Impact and Inescapable Effects of Coronavirus: History to Modern Pandemic Episode

Coronavirus disease 2019 (COVID-19) is an acute respiratory tract infection causing a pandemic that emerged in 2019 initially in China involving 13.8% cases with severe, and 6.1% with critical course and later throughout the globe. Vaccines or antiviral medications are yet to be used to prevent or treat infections of Human Coronavirus (HCoV). The much-discovered HCoV found in 2003, SARS-COVID-19, which caused respiratory syndrome, has special pathogenesis as it causes respiratory tract infection. The coronavirus spike protein's association with its host cell receptor complement is crucial in deciding the virus infectivity, tissue tropism and species variety. SARS, COVID-19, infects human cells by binding to angiotensin-converting enzyme 2 (ACE2) receptor and uses the TMPRSS2 cell protease to activate it. Lungs are most affected by COVID-19 as host cells are accessed by the virus through ACE2, which is most abundant in alveolar cells of the lungs. Special attention and efforts should be given in reducing transmission in vulnerable populations, including infants, health care providers and the elderly. COVID 19, is the main causative agent of potentially lethal disease and is of significant concern for global public health and in pandemics which was highlighted in this review.Copyright © 2021 Bentham Science Publishers.

The study of the effect of the data collected during vaccination period on the prediction of the number of Covid-19 cases

Coronavirus disease (Covid-19) is a serious health problem for the world. Most of the countries are affected by this infectious disease. Many countries have started vaccination against Covid-19. The number of confirmed cases every day changes rapidly. Public health planners want to know these numbers in advance to arrange health facilities accordingly. Many machine learning models have been developed for the prediction of the number of Covid-infected people. The accuracy of these models depends upon the training data. Data collected during the period when there is no vaccination and data collected during the vaccination period have different properties. The models trained on different datasets perform differently. In this paper, we study the effect of the data collected during the vaccination period. The study will be helpful in generating more accurate prediction models for the vaccination period.

A Data Driven Decision Making and Contract Tracing App for Organizations to Combat COVID-19

In this paper we review the threat posed by the COVID-19 pandemic, the justification for the elimination strategy adopted by New Zealand, and some of the actions required to maximize the chances of success. During the current COVID-19 pandemic, there have been many efforts to predict the infection cases, number of fatalities, and other medical indicators, using a range of statistical or epidemiological models. During the current COVID-19 pandemic, there have been many efforts to forecast the infection cases, deaths and other medical indicators including hospital capacity calculation, with a variety of predictive epidemiological models. These forecasting projects have influenced policies in some countries. However, the prediction of the COVID-19 pandemic as a 'wicked problem' is uncertain by nature. The uncertainty is deep-rooted in the many unknown unknowns about the communicable virus itself and the complexity, heterogeneity and dynamism of human behaviors, government interventions and testing protocols. As there are no set standards between and sometimes within the countries, it makes it a 'wicked problem', nearly impossible to predict. The wicked and uncertain nature of this pandemic makes the aim for prediction accuracy deceptive. Herein, we propose to be cautious about the intent for 'accurate' predictions or models. Instead of making inaccurate predictions let us try to understand the data that is available to us to explore the significant indicators of the uncertainty. Such indicators are expected to make the planning and policy more 'future-informed' and possibly introduce and guide pre-cautionary actions now to shape the real future. Also, we have proposed here a Power Apps-based app for organizational users to do a check in on their known location(s) to facilitate contact tracing if needed in an event of Novel Coronavirus suspected case as the countries move between different lockdown levels. © 2020 IEEE.