License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.GIScience.2023.48
URN: urn:nbn:de:0030-drops-189435
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2023/18943/
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Liu, Huixin ; Wise, Sarah

Agent-Based Modelling and Disease: Demonstrating the Role of Human Remains in Epidemic Outbreaks (Short Paper)

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LIPIcs-GIScience-2023-48.pdf (1 MB)

Abstract

Hemorrhagic fever viruses present a high risk to humans, given their associated high fatality rates, extensive care requirements, and few relevant vaccines. One of the most famous such viruses is the Ebola virus, which first came to international attention during an outbreak in 1976. Another is Marburg virus, cases of which are being reported in Equatorial Guinea at the time of writing. Researchers and governments all over the world share a goal in seeking effective ways to reduce or prevent the influence or spreading of such diseases. This study introduces a prototype agent-based model to explore the epidemic infectious progression of a simulated fever virus. More specifically, this work seeks to recreate the role of human remains in the progression of such an epidemic, and to help gauge the influence of different environmental conditions on this dynamic.

BibTeX - Entry

@InProceedings{liu_et_al:LIPIcs.GIScience.2023.48,
  author =	{Liu, Huixin and Wise, Sarah},
  title =	{{Agent-Based Modelling and Disease: Demonstrating the Role of Human Remains in Epidemic Outbreaks}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{48:1--48:7},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-288-4},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{277},
  editor =	{Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2023/18943},
  URN =		{urn:nbn:de:0030-drops-189435},
  doi =		{10.4230/LIPIcs.GIScience.2023.48},
  annote =	{Keywords: Disease modelling, agent-based model, hemorrhagic fever virus, epidemiology, safe burial practices}
}

Keywords: Disease modelling, agent-based model, hemorrhagic fever virus, epidemiology, safe burial practices
Collection: 12th International Conference on Geographic Information Science (GIScience 2023)
Issue Date: 2023
Date of publication: 07.09.2023
Supplementary Material: Software: https://github.com/Huixin-coder/Huixin--Giscience-2023.git

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