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MOSES: A Matlab-based open-source stochastic epidemic simulator.

Huseyin Atakan Varol

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    Summary
    This summary is machine-generated.

    This study introduces an open-source epidemic simulator using Discrete Time Markov Chains. The tool efficiently models various infectious disease dynamics, aiding in testing control strategies.

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    Area of Science:

    • Computational epidemiology
    • Mathematical modeling of infectious diseases

    Background:

    • Epidemic modeling is crucial for understanding disease spread.
    • Existing simulators may lack flexibility or efficiency for complex scenarios.

    Purpose of the Study:

    • To present an open-source, flexible, and computationally efficient stochastic epidemic simulator.
    • To enable the testing of various epidemic control algorithms.

    Main Methods:

    • Implementation of a Discrete Time Markov Chain (DTMC) based simulator in Matlab.
    • Development of a simulator capable of simulating the SEQIJR (Susceptible, Exposed, Quarantined, Infected, Isolated, Recovered) model.
    • Design for compatibility with network-based epidemic simulators.

    Main Results:

    • The simulator successfully reproduces diverse epidemic model behaviors.
    • Demonstrated computational efficiency in simulations.
    • Flexibility to simplify or extend epidemic models by adjusting parameters or code.

    Conclusions:

    • The open-source simulator provides a valuable tool for epidemiological research.
    • It facilitates the evaluation of control strategies and integration into network models.
    • The simulator offers an efficient and adaptable platform for studying epidemic dynamics.