Analytical Insights into COVID19 Pandemic Predictions: A Machine Learning Perspective

Abstract

The world is experiencing implications of contagious, transferable and pathogenic infections caused by Coronavirus disease 19 (COVID-19) aka Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). It is spreading out everywhere throughout the globe. In genomics reviews, SARS-CoV-2, associated with a genuine strain was found. Although intermediate origin sources and transcription to humans are not known, transfer from humans to humans have widely entrenched. Within reach are no clinically endorsed antiviral medications. Antibodies are open for COVID-19. Be that as it may, wide-region antiviral medications have evaluated against COVID-19 for the most part in the clinical examination, bringing about clinical recovery. An appearance and pathogenic of COVID-19 diseases are generally examined, human coronavirus Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV), and the Middle East Respiratory Syndrome Coronavirus (MERS-CoV). This study presents insights into effective approaches to vaccine development including treatments that deal with this virus epidemic through a machine learning perspective. The outcome of machine learning algorithms executed on datasets available on Kaggle website and mohfw.gov portray the spread of coronavirus in India.

Note:

Funding: None to declare

Declaration of Interest: None to declare

Keywords: Coronaviruses, COVID-19, Contagion, Epidemic, Origin, Outbreak, Pandemic, Severe Acute Respiratory Syndrome Coronavirus 2(SARS-CoV), Spread