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全球健康灾难，对人们感知世界和日常生活的方式产生了深远影响。就其对人类死亡率和许多其他社会阵线或驱动力的影响而言，这似乎是全世界目前面临的最大威胁，其估计值尚不清楚。因此，本研究重点关注因 COVID-19 大流行而受到严重影响的最关键部门，特别是印度。根据与国家整体经济的直接联系考虑，这些部门包括经济和金融、教育、医疗保健、工业、电力和能源、石油市场、就业和环境。根据有关大流行和上述部门的现有数据以及有关COVID-19传播的预测数据，使用指数平滑、线性回归、霍尔特和温特斯四种包容性数学模型来分析疫情的严重性此次 COVID-19 爆发造成的影响也以图形方式可视化。所有模型均使用 COVID-19 感染率、每日病例数和死亡人数、印度 GDP 和失业率等数据进行测试。比较所得结果，提出最佳预测模型。本研究旨在评估这一流行病对国家驱动部门的影响，并提出一些减轻这些对国家经济影响的策略建议。