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Pandemic Simulation and Forecasting of exit strategies:Convergence of Machine Learning and EpidemiologicalModels
Ghamizi, Salah; Rwemalika, Renaud; Cordy, Maxime et al.
2020
 

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Keywords :
Covid19; Machine Learning; SEIR
Abstract :
[en] The COVID-19 pandemic has created a public health emergency unprecedented in this century. The lack ofaccurate knowledge regarding the outcomes of the virus has made it challenging for policymakers to decideon appropriate countermeasures to mitigate its impact on society, in particular the public health and the veryhealthcare system.While the mitigation strategies (including the lockdown) are getting lifted, understanding the current im-pacts of the outbreak remains challenging. This impedes any analysis and scheduling of measures requiredfor the different countries to recover from the pandemic without risking a new outbreak.Therefore, we propose a novel approach to build realistic data-driven pandemic simulation and forecastingmodels to support policymakers. Our models allow the investigation of mitigation/recovery measures andtheir impact. Thereby, they enable appropriate planning of those measures, with the aim to optimize theirsocietal benefits.Our approach relies on a combination of machine learning and classical epidemiological models, circum-venting the respective limitations of these techniques to allow a policy-making based on established knowl-edge, yet driven by factual data, and tailored to each country’s specific context.
Disciplines :
Computer science
Author, co-author :
Ghamizi, Salah ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Computer Science and Communications Research Unit (CSC)
Rwemalika, Renaud ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Cordy, Maxime  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Le Traon, Yves ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Computer Science and Communications Research Unit (CSC)
Papadakis, Mike ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Computer Science and Communications Research Unit (CSC)
Language :
English
Title :
Pandemic Simulation and Forecasting of exit strategies:Convergence of Machine Learning and EpidemiologicalModels
Publication date :
2020
Publisher :
University of Luxembourg
Available on ORBilu :
since 11 May 2020

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