COVID-19 pandemic decision support system for a population defense strategy and vaccination effectiveness

Costas A Varotsos; Vladimir F Krapivin; Yong Xue; Vladimir Soldatov; Tatiana Voronova

doi:10.1016/j.ssci.2021.105370

COVID-19 pandemic decision support system for a population defense strategy and vaccination effectiveness

Saf Sci. 2021 Oct:142:105370. doi: 10.1016/j.ssci.2021.105370. Epub 2021 Jun 5.

Authors

Costas A Varotsos¹, Vladimir F Krapivin², Yong Xue^{3

4}, Vladimir Soldatov², Tatiana Voronova¹

Affiliations

¹ Department of Environmental Physics and Meteorology, National and Kapodistrian University of Athens, Panepistimioupolis, Bldg PHYS-V, GR-157 84 Athens, Greece.
² Kotelnikov's Institute of Radioengineering and Electronics, Fryazino Branch, Russian Academy of Sciences, Vvedensky 1, Fryazino, Moscow Region 141190, Russian Federation.
³ School of Environment Science and Spatial Informatics, University of Mining and Technology, Xuzhou, Jiangsu 221116, PR China.
⁴ Department of Electronics, Computing and Mathematics, College of Science and Engineering, University of Derby, Kedleston Road, Derby DE22 1GB, UK.

Abstract

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.

Keywords: Big data; COVID-19; Decision making; Model; Prognosis; Simulation; Trend; Vaccination.