COVID-19 has been spreading rapidly around the world since December 2019. The main goal of this study is to develop a more effective method for diagnosing and predicting the COVID-19 spread and to evaluate the effectiveness of control measures to reduce and stop the virus spread. To this end, the COVID-19 Decision-Making System (CDMS) was developed to study disease transmission. CDMS divides the population into groups as susceptible, infected, cured and dead. The trends of the people's number in these groups have deterministic and stochastic components. The deterministic components are described by a differential equations system with parameters determined by the data reported. The stochastic components are represented as an indicator of instability that characterizes the tendency of COVID-19 spread. The simulation experiments have shown a good agreement between the CDMS estimates and the data reported in Russia and Greece. The analysis performed showed that the newly-introduced instability indicator may be the precursor to the pandemic dynamics. In this context, our results showed three potential candidates for a second wave of COVID-19 disease: USA, Russia and Brazil. Although the proportion of infected individuals in countries with high temperatures is lower than in European countries and Russia, temperature and humidity are slowly affecting the effects of the pandemic. Finally, the results presented may contribute to the urgent need to reduce the risks associated with the second wave of the COVID-19, to improve public health intervention and safety measures to be taken by various countries.
Keywords: COVID-19; Indicator; Instability; Model; Pandemic; Population safety.
© 2020 Elsevier Ltd. All rights reserved.