Sentiment Analysis of COVID-19 Vaccination in Bangla Language with Code-Mixed Text from Social Media

The vaccination program which helps avert pandemics is facing new hurdles, including the emergence of hazardous new virus strains and public distrust. Analyzing the sentiment expressed in social media interactions related to vaccines may aid the health authority in implementing public safety procedures and guide the government in developing appropriate policies. The purpose of this research is to identify the public sentiments toward the COVID-19 vaccination in Bangladesh from social media comments. Comments posted on social media platforms often mix formal and informal language known as code-mixed text and do not adhere to any particular grammatical standards. In addition, the Bangla language lacks computational models and annotated resources for sentiment analysis. To overcome this, we created CoVaxBD, a Bangla-English code-mixed and sentiment-annotated corpus of Facebook comments. This paper also proposes a model for sentiment analysis based on the multilingual BERT. It achieves a validation accuracy of around 97.3 % and a precision score of approximately 97.4%. © 2022 IEEE.

Agent Based Simulatable City Digital Twin to Explore Dynamics of Covid-19 Pandemic

Predicting the evolution of Covid19 pandemic has been a challenge as it is significantly influenced by the characteristics of people, places and localities, dominant virus strains, extent of vaccination, and adherence to pandemic control interventions. Traditional SEIR based analyses help to arrive at a coarse-grained 'lumped up' understanding of pandemic evolution which is found wanting to determine locality-specific measures of controlling the pandemic. We comprehend the problem space from system theory perspective to develop a fine-grained simulatable city digital-twin for 'in-silico' experimentations to systematically explore - Which indicators influence infection spread to what extent? Which intervention to introduce, and when, to control the pandemic with some a-priori assurance? How best to return to a new normal without compromising individual health safety? This paper presents a digital twin centric simulation-based approach, illustrates it in a real-world context of an Indian City, and summarizes the learning and insights based on this experience. © 2022 IEEE.

Design and Development of Conversational Chatbot for Covid-19 using NLP: an AI application

Since the discovery of corona virus (nCOV-19), and its subsequent progression into a global pandemic, an enormous hurdle faced by hospitals and their healthcare staff has been to streamline, and look after the huge flow of cases. It has become increasingly difficult to consult a Covid specialist when the first wave occurred in rural and areas not connected as well to modern amenities. Thus, it has become obvious that an interactive Chatbot with efficient execution can help patients living in such areas by educating on the appropriate preventive measures, news on virus strains, reducing the psychological damage caused by the fear of the virus and mental effects of solitary isolation. This study displays and discusses the schematics of an artificial intelligence (AI) chatbot for the purpose of evaluation, diagnosis and recommending immediate preventive as well as safety measures for patients who have been exposed to nCOV-19, and doubles as a virtual assistant to aid in measuring the severity of the infection via symptom analysis and connects with the authorised medical facilities when it progresses to a serious stage. © 2022 IEEE.

Convolution Neural network based Marine Predator Algorithm for COVID-19 detection

COVID-19 is among the dangerous illness in the world due to its quickly spreading, posing a new challenge for researchers to discover it early. In last few months, new covid19 virus strains have been found in South Africa, India, and United Kingdom (UK) due to the mutation of the virus. Owing this critical situation of the world health and with increased number of the cases with the absence of efficient a cure vaccine, timely quarantine and medical treatment, as well as reliable identification of COVID-19, are required to prevent and contain this pandemic. Radiology images and Artificial Intelligence techniques are the most used techniques in computer-aided medical diagnosis for Covid-19 detection. The present paper shows a Convolution Neural Network based novel metaheuristic techniques called Marine Predator Algorithm for detecting Covid-19 and well differentiate between Covid-19 and Pneumonia disease. Our proposed system achieves good results in term of classification such as 93% of accuracy, 95% of precision, 97% of recall and F1-score 95%. © 2021 IEEE.

Monitoring of Social distancing Face mask Using CNN

The outbreak of the Pandemic in last few months, rapid increase in the transmission of the virus and also the new emerging various strains of COVID-19 corona virus has led to complete Iockdown in the entire world. Meanwhile Iockdown imposed on various countries for longer duration has affected almost every sector of the society causing loss leading to hunger and poverty in the world. By considering all the situations and difficulties underwent by the human society a clear scenario where country not only needs Iockdown as it cannot be the effective solution in slowing down the rate of disease affecting people, So Society is Constantly looking for the alternatives that could help every sector in their business without loss is the topic of the hour. An alternative which could satisfy the above conditions is by Social Distancing and Wearing the Face mask. There by proposing our Real Time System which will detect whether required distance is maintained between two people and detect whether the face mask is worn or not by people with the aid of Web Camera using the most trending technologies Artificial Intelligence, Machine Learning Algorithms, Deep Learning, CNN and few more. © 2021 IEEE.

A review on evolution of emerging SARS-CoV-2 variants based on spike glycoprotein.

Since the inception of SARS-CoV-2 in December 2019, many variants have emerged over time. Some of these variants have resulted in transmissibility changes of the virus and may also have impact on diagnosis, therapeutics and even vaccines, thereby raising particular concerns in the scientific community. The variants which have mutations in Spike glycoprotein are the primary focus as it is the main target for neutralising antibodies. SARS-CoV-2 is known to infect human through Spike glycoprotein and uses receptor-binding domain (RBD) to bind to the ACE2 receptor in human. Thus, it is of utmost importance to study these variants and their corresponding mutations. Such 12 different important variants identified so far are B.1.1.7 (Alpha), B.1.351 (Beta), B.1.525 (Eta), B.1.427/B.1.429 (Epsilon), B.1.526 (Iota), B.1.617.1 (Kappa), B.1.617.2 (Delta), C.37 (Lambda), P.1 (Gamma), P.2 (Zeta), P.3 (Theta) and the recently discovered B.1.1.529 (Omicron). These variants have 84 unique mutations in Spike glycoprotein. To analyse such mutations, multiple sequence alignment of 77681 SARS-CoV-2 genomes of 98 countries over the period from January 2020 to July 2021 is performed followed by phylogenetic analysis. Also, characteristics of new emerging variants are elaborately discussed. The individual evolution of these mutation points and the respective variants are visualised and their characteristics are also reported. Moreover, to judge the characteristics of the non-synonymous mutation points (substitutions), their biological functions are evaluated by PolyPhen-2 while protein structural stability is evaluated using I-Mutant 2.0.

The COVID-19 pandemic through eyes of a NYC fertility center: a unique learning experience with often unexpected results.

Affecting basic tenets of human existence such as health, economic as well as personal security and, of course, reproduction, the COVID-19 pandemic transcended medical specialties and professional disciplines. Yet, six months into the pandemic, there still exists no consensus on how to combat the virus in absence of a vaccine. Facing unprecedented circumstances, and in absence of real evidence on how to proceed, our organization early in the pandemic decided to act independently from often seemingly irrational guidance and, instead, to carefully follow a quickly evolving COVID-19 literature. Here described is the, likely, unique journey of a fertility center that maintained services during peaks of COVID-19 and political unrest that followed. Closely following publicly available data, we recognized relatively early that New York City and other East Coast regions, which during the initial COVID-19 wave between March and May represented the hardest-hit areas in the country, during the second wave, beginning in June and still in progress, remained almost completely unaffected. In contrast, south western regions, almost completely unaffected by the initial wave, were severely affected in the second wave. These two distinctively different infectious phenotypes suggested two likely explanations: The country was witnessing infections with two different SARS-CoV-2 viruses and NYC (along with the East Coast) acquired during the first wave much better immunity to the virus than south western regions. Both hypotheses since have been confirmed: East and West Coasts, indeed, were initially infected by two distinctively different lineages of the virus, with the East Coast lineage being 10-times more infectious. In addition, immunologists discovered an up to this point unknown long-term anti-viral innate (cellular) immune response which offers additional and much broader anti-viral immunity than the classical adaptive immunity via immobilizing antibodies that has been known for decades. Consequently, we predict that in the U.S., even in absence of an available vaccine, COVID-19, by September-October, will be at similarly low levels as are currently seen in NYC and other East Coast regions (generally < 1% test-positivity). We, furthermore, predict that, if current mitigation measures are maintained and no newly aggressive mutation of the virus enters the country, a significant fall-wave of COVID-19, in combination with the usual fall wave of influenza, appears unlikely. To continue serving patients uninterrupted throughout the pandemic, turned for all of our center's staff into a highly rewarding experience, garnered respect and appreciation from patients, and turned into an absolutely unique learning experience.