An Inclusive Covid-19 Dashboard with Automatic Phase Detection

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At present, the spread of COVID-19 is shown to have an exponential trend in most countries. An exponential curve is difficult for both comparison and prediction as it has a vertical asymptotic trend to infinity. We have developed a platform-independent web-based system that automatically divides the duration of spread of the disease based on rate of increase in new cases, and shows a set of graphs which are easier to interpret and extrapolate than a single exponential graph. The shape of the graphs (like linear, parabolic or exponential) can be compared at different stages with respect to the average number of new cases and deaths. The system can be used to compare the spread of the pandemic at country, state and district levels.

It may also be noted that the fatality rate for any natural calamity or pandemic is often higher in people with disabilities and a major cause is not having access to relevant information. We are working on developing a Covid 19 dashboard for people with disabilities. Instead of looking for a specific disability we took an inclusive approach of adding new modalities of interaction with a web based Covid 19 dashboard that can include a wider population than existing ones. The present version of the system supports hands-free interaction through eye tracking, automatic speech recognition and text-to-speech converter.

Publication:

Pradipta Biswas, Kamalpreet Singh Saluja, Somnath Arjun, Lrd Murthy, Gowdham Prabhakar, Vinay Krishna Sharma, and Jeevitha Shree Dv. 2020. COVID-19 Data Visualization through Automatic Phase Detection. Digit. Gov.: Res. Pract. 1, 4, Article 25 (August 2020), 8 pages. DOI: