@Article{cmes.2020.013280,
AUTHOR = {Panagiotis G. Asteris, Maria G. Douvika, Chrysoula A. Karamani, Athanasia D. Skentou, Katerina Chlichlia, Liborio Cavaleri, Tryfon Daras, Danial J. Armaghani, Theoklis E. Zaoutis},
TITLE = {A Novel Heuristic Algorithm for the Modeling and Risk Assessment of the COVID-19 Pandemic Phenomenon},
JOURNAL = {Computer Modeling in Engineering \& Sciences},
VOLUME = {125},
YEAR = {2020},
NUMBER = {2},
PAGES = {815--828},
URL = {http://www.techscience.com/CMES/v125n2/40324},
ISSN = {1526-1506},
ABSTRACT = {The modeling 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 decision-making. To 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 UK.
The 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 conditions. Based on derived predicted
epidemic curves, a new 3D-epidemic surface is proposed to assess the epidemic
phenomenon at any time of its evolution. This research highlights the potential of the proposed model as a tool which can assist in the risk assessment of
the COVID-19. Mapping its development through 3D-epidemic surface can
assist in revealing its dynamic nature as well as differences and similarities
among different districts.},
DOI = {10.32604/cmes.2020.013280}
}