Τίτλος:
COVID-19 pandemic decision support system for a population defense
strategy and vaccination effectiveness
Γλώσσες Τεκμηρίου:
Αγγλικά
Περίληψη:
The year 2020 ended with a significant COVID-19 pandemic, which
traumatized almost many countries where the lockdowns were restored, and
numerous emotional social protests erupted. According to the World
Health Organization, the global epidemiological situation in the first
months of 2021 deteriorated. In this paper, the decision-making
supporting system (DMSS) is proposed to be an epidemiological prediction
tool. COVID-19 trends in several countries and regions, take into
account the big data clouds for important geophysical and
socio-ecological characteristics and the expected potentials of the
medical service, including vaccination and restrictions on population
migration both within the country and international traffic. These
parameters for numerical simulations are estimated from officially
delivered data that allows the verification of theoretical results. The
numerical simulations of the transition and the results of COVID-19 are
mainly based on the deterministic approach and the algorithm for
processing statistical data based on the instability indicator. DMSS has
been shown to help predict the effects of COVID-19 depending on the
protection strategies against COVID-19 including vaccination. Numerical
simulations have shown that DMSS provides results using accompanying
information in the appropriate scenario.
Συγγραφείς:
Varotsos, Costas A.
Krapivin, Vladimir F.
Xue, Yong and
Soldatov, Vladimir
Voronova, Tatiana
Περιοδικό:
SAFETY SCIENCE
Λέξεις-κλειδιά:
COVID-19; Decision making; Big data; Prognosis; Trend; Model;
Vaccination; Simulation
DOI:
10.1016/j.ssci.2021.105370
