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Fluid Model-Checking in UPPAAL for Covid-19

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12476))

Abstract

During the spring of 2020, the BEOCOVID project has been funded to investigate the use of stochastic hybrid models, statistical model checking and machine learning to analyse, predict and control the rapid spreading of Covid-19 . In this paper we focus on the SEIHR epidemiological model instance of Covid-19 pandemics and show how the risk of viral exposure, the impact of super-spreader events as well as other scenarios can be modelled, estimated and controlled using the tool .

The project was funded by Poul Due Jensens Foundation grant.

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Notes

  1. 1.

    https://www.ssi.dk.

  2. 2.

    Assuming a fixed number of compartments.

  3. 3.

    Assuming, of course, that the given model is valid with respect to reality.

  4. 4.

    https://www.sst.dk/da/corona/tal-og-overvaagning.

  5. 5.

    https://smittestop.dk/.

  6. 6.

    https://sum.dk/Aktuelt/Nyheder/Coronavirus/2020/Maj/~/media/Filer%20-%20dokumenter/01-corona/App/Politisk-aftale-om-smittessporingsappen.pdf.

  7. 7.

    https://smittestop.dk/spoergsmaal-og-svar.

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Correspondence to Kim G. Larsen or Danny B. Poulsen .

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Jensen, P.G., Jørgensen, K.Y., Larsen, K.G., Mikučionis, M., Muñiz, M., Poulsen, D.B. (2020). Fluid Model-Checking in UPPAAL for Covid-19. In: Margaria, T., Steffen, B. (eds) Leveraging Applications of Formal Methods, Verification and Validation: Verification Principles. ISoLA 2020. Lecture Notes in Computer Science(), vol 12476. Springer, Cham. https://doi.org/10.1007/978-3-030-61362-4_22

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  • DOI: https://doi.org/10.1007/978-3-030-61362-4_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-61361-7

  • Online ISBN: 978-3-030-61362-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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