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An ABMS COVID-19 Propagation Model for Hospital Emergency Departments

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Cloud Computing, Big Data and Emerging Topics (JCC-BD&ET 2024)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 2189))

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Abstract

The spread of COVID-19 between different agents in a hospital emergency department can be simulated by modeling the interactions between the agents and the environment. In this research, we use Agent Based Modeling and Simulation techniques to build a model of COVID-19 propagation based on an Emergency Department Simulator which has been tested and validated previously. The benefits of ABM include its ability to simulate complex systems, its flexibility, and its ability to model the interactions between different agents in the system. The obtained model will allow us to build a propagation simulator that enables us to build virtual environments with the aim of analyzing how the interactions between agents influence the rate of virus transmission. The model can be used to study the effectiveness of different interventions, such as social distancing, wearing masks, and vaccination, in reducing the spread of COVID-19.

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References

  1. Davoli, E., World Health Organization: A practical tool for the preparation of a hospital crisis preparedness plan, with special focus on pandemic influenza. WHO Regional Office for Europe, No. EUR/06/5064207, Copenhagen (2006)

    Google Scholar 

  2. Taboada, M., Cabrera, E., Iglesias, M.L., Epelde, F., Luque, E.: An agent-based decision support system for hospitals emergency departments. Procedia Comput. Sci. 4, 1870–1879 (2011)

    Google Scholar 

  3. Cabrera, E., Luque, E., Taboada, M., Epelde, F., Iglesias, M.L.: ABMS optimization for emergency departments. In: Proceedings of the 2012 Winter Simulation Conference (WSC), pp. 1–12. IEEE (2012)

    Google Scholar 

  4. Liu, Z., Rexachs, D., Luque, E., Epelde, F., Cabrera, E.: Simulating the micro-level behavior of emergency department for macro-level features prediction. In: 2015 Winter Simulation Conference (WSC), pp. 171–182. IEEE (2015)

    Google Scholar 

  5. Jaramillo, C., Rexachs, D., Luque, E., Epelde, F., Taboada, M.: Modeling the contact propagation of nosocomial infection in hospital emergency departments. In: The Sixth International Conference on Advances in System Simulation, pp. 84–89. SIMUL (2014)

    Google Scholar 

  6. Wang, Y., Xiong, H., Liu, S., Jung, A., Stone, T., Chukoskie, L.: Simulation agent-based model to demonstrate the transmission of COVID-19 and effectiveness of different public health strategies. Front. Comput. Sci. 82, 1–8 (2021)

    Google Scholar 

  7. Hinch, R., et al.: OpenABM-Covid19—an agent-based model for non-pharmaceutical interventions against COVID-19 including contact tracing. PLoS Comput. Biol. 17(7), e1009146 (2021)

    Google Scholar 

  8. Ponsford, L.R., Weaver, M.A., Potter, M.: Best practices identified in an academic hospital emergency department to reduce transmission of COVID-19. Adv. Emerg. Nurs. J. 43(4), 355 (2021)

    Google Scholar 

  9. Howick, S., McLafferty, D., Anderson, G.H., Pravinkumar, S.J., Van Der Meer, R., Megiddo, I.: Evaluating intervention strategies in controlling coronavirus disease 2019 (COVID-19) spread in care homes: An agent-based model. Infect. Control Hosp. Epidemiol. 42(9), 1060–1070 (2021)

    Google Scholar 

  10. Morawska, L., Milton, D.K.: It is time to address airborne transmission of COVID-19. Clin. Infect. Dis. 71(9), 2311–2313 (2020)

    Google Scholar 

  11. Morawska, L., et al.: How can airborne transmission of COVID-19 indoors be minimised? Environ. Int. 142, 105832 (2020)

    Article  Google Scholar 

  12. Rahaman, H., Barik, D.: Investigation of airborne spread of COVID-19 using a hybrid agent-based model: a case study of the UK. R. Soc. Open Sci. 10(7), 230377 (2023)

    Article  Google Scholar 

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Acknowledgments

This research has been supported by the Agencia Estatal de Investigacion (AEI), Spain and the Fondo Europeo de Desarrollo Regional (FEDER) UE, under contract PID2020-112496GB-I00 and partially funded by the Fundacion Escuelas Universitarias Gimbernat (EUG).

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Correspondence to Morteza Ansari Dogaheh .

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Ansari Dogaheh, M., Taboada, M., Epelde, F., Luque, E., Rexachs, D., Wong, A. (2025). An ABMS COVID-19 Propagation Model for Hospital Emergency Departments. In: Naiouf, M., De Giusti, L., Chichizola, F., Libutti, L. (eds) Cloud Computing, Big Data and Emerging Topics. JCC-BD&ET 2024. Communications in Computer and Information Science, vol 2189. Springer, Cham. https://doi.org/10.1007/978-3-031-70807-7_8

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  • DOI: https://doi.org/10.1007/978-3-031-70807-7_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-70806-0

  • Online ISBN: 978-3-031-70807-7

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