Globally, an approximate of 380,000 patients succumbed to death due to the pandemic COVID-19 which also infected more than six million people since December 2019. Not sparing anyone, COVID-19 infections are widely reported among healthcare professionals, sanitation workers and researchers too while global leaders and various governments are providing their best in defending their citizens against this airborne and contact spread virus. In order to contain the virus and protect millions of lives from this deadly coronavirus, there is a need to have a combination of advanced engineering technology and medical facilities. Application of applied science, engineering and technology diffuse almost every aspect of contemporary living. Grasping the fundamentals to determine humanity's most imperative and forthcoming challenges is essential. Artificial Intelligence, the technology that learns, adapts and reciprocates the actions according to the situations, finds optimum position in the fight against corona virus and acts as a powerful tool against this pandemic. In this research article, the authors discusses how Artificial Intelligence (AI) can be leveraged to fight the deadly virus. The research paper further discusses the efficient utilization of AI across the globe to help in testing, treating and serving the population in these hard times. This manuscript focuses on the potential impact of the process in which AI can be implemented to prevent, test and treat.

Background: Non communicable diseases are responsible for a high proportion of deaths and disabilities. The major risk factors attributed to this are smoking, heavy alcohol drinking, inadequate fruit, and vegetable consumptions, and physical inactivity. While there are data available to understand the prevalence of non-communicable risk factors among men and women, there is no data among transgender community. Hence this study was conducted to assess the prevalence of NCD risk factors among the male-to-female transgender community. Methods: This cross sectional study was conducted among 54 transwomen who had been registered with two social welfare organizations for transgender community in Chennai. The risk factor was assessed using WHO STEPS instrument. Results: Among the transwomen, 16.7% were currently smoking tobacco, while 18.5% were using smokeless forms of tobacco. Alcohol consumption was observed in 44.4% of the population. 62.9% of them were not involved in any kind of exerting physical activity for recreation. 25.9% had undergone hormone supplementation for gender affirmation. Prevalence of obesity was 20.4% in the study population. The prevalence of hypertension, diabetes and hypercholesterolemia was 11.1%, 5.6% and 7.4% respectively. Conclusions: High Prevalence of certain risk factors such as smokeless tobacco usage, alcohol consumption and hormone supplementation were seen among the male-to-female transgender community compared to the general population. Targeted interventions must be made so that specific attention is given to the transgender community in various NCD programs by the government. They must also be supported and accepted by every member of this society.

Background: During the COVID-19 pandemic, millions of Indians were self-quarantined generating exceptional challenges and stress for all people and more so among regular tobacco users. Tobacco use is known to be detrimental to lung and immune function, thus suppressing the body's ability to combat infections including the novel coronavirus, COVID-19. This study was intended at surveying the stress, tobacco consumption patterns, and the coping behavior during the COVID-19 pandemic. Methodology: Seven hundred and twenty-nine current tobacco users aged 18 years and above participated in the questionnaire study on stress due to COVID-19, tobacco consumption patterns during lockdown, years of tobacco use, prior quit attempts, thoughts of quitting currently, and means of purchasing and coping behavior. The data were subjected to statistical analysis. Results: The average Fagerström Test for Nicotine Dependence score was 6, and males had higher scores than females. 68.4% of tobacco users reported increased use, 5.07% decreased use, and 26.4% no change in tobacco use during the lockdown. Causes for increased tobacco use were stress (62.1%), being alone and restrictions in movement (21.6%), and boredom (16.3%), while the fear of contracting COVID infection and becoming severely ill has motivated few (31.6%) to decrease tobacco use. 50.9% wanted to quit, the thought of quitting tobacco was more among men (54%) as compared to women and was higher among smokers as compared to smokeless tobacco users. Conclusion: Tobacco users appear to be affected by stress related to the COVID-19 pandemic, with majority of them increasing the consumption.

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Human race has faced many epidemics and pandemics in past. The trajectory reveals that there is a pandemic almost every century. Our generation has witnessed the outbreak of coronavirus disease (COVID-19) pandemic, which turned out to be largest pandemic ever. Viruses have affected global population in the past century can answer the questions of the post Corona trauma. It has been noticed that most of the epidemics and pandemics are inflicted by the influenza viruses. Scientists have elucidated the structures of the viruses that have infected earlier. The homology between them and COVID-19 can be studied in order to fight the virus. In this paper, journey of novel corona virus has been discussed from a simple flu to become a pandemic within a short span of time. All the factors including the major countries responsible for spreading the pandemic owing to their volume, speed of human travel and socio-economic reasons seems to be the reason according to the review. We also compared the structures of the epidemic and pandemic causing viruses. Some of the COVID-19 studies mentioned which used machine learning models, and then by the use of machine learning we analyzed characteristics of three diseases (H1N1, COVID-19, and SARS) to obtain the plots of the autocorrelation against the lag of the number of confirmed cases, recovered cases, and deaths of/caused by COVID-19.