ABSTRACT
“Novel Coronavirus”, commonly known as COVID-19 has spread nearly to the entire world. The number of impacted cases and deaths has increased significantly in each country, posing a challenge for the world’s health organizations. The goal of this paper was to better comprehend and analyze the growth of the disease in India, including confirmed, recovered, fatalities, and active cases of COVID-19. Data analysis affects an organization’s decision-making process with interactive visual representation. The proposed model was an ensemble model that was built using linear regression, polynomial regression, and support vector machine (SVM) regression models. The model predicted the number of confirmed cases from 30th May 2021 to 15th June 2021 based on the data available from 22 January 2020 to 29 May 2021 and improved accuracy was obtained when compared with the actual data. Forecasting the confirmed cases might assist health organizations in planning medical facilities. Following that, an appropriate machine leraning (ML) model must be found that can predict the number of new cases in the future. © 2022, Institute of Advanced Engineering and Science. All rights reserved.
ABSTRACT
The corona virus disease is recognized as a global threat to the health industry and is a new challenge to the research area. To deal with this corona virus disease (COVID-19), which is currently sparked, all over the globe, machine learning (ML) plays a major role in variety of ways. This paper presents the analysis of the deadly COVID-19 outbreak to fight against this pandemic. This study is based on the dataset of confirmed cases, deaths, and recoveries worldwide as provided by the Johns Hopkins University. At first, we analyzed the pattern and characteristics of the growth of the pandemic by publicly available data. Secondly, we presented a comparative study and, finally, developed a future forecast model by taking three machine learning algorithms are support vector machine, linear regression, and Bayesian ridge regression. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
The novel coronavirus disease is a rapidly spreading infection caused by recently discovered different variants of SARS CoV-2 viruses, causing mild to severe respiratory symptoms in the majority of people. The Coronavirus disease 2019 pandemic has spread almost all the nooks and corners of the world. There are significant possible approaches pharmaceutically to fight against COVID-19. Original full-text research articles were searched online in PubMed, ScienceDirect, ResearchGate, Google Scholar, Core and Wiley Online Library. Scientists throughout the world are working on different platforms and targeting certain proteins moieties against SARS CoV-2 for the development of methods of safety, efficacy and potential vaccine candidates. Many candidates showed efficacy in In-vitro studies but relatively few clinical studies proceeded through different vaccine development platforms, such as entire virus vaccines, plant-based and nucleic acid vaccines, recombinant protein subunit vaccines. This review study provides a short description of SARS-CoV-2 characteristics and deals with recent developments in the design of attempts to produce vaccines to combat COVID-19.