Kumar Saket, Viral Rajkumar, Deep Vikas, Sharma Purushottam, Kumar Manoj, Mahmud Mufti, Stephan Thompson
Amity School of Engineering and Technology, Amity University Uttar Pradesh, Noida, India.
School of Computer Science, University of Petroleum, Energy Studies (UPES), Bidoli, Dehradun, India.
Pers Ubiquitous Comput. 2023;27(3):807-830. doi: 10.1007/s00779-021-01530-7. Epub 2021 Mar 26.
The pandemic caused by the coronavirus disease 2019 (COVID-19) has produced a global health calamity that has a profound impact on the way of perceiving the world and everyday lives. This has appeared as the greatest threat of the time for the entire world in terms of its impact on human mortality rate and many other societal fronts or driving forces whose estimations are yet to be known. Therefore, this study focuses on the most crucial sectors that are severely impacted due to the COVID-19 pandemic, in particular reference to India. Considered based on their direct link to a country's overall economy, these sectors include economic and financial, educational, healthcare, industrial, power and energy, oil market, employment, and environment. Based on available data about the pandemic and the above-mentioned sectors, as well as forecasted data about COVID-19 spreading, four inclusive mathematical models, namely-exponential smoothing, linear regression, Holt, and Winters, are used to analyse the gravity of the impacts due to this COVID-19 outbreak which is also graphically visualized. All the models are tested using data such as COVID-19 infection rate, number of daily cases and deaths, GDP of India, and unemployment. Comparing the obtained results, the best prediction model is presented. This study aims to evaluate the impact of this pandemic on country-driven sectors and recommends some strategies to lessen these impacts on a country's economy.
2019年冠状病毒病（COVID-19）引发的大流行造成了一场全球健康灾难，对人们认识世界的方式和日常生活产生了深远影响。就其对人类死亡率以及许多其他社会层面或驱动因素的影响而言，这已成为当今世界面临的最大威胁，而这些影响目前仍难以估量。因此，本研究聚焦于受COVID-19大流行严重影响的最关键领域，特别是以印度为例。基于这些领域与一个国家整体经济的直接关联，这些领域包括经济与金融、教育、医疗保健、工业、电力与能源、石油市场、就业和环境。基于有关该大流行及上述领域的现有数据，以及关于COVID-19传播的预测数据，使用了四种包容性数学模型，即指数平滑法、线性回归、霍尔特法和温特斯法，来分析此次COVID-19疫情造成的影响的严重程度，并以图形方式进行了可视化展示。所有模型均使用诸如COVID-19感染率、每日病例数和死亡数、印度国内生产总值以及失业率等数据进行测试。通过比较所得结果，给出了最佳预测模型。本研究旨在评估这场大流行对国家驱动领域的影响，并提出一些策略以减轻其对一个国家经济的影响。
