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Similar to the Rumors version, this script simulates the spread of a disease within a population while also accounting for the probabilities of recovery, death, and contagion. The simulation includes the option for recovery. The generated data is then converted into a CSV file, which can be used for conducting small-scale data science research.

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SIR Simulator

The user can modify those parametes safety CUSTOM VALUES ### # G = (V,E) nodes = 1200 # |V| = nodes, population # ite = 10 # iterations # percentuale = 0.7 #percentage of flips of the edges # alfa1 = 0.9 # percentage of to be contaged beta1 = 0.2# percentage of recovery S = 3 # infected-spreaders ##

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To collect more info about that work, at beginning it was related the Rumors spread only https://www.researchgate.net/publication/311066703_Remarks_on_a_rumor_propagation_model

But after the dramatically case of corona virus, I figured also the interesting in estimate the spread of viral disease in a small population. It is not an understatement to assume that the recovered may get sick again, due to the fact that the corona-virus is unfortunately changing over time. For this fact the recovered are back in the list of susceptible. That script doesnt consider that this virus is more aggressive vs chinese races instead others. More over that descend from rumors transmission in social media.

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Similar to the Rumors version, this script simulates the spread of a disease within a population while also accounting for the probabilities of recovery, death, and contagion. The simulation includes the option for recovery. The generated data is then converted into a CSV file, which can be used for conducting small-scale data science research.

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