Modeling epidemic spread with spike-based models

Kathleen Hamilton; Prasanna Date; Bill Kay; Catherine Schuman D.

doi:10.1145/3407197.3407219

Modeling epidemic spread with spike-based models

Kathleen Hamilton, Prasanna Date, Bill Kay, Catherine Schuman D.

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

15 Scopus citations

Abstract

The Susceptible-Infected-Recovered/Removed model is a standard model for epidemiological spread of disease through vulnerable populations. In this paper we show how SIR network dynamics can be implemented using spiking neurons.

Original language	English
Title of host publication	ICONS 2020 - Proceedings of International Conference on Neuromorphic Systems 2020
Publisher	Association for Computing Machinery
ISBN (Electronic)	9781450388511
DOIs	https://doi.org/10.1145/3407197.3407219
State	Published - Jul 28 2020
Event	2020 International Conference on Neuromorphic Systems, ICONS 2020 - Virtual, Online, United States Duration: Jul 28 2020 → Jul 30 2020

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	2020 International Conference on Neuromorphic Systems, ICONS 2020
Country/Territory	United States
City	Virtual, Online
Period	07/28/20 → 07/30/20

Funding

Notice: This manuscript has been authored in part by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).

Keywords

epidemiological modeling
neuromorphic algorithms
spiking neural networks

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10.1145/3407197.3407219

Cite this

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title = "Modeling epidemic spread with spike-based models",

abstract = "The Susceptible-Infected-Recovered/Removed model is a standard model for epidemiological spread of disease through vulnerable populations. In this paper we show how SIR network dynamics can be implemented using spiking neurons.",

keywords = "epidemiological modeling, neuromorphic algorithms, spiking neural networks",

author = "Kathleen Hamilton and Prasanna Date and Bill Kay and {Schuman D.}, Catherine",

note = "Publisher Copyright: {\textcopyright} 2020 ACM.; 2020 International Conference on Neuromorphic Systems, ICONS 2020 ; Conference date: 28-07-2020 Through 30-07-2020",

year = "2020",

month = jul,

day = "28",

doi = "10.1145/3407197.3407219",

language = "English",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery",

booktitle = "ICONS 2020 - Proceedings of International Conference on Neuromorphic Systems 2020",

}

Hamilton, K , Date, P, Kay, B & Schuman D., C 2020, Modeling epidemic spread with spike-based models. in ICONS 2020 - Proceedings of International Conference on Neuromorphic Systems 2020., 3407219, ACM International Conference Proceeding Series, Association for Computing Machinery, 2020 International Conference on Neuromorphic Systems, ICONS 2020, Virtual, Online, United States, 07/28/20. https://doi.org/10.1145/3407197.3407219

Modeling epidemic spread with spike-based models. / Hamilton, Kathleen ; Date, Prasanna; Kay, Bill et al.
ICONS 2020 - Proceedings of International Conference on Neuromorphic Systems 2020. Association for Computing Machinery, 2020. 3407219 (ACM International Conference Proceeding Series).

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

TY - GEN

T1 - Modeling epidemic spread with spike-based models

AU - Hamilton, Kathleen

AU - Date, Prasanna

AU - Kay, Bill

AU - Schuman D., Catherine

PY - 2020/7/28

Y1 - 2020/7/28

N2 - The Susceptible-Infected-Recovered/Removed model is a standard model for epidemiological spread of disease through vulnerable populations. In this paper we show how SIR network dynamics can be implemented using spiking neurons.

AB - The Susceptible-Infected-Recovered/Removed model is a standard model for epidemiological spread of disease through vulnerable populations. In this paper we show how SIR network dynamics can be implemented using spiking neurons.

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KW - neuromorphic algorithms

KW - spiking neural networks

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U2 - 10.1145/3407197.3407219

DO - 10.1145/3407197.3407219

M3 - Conference contribution

AN - SCOPUS:85091518074

T3 - ACM International Conference Proceeding Series

BT - ICONS 2020 - Proceedings of International Conference on Neuromorphic Systems 2020

PB - Association for Computing Machinery

T2 - 2020 International Conference on Neuromorphic Systems, ICONS 2020

Y2 - 28 July 2020 through 30 July 2020

ER -

Modeling epidemic spread with spike-based models

Abstract

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Keywords

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