ABSTRACT
The whole world is presently battling against the Coronavirus pandemic, which has tested every aspect of life. The virus spread has severe implications on the global economy. In the face of a deteriorating economic environment brought on by globalisation, Indian industries must bear the significant economic brunt and suffer severe consequences. One among the seriously affected industry is the well-reputed Indian IT industry. During COVID 19 era, employees from the IT sector have faced various troublesome situations. In the present study, a web-based survey consisting of questions concerning WFH during pandemic has been conducted to visualise the repercussions caused due to COVID 19 pandemic. This paper studies the benefits, challenges, and implications for IT firms moving forward while also analysing employees’ perceptions of the current work situation to improve the current systems. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
The SARS-CoV-2 driven disease COVID-19 is pandemic with increasing human and monetary costs. COVID-19 has put an unexpected and inordinate degree of pressure on healthcare systems of strong and fragile countries alike. To launch both containment and mitigation measures, each country requires estimates of COVID-19 incidence as such preparedness allows agencies to plan efficient resource allocation and to design control strategies. Here, we have developed a new adaptive, interacting, and cluster-based mathematical model to predict the granular trajectory of COVID-19. We have analyzed incidence data from three currently afflicted countries of Italy, the United States of America, and India. We show that our approach predicts state-wise COVID-19 spread for each country with reasonable accuracy. We show that Rt, as the effective reproduction number, exhibits significant spatial variations in these countries. However, by accounting for the spatial variation of Rt in an adaptive fashion, the predictive model provides estimates of the possible asymptomatic and undetected COVID-19 cases, both of which are key contributors in COVID-19 transmission. We have applied our methodology to make detailed predictions for COVID19 incidences at the district and state level in India. Finally, to make the models available to the public at large, we have developed a web-based dashboard, namely "Predictions and Assessment of Corona Infections and Transmission in India" (PRACRITI, see http://pracriti.iitd.ac.in), which provides the detailed Rt values and a three-week forecast of COVID cases.