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 anlyse, 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 Uppaal SMC.
Original languageEnglish
Title of host publicationLeveraging Applications of Formal Methods, Verification and Validation : Verification Principles - 9th International Symposium on Leveraging Applications of Formal Methods, ISoLA 2020, Proceedings
EditorsTiziana Margaria, Bernhard Steffen
Number of pages19
PublisherSpringer
Publication date2020
Pages385-403
ISBN (Print)978-3-030-61361-7
ISBN (Electronic)978-3-030-61362-4
DOIs
Publication statusPublished - 2020
Event9th International Symposium on Leveraging Applications of Formal Methods, Verification and Validation, ISoLA 2020 - Rhodes, Greece
Duration: 20 Oct 202030 Oct 2020

Conference

Conference9th International Symposium on Leveraging Applications of Formal Methods, Verification and Validation, ISoLA 2020
CountryGreece
CityRhodes
Period20/10/202030/10/2020
SeriesLecture Notes in Computer Science
Volume12476
ISSN0302-9743

Bibliographical note

Funding Information:
The project was funded by Poul Due Jensens Foundation grant.

Funding Information:
– In early April researchers at Danmarks Tekniske Universitet (DTU) and Aal-borg Universitet (AAU) started a research project funded by Novo Nordisk Fonden (NNF) to develop and improve modelling tools of Covid-19 to assist decision makers to evaluate the effectiveness and impact of preventive mea-sures. The project has been carried out in collaboration with SSI.

Publisher Copyright:
© 2020, Springer Nature Switzerland AG.

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