The COVID-19 outbreak resulted in multiple waves of infections that have been associated with different SARS-CoV-2 variants. Studies have reported differential impact of the variants on respiratory health of patients. We explore whether acoustic signals, collected from COVID-19 subjects, show computationally distinguishable acoustic patterns suggesting a possibility to predict the underlying virus variant. We analyze the Coswara dataset which is collected from three subject pools, namely, i) healthy, ii) COVID-19 subjects recorded during the delta variant dominant period, and iii) data from COVID-19 subjects recorded during the omicron surge. Our findings suggest that multiple sound categories, such as cough, breathing, and speech, indicate significant acoustic feature differences when comparing COVID-19 subjects with omicron and delta variants. The classification areas-under-the-curve are significantly above chance for differentiating subjects infected by omicron from those infected by delta. Using a score fusion from multiple sound categories, we obtained an area-under-the-curve of 89% and 52.4% sensitivity at 95% specificity. Additionally, a hierarchical three class approach was used to classify the acoustic data into healthy and COVID-19 positive, and further COVID-19 subjects into delta and omicron variants providing high level of 3-class classification accuracy. These results suggest new ways for designing sound based COVID-19 diagnosis approaches.

As we all want to know the science behind virus severity to lead better well planned lives. If not through logics of biology then AI can come in to help. How a virus effects lungs while another just causes cold and cough, there must be some biology behind this. If not sure take help of AI and Machines which can Learn anything these days once data is collected and data fed in the machines. In this article I present my proposal to detect virus severity right after the virus structure has been detected.

Right about now, a whole lot of parents are looking around and asking themselves: What is school going to look like this year? Here in New York, this is the time of year when I get letters telling me who my kids' teachers are going to be and how to track down school supplies. In other parts of the country, kids are already back in classrooms. And after more than a year of disrupted and hybrid learning, everyone has had this hope that this year will be different. You just have to press play on a couple of videos from school board meetings across the country to realize how elusive "normal" still is. A lot of the meetings I've been watching recently are about masks--who should be wearing them and who shouldn't.