Impact of post-COVID-19 on the elderly-emotional stress and effects: A data science approach

Considering the current level of the majority of people affected by the COVID-19 pandemic in public, there seem to be lengthy financial and psychiatric consequences. Depression is a significant psychological condition among the aged, affecting their well-being. The goal of this research is to investigate the levels of tension and related variables in older adults. These could result in severe emotional and physiological abnormalities, including PTSD (post-traumatic stress disorder), stress, nervousness, suicidal tendencies, and behavioral issues. Isolation, disinformation on social networking sites, financial instability, and discrimination are all possible causes. Because medical practitioners are at significantly higher risk of getting PTSD and exhaustion, it is critical to study and investigate the effects and drivers to avoid, recognize, and control these disorders. Providing customer service for nervous people, videoconferencing, internet networking & assistance communities, promoting relaxation, investigating psychiatric repercussions, and designing and implementing appropriate therapies are relevant diagnoses. © 2022 Nova Science Publishers, Inc. All rights reserved.

State-wise prevalence of COVID 19 in India by using machine learning approaches

Coronavirus is one of the world’s most critical issues, till date. Comprehension of causative variables such as mellitus, heart-related issues, asthma, blood pressure, etc., including the intrinsic transmission mechanisms of the disease, COVID 19 and its eradication are important for neurological investigation. Hence, the advance of appropriate modeling approaches and methods applied to current corona information on the pervasiveness of the pandemic and other serious illness aspects, is taking consideration. The prevalence of COVID 19 in India has reached epidemic proportions, and this disease is becoming a significantly increasing case in India. In this work, polynomial regression analysis methods employ to to forecast the number of COVID 19 corona patients. In this, we described a decision tree, polynomial and random forest classification of disease in COVID 19 incidences modelling and forecasting in India and a predicted prevalence of high level of confidence.