Big Data Analytics for Understanding and Fighting COVID-19

Abstract

The coronavirus disease of 2019 (COVID-19), outbreak has hit millions of people and claiming thousands of lives worldwide. In times of unforeseen adversity like COVID-19, big data and advanced technologies are one of the few effective means to combat fast-disseminating flu for which vaccines are yet unknown. Today, many countries are employing big data, machine learning, and other digital tools to track and control this pandemic. In addition, the big data analytics propelled comparative genomic studies of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) strains have opened the door to information on mutations, virulence, evolutionary selection, and more. This has enabled the pharmaceutical and healthcare industries to improve diagnostics, aid drug discovery, and develop personalized medicine strategies. The recurrent mutations and genetic diversity identified in SARS-CoV-2 strains provide the basis to develop a cocktail of vaccines and also facilitate to develop region-specific diagnostic tools, thereby decreasing the chances of failures in testing in the fields. This chapter highlights the chief aspects of big data in current COVID-19 outbreak to figure out the best responses to fight against SARS-CoV-2 and future pandemics. Many software and applications have been developed to track and predict the infection. Similarly, mobile apps are launched for COVID-19 preliminary diagnosis and advanced diagnosis is achieved by medical image processing assisted by AI technologies. Therefore, the big data analytics has accelerated the processes of tracking, prediction, diagnosis and prognosis that have facilitated the health workers, scientists, epidemiologists, and policy makers to make more informed decisions in fighting SARS-CoV-2.