An Investigation on how Diagnostic Analytics may be utilized to Determine Patterns of Illness Spread during the COVID-19 Pandemic

Abstract

During the COVID-19 pandemic, it was challenging to stop the infection’s spread. The virus spread swiftly, affecting more than 70 million people globally in almost every area. The World Health Organization’s failure to set up a system to track different COVID-19 variants and its efficacy at first resulted in seven million deaths globally. We could not immediately give a vaccine for the broader public, even with our advanced technology. Even in the midst of chaos data scientists played a critical role in stopping the pandemic’s spread. Future trends were successfully predicted by predictive algorithms developed by data scientists. This paper looks at the use of diagnostic analytics during COVID-19 and how it helped to halt the infection’s spread.