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Towards a Realistic Model for Simulating Spread of Infectious COVID-19 Disease

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Published:05 October 2020Publication History

ABSTRACT

The classical compartment model namely SEIR was not designed originally for COVID-19. There are significant numbers of people infected by COVID-19 did not get sick immediately but have become carriers of COVID-19. The patients might have certain length of incubation period. In order to cover the quarantine and asymptomatic variables, the existing SEIR model is extended to a multi-compartment infectious disease model. The contribution presented in this paper is a new model called SEAIRD which caters for the new characteristics of the 2019-nCoV, therefore applicable for the inclusion of asymptomatic population in the simulation.

References

  1. Simon James Fong, Gloria Li, Nilanjan Dey, Rubén González Crespo, Enrique Herrera-Viedma, Finding an Accurate Early Forecasting Model from Small Dataset: A Case of 2019-nCoV Novel Coronavirus Outbreak. International Journal of Interactive Multimedia and Artificial Intelligence, Volume 6, Number 1, March 2020, pp. 132--140Google ScholarGoogle Scholar
  2. Santosh, K.C. AI-Driven Tools for Coronavirus Outbreak: Need of Active Learning and Cross-Population Train/Test Models on Multitudinal/Multimodal Data. J Med Syst 44, 93 (2020)Google ScholarGoogle Scholar
  3. Composite Monte Carlo Decision Making under High Uncertainty of Novel Coronavirus Epidemic Using Hybridized Deep Learning and Fuzzy Rule Induction, Applied Soft Computing Journal, Article number 106282, DOI 10.1016/j.asoc.2020.106282, May 2020, In PressGoogle ScholarGoogle Scholar
  4. Carcione José M., Santos Juan E., Bagaini Claudio, Ba Jing, A Simulation of a COVID-19 Epidemic Based on a Deterministic SEIR Model, Frontiers in Public Health, Volume 8, 2020, pp.230, DOI=10.3389/fpubh.2020.00230Google ScholarGoogle ScholarCross RefCross Ref
  5. Godio A, Pace F, Vergnano A. SEIR Modeling of the Italian Epidemic of SARS-CoV-2 Using Computational Swarm Intelligence. Int J Environ Res Public Health. 2020;17(10):3535. Published 2020 May 18. doi: 10.3390/ijerph17103535Google ScholarGoogle Scholar
  6. Coronavirus disease (COVID-19) pandemic, WHO, https://www.who.int/emergencies/diseases/novel-coronavirus-2019 [Last accessed on 31 July 2020]Google ScholarGoogle Scholar
  7. Rustam, A. H. (2006). Epidemic network and centrality (Master's thesis, Høgskolen i Oslo. Avdeling for ingeniørutdanning).Google ScholarGoogle Scholar
  8. Pandey G, Chaudhary P, Gupta R, et al. SEIR and Regression Model based COVID-19 outbreak predictions in India[J]. arXiv preprint arXiv:2004.00958, 2020.Google ScholarGoogle Scholar
  9. Yang, Z., Zeng, Z., Wang, K., Wong, S. S., Liang, W., Zanin, Liang, J. (2020). Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions. Journal of Thoracic Disease, 12(3), 165.Google ScholarGoogle ScholarCross RefCross Ref
  10. Randolph, H. E., & Barreiro, L. B. (2020). Herd Immunity: Understanding COVID-19. Immunity, 52(5), 737--741.Google ScholarGoogle ScholarCross RefCross Ref

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  1. Towards a Realistic Model for Simulating Spread of Infectious COVID-19 Disease

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    • Published in

      cover image ACM Other conferences
      BDIOT '20: Proceedings of the 2020 4th International Conference on Big Data and Internet of Things
      August 2020
      108 pages
      ISBN:9781450375504
      DOI:10.1145/3421537

      Copyright © 2020 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 5 October 2020

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      Overall Acceptance Rate75of136submissions,55%

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