Knowledge Bank

A pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), named as coronavirus disease 2019 (COVID-19) by the World Health Organization (WHO), emerged in Wuhan, China and it is currently underway resulting in worldwide severe morbidity and mortality.

Since the beginning of the pandemic, visualizations have assisted us to understand the unpredictable nature of this virus by providing detailed information based on data and variables on the ground. During the pandemic, visualizations can help us to analyze features such as the infection rate within different groups of people, thus we could interpret the reasons behind the high infection rate.

The objective of our study is to overview some of the state-of-art visualization techniques to illustrate the dynamics of the COVID-19 spread for Ohio. Although there are some potential variables, such as age, that are known to be associated with COVID-19, it remains unclear if the affection and death rates for COVID-19 differ significantly for some other factors. Therefore, we are going to analyze COVID-19 data from Ohio and the USA to discover such factors statistically.