ABSTRACT
COVID-19 has various symptoms, and they are cold, cough, mild or high fever, and breathing problems for severe cases. In addition, it is in talk that diabetes, chronic obstructive pulmonary disease (COPD), cardiovascular, asthma, and many diseases invite the virus. Machine learning and data analysis are considered best for predicting approaches for finding various aspects of the effect of the virus. In this chapter, the authors deal with symptoms that have been recorded in the dataset and try to find which pre-defined symptoms are considered effective or responsible in positive case of infection by coronavirus. The dataset has been taken from Kaggle. As the dataset is categorical in nature, the authors use correlation and logistic regression analysis to find the symptoms that prevail in the patient and have caused the infection in them. This is also about dimensionality reduction and feature selection where they are reducing the available features based on regression. © 2022, IGI Global.
ABSTRACT
Introduction: The world has been facing a pandemic of COVID-19, and while dealing with this pandemic is not easy for anyone, it is especially hard on health care workers (HCWs) as they are the front-line warriors. Aim of the study: To assess the psychological disturbances that the COVID-19 pandemic has inflicted on healthcare workers in India and to assess the correlation between different parameters including socio-demographic variables, job-related variables, personal history and psychological disturbances such as perceived stress, depression and anxiety. Material and methods: Health care workers from a few tertiary care institutes (government as well as private sectors, which are caring for patients with COVID-19) in a western state of India were invited to participate with a self-administered online questionnaire. That questionnaire consisted of self-report scales including Fear of COVID-19 Scale, the Depression, Anxiety and Stress Scale 21 items (DASS 21), and the Perceived Stress Scale with socio-demographic, job-related and personal details. Results: Out of 302 subjects, on the Perceived Stress Scale, 101 (33.44%) reported low, 185 (61.26%) moderate and 16 (5.30%) high levels of stress. On DASS 21, depression was reported by 56 (18.54%) subjects, 60 (19.87%) subjects were found to have anxiety and 50 (16.56%) subjects reported to have stress. Perceived stress score on Perceived Stress Scale (PSS) was significantly correlated with the depression, anxiety and stress score on DASS 21. A few risk factors such as female gender, single marital status, past history of psychiatric illness, working as interns and residents doctors with lesser experience and high risk duty areas such as COVID-19 duties in a particular situation were significantly associated with psychological disturbances such as stress, depression and anxiety. Conclusions: We observed significant psychological impacts of the COVID-19 pandemic on HCWs as well as a few risk factors related to it. Supporting the mental health of HCWs is a critical part of the public health response to maintain an adequate workforce and to maximize the ability of HCWs to face this pandemic. © 2020 Termedia Publishing House Ltd.. All rights reserved.
ABSTRACT
Background: Tuberculosis (TB) is long standing disease and SARS-COV-2 being global pandemic in current era. Interactions between SARS-COV-2 and TB needs analysis, as both has major infection-related morbidity and mortality worldwide. This study was conducted to evaluate impact of super imposing viral pandemic over chronic diseases like tuberculosis. Methodology: A Retrospective study done in 75 patients registered under RNTCP program at our centre. Epidemiological data, diagnostic timing of TB, duration of AKT, history of SARS-COV-2 symptoms and SARS-COV-2 diagnostic result were evaluated. Analysis conducted based on incidence of COVID-19 infection in active cases of TB.