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

Huseyin Atakan Varol

doi:10.1109/EMBC.2016.7591271

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

Huseyin Atakan Varol

Department of Robotics and Mechatronics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

This paper presents an open-source stochastic epidemic simulator. Discrete Time Markov Chain based simulator is implemented in Matlab. The simulator capable of simulating SEQIJR (susceptible, exposed, quarantined, infected, isolated and recovered) model can be reduced to simpler models by setting some of the parameters (transition probabilities) to zero. Similarly, it can be extended to more complicated models by editing the source code. It is designed to be used for testing different control algorithms to contain epidemics. The simulator is also designed to be compatible with a network based epidemic simulator and can be used in the network based scheme for the simulation of a node. Simulations show the capability of reproducing different epidemic model behaviors successfully in a computationally efficient manner.

Original language	English
Title of host publication	2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2636-2639
Number of pages	4
Volume	2016-October
ISBN (Electronic)	9781457702204
DOIs	https://doi.org/10.1109/EMBC.2016.7591271
Publication status	Published - Oct 13 2016
Event	38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 - Orlando, United States Duration: Aug 16 2016 → Aug 20 2016

Conference

Conference	38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
Country	United States
City	Orlando
Period	8/16/16 → 8/20/16

ASJC Scopus subject areas

Signal Processing
Biomedical Engineering
Computer Vision and Pattern Recognition
Health Informatics

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MOSES : A Matlab-based open-source stochastic epidemic simulator. / Varol, Huseyin Atakan.

2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016. Vol. 2016-October Institute of Electrical and Electronics Engineers Inc., 2016. p. 2636-2639 7591271.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Varol, HA 2016, MOSES: A Matlab-based open-source stochastic epidemic simulator. in 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016. vol. 2016-October, 7591271, Institute of Electrical and Electronics Engineers Inc., pp. 2636-2639, 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016, Orlando, United States, 8/16/16. https://doi.org/10.1109/EMBC.2016.7591271

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abstract = "This paper presents an open-source stochastic epidemic simulator. Discrete Time Markov Chain based simulator is implemented in Matlab. The simulator capable of simulating SEQIJR (susceptible, exposed, quarantined, infected, isolated and recovered) model can be reduced to simpler models by setting some of the parameters (transition probabilities) to zero. Similarly, it can be extended to more complicated models by editing the source code. It is designed to be used for testing different control algorithms to contain epidemics. The simulator is also designed to be compatible with a network based epidemic simulator and can be used in the network based scheme for the simulation of a node. Simulations show the capability of reproducing different epidemic model behaviors successfully in a computationally efficient manner.",

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

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