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A Novel Heuristic Algorithm for theModeling and Risk Assessment of the COVID-19 Pandemic Phenomenon

Computer Modeling in Engineering & Sciences 2020年第11期125卷 815-828页

作者： Panagiotis G.Asteris Maria G.Douvika Chrysoula A.Karamani Athanasia D.Skentou Katerina Chlichlia liborio cavaleri Tryfon Daras Danial J.Armaghani Theoklis E.Zaoutis Computational Mechanics Laboratory School of Pedagogical and Technological EducationAthens15122Greece Laboratory of Molecular Immunology Department of Molecular Biology and GeneticsDemocritus University of ThraceAlexandroupolisGreece Department of Civil EnvironmentalAerospace and Materials EngineeringUniversity of PalermoPalermoItaly School of Environmental Engineering Technical University of CreteChaniaGreece Department of Civil Engineering Faculty of EngineeringUniversity of MalayaKuala LumpurMalaysia Division of Infectious Diseases The Children’s Hospital of PhiladelphiaPerelman School of MedicineUniversity of PennsylvaniaPHLUSA

Themodeling and risk assessment of a pandemic phenomenon such as COVID-19 is an important and complicated issue in epidemiology,and such an attempt is of great interest for public health *** this end,in the present study,based on a recent heuristic algorithm proposed by the authors,the time evolution of COVID-19 is investigated for six different countries/states,namely New York,California,USA,Iran,Sweden and *** number of COVID-19-related deaths is used to develop the proposed heuristic model as it is believed that the predicted number of daily deaths in each country/state includes information about the quality of the health system in each area,the age distribution of population,geographical and environmental factors as well as other *** on derived predicted epidemic curves,a new 3D-epidemic surface is proposed to assess the epidemic phenomenon at any time of its *** research highlights the potential of the proposed model as a tool which can assist in the risk assessment of the *** its development through 3D-epidemic surface can assist in revealing its dynamic nature as well as differences and similarities among different districts.

关键词： Algorithm COVID-19 Gaussian-function heuristic model pandemic trend prediction SARS-CoV-2

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