Author: Haluk Akay; George Barbastathis
Title: MARKOVIAN RANDOM WALK MODELING AND VISUALIZATION OF THE EPIDEMIC SPREAD OF COVID-19 Document date: 2020_4_17
ID: fetbio7q_4
Snippet: In order to simulate epidemic spreading, the possible states an agent can assume are based on the Susceptible -Infected -Removed (SIR) model, a set of nonlinear ordinary differential equations which can be used to track the magnitude of each population, assuming a closed system where S(t) + I(t) + R(t) = N is constant. In this system, the coefficient β represents the rate of transmission of the disease from the infected to the susceptible popula.....
Document: In order to simulate epidemic spreading, the possible states an agent can assume are based on the Susceptible -Infected -Removed (SIR) model, a set of nonlinear ordinary differential equations which can be used to track the magnitude of each population, assuming a closed system where S(t) + I(t) + R(t) = N is constant. In this system, the coefficient β represents the rate of transmission of the disease from the infected to the susceptible population, and γ represents the rate of removal, corresponding to recovery or death. It is justifiable to lump the latter two populations into one for the purpose of modeling, as long as both cease to be capable of further infecting others. The coupled ordinary differential equations describing the SIR model are
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