from one location to somewhere far away in a very short time.