Sinha Arvind Kumar, Namdev Nishant, Shende Pradeep
Department of Mathematics, National Institute of Technology Raipur, Raipur, Chhattisgarh 492010 India.
Netw Model Anal Health Inform Bioinform. 2022;11(1):5. doi: 10.1007/s13721-021-00350-2. Epub 2021 Dec 10.
The novel coronavirus SARS-Cov-2 is a pandemic condition and poses a massive menace to health. The governments of different countries and their various prohibitory steps to restrict the virus's expanse have changed individuals' communication processes. Due to physical and financial factors, the population's density is more likely to interact and spread the virus. We establish a mathematical model to present the spread of the COVID-19 in India and worldwide. By the simulation process, we find the infected cases, infected fatality rate, and recovery rate of the COVID-19. We validate the model by the rough set method. In the method, we obtain the accuracy for the infected case is 90.19%, an infection-fatality of COVID-19 is 94%, and the recovery is 85.57%, approximately the same as the actual situation reported WHO. This paper uses the generalized simulation process to predict the outbreak of COVID-19 for different continents. It gives the way of future trends of the COVID-19 outbreak till December 2021 and casts enlightenment about learning the drifts of the outbreak worldwide.
新型冠状病毒SARS-CoV-2引发了全球大流行，对健康构成了巨大威胁。不同国家的政府及其采取的各种限制病毒传播的禁止性措施改变了人们的交流方式。由于物理和经济因素，人口密度越高，病毒越容易传播。我们建立了一个数学模型来呈现新冠病毒在印度和全球的传播情况。通过模拟过程，我们得出了新冠病毒的感染病例数、感染死亡率和康复率。我们用粗糙集方法对模型进行了验证。在该方法中，我们得出感染病例的准确率为90.19%，新冠病毒的感染死亡率为94%，康复率为85.57%，与世界卫生组织报告的实际情况大致相同。本文采用广义模拟过程来预测不同大洲的新冠疫情爆发情况。它给出了截至2021年12月新冠疫情爆发的未来趋势，并为了解全球疫情趋势提供了启示。
