Data Analytics on COVID-19 Survey Dataset

Abstract: Data Analytics and Predictive analysis is essential on medical records, because the extent of spread of COVID-19 disease is huge and is already declared as a pandemic. Coronaviruses are a group of viruses which have been said to have originated from Wuhan, China belonging to the family of Coronaviridae. Human coronaviruses can cause lung infections which can be fatal if left untreated. COVID-19 death is defined for surveillance purposes as a death resulting from a clinically compatible illness in a probable or confirmed COVID-19 case, unless there is a clear alternative cause of death that cannot be related to COVID disease.[1] There should be no period of complete recovery between the illness and death. In our paper we have published the results based on a survey conducted by our team and, used Data Analytic tools and Predictive Analysis on the acquired data. Vital questions have been asked and opinions have been collected from around 500 residents of each area in Bangalore Urban zone. Visualization tools using Python libraries have refined our data visualization process. Sampling rate is fixed not to overfit or under fit during supervised learning using Artificial Intelligence (AI).

Keywords: Data Analytics and Predictive analysis, Coronaviruses, Coronaviridae, COVID-19, Data Analytic tools and Predictive Analysis, Visualization tools, Python libraries, supervised learning using Artificial Intelligence (AI).