A recent study based on prediction approach over Coronavirus disease-2019 cases in India using regression modeling of artificial intelligence

The advent of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; formerly named coronavirus virus or 2019-nCoV) disease (COVID-19) in China at the end of 2019 has caused a large global outbreak and is a major public health issue. As of February 20, 2021, data from the World Health Organization (WHO) have shown that more than 10,977,387 confirmed cases and 156,240 deaths have been identified in India. On January 30, 2020, the WHO declared COVID-19 as the sixth public health emergency of international concern. In India, there are 81,990 numbers of confirmed cases that have been identified as on May 15, 2020. In this regard, the Indian Council of Medical Research (ICMR) takes an initiative for providing intensive care to COVID-19 patients and to fulfill their needs. The percentage of patients infected with COVID-19 reported daily in India between April 1 and May 14, 2020 has been consistently between 20.64% and 30.81% of patients who are actively infected. Currently, India is sustaining in the pandemic situation. The number of patients infected since May 14 in India closely follows an exponential trend. If this trend continues for 1 more week, there will be 1-13 lakhs infected patients till mid-March and India will enter into a serious situation. Intensive care units are then at maximum capacity; up to 710,761 hospital isolation beds will be needed by mid-March, 2020. In this chapter, we discuss the preparations related to COVID-19 and its impact on the second highest populated country in the world. A prediction model is proposed to forecast the COVID-19 confirmed cases with high accuracy. The analysis might help political leaders and health authorities to allocate enough resources, including personnel, beds, and intensive care facilities, to manage the situation in the next few days and weeks.