Abstract
Studying potentially harmful infectious agents for some population and trying to explain and predicts how the disease evolves in the time are difficult because many factors interactions. An solution is to analyse real systems by mean of simulations models. In these cases, Cellular Automata have been used with success, they can recreate a virtual world take account problem main features and their correlations. We developed an efficient and portable cellular automata model in Graphic Processing Units to simulate viral diseases propagation. The achieved efficiency allows us estimate in a short time the viral disease behaviour when it is known or not, as well as its associated uncertainty. Besides, it is suitable to test effects of different measures that tending towards stop the spread. We describe the solution and evaluate it for two viral diseases: Seasonal Influenza and COVID-19.
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Lucero, M., Miranda, N., Piccoli, F. (2020). Viral Diseases Propagation Analysis in Short Time. In: Rucci, E., Naiouf, M., Chichizola, F., De Giusti, L. (eds) Cloud Computing, Big Data & Emerging Topics. JCC-BD&ET 2020. Communications in Computer and Information Science, vol 1291. Springer, Cham. https://doi.org/10.1007/978-3-030-61218-4_4
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DOI: https://doi.org/10.1007/978-3-030-61218-4_4
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