We modelled emergence and spread of the Omicron variant of SARS-CoV-2 in Australia between December 2021 and June 2022. This pandemic stage exhibited a diverse epidemiological profile with emergence of co-circulating sub-lineages of Omicron, further complicated by differences in social distancing behaviour which varied over time. Our study delineated distinct phases of the Omicron-associated pandemic stage, and retrospectively quantified the adoption of social distancing measures, fluctuating over different time periods in response to the observable incidence dynamics. We also modelled the corresponding disease burden, in terms of hospitalisations, intensive care unit occupancy, and mortality. Supported by good agreement between simulated and actual health data, our study revealed that the nonlinear dynamics observed in the daily incidence and disease burden were determined not only by introduction of sub-lineages of Omicron, but also by the fluctuating adoption of social distancing measures. Our high-resolution model can be used in design and evaluation of public health interventions during future crises.

This paper presents the findings of an exploratory study on the continuously generating Big Data on Twitter related to the sharing of information, news, views, opinions, ideas, feedback, and experiences about the COVID-19 pandemic, with a specific focus on the Omicron variant, which is the globally dominant variant of SARS-CoV-2 at this time. A total of 12028 tweets about the Omicron variant were studied, and the specific characteristics of tweets that were analyzed include - sentiment, language, source, type, and embedded URLs. The findings of this study are manifold. First, from sentiment analysis, it was observed that 50.5% of tweets had a neutral emotion. The other emotions - bad, good, terrible, and great were found in 15.6%, 14.0%, 12.5%, and 7.5% of the tweets, respectively. Second, the findings of language interpretation showed that 65.9% of the tweets were posted in English. It was followed by Spanish, French, Italian, and other languages. Third, the findings from source tracking showed that Twitter for Android was associated with 35.2% of tweets. It was followed by Twitter Web App, Twitter for iPhone, Twitter for iPad, and other sources. Fourth, studying the type of tweets revealed that retweets accounted for 60.8% of the tweets, it was followed by original tweets and replies that accounted for 19.8% and 19.4% of the tweets, respectively. Fifth, in terms of embedded URL analysis, the most common domain embedded in the tweets was found to be twitter.com, which was followed by biorxiv.org, nature.com, and other domains. Finally, to support similar research in this field, we have developed a Twitter dataset that comprises more than 500,000 tweets about the SARS-CoV-2 omicron variant since the first detected case of this variant on November 24, 2021.

The COVID-19 Omicron variant, reported to be the most immune evasive variant of COVID-19, is resulting in a surge of COVID-19 cases globally. This has caused schools, colleges, and universities in different parts of the world to transition to online learning. As a result, social media platforms such as Twitter are seeing an increase in conversations related to online learning in the form of tweets. Mining such tweets to develop a dataset can serve as a data resource for different applications and use-cases related to the analysis of interest, views, opinions, perspectives, attitudes, and feedback towards online learning during the current surge of COVID-19 cases caused by the Omicron variant. Therefore, this work presents a large-scale open-access Twitter dataset of conversations about online learning from different parts of the world since the first detected case of the COVID-19 Omicron variant in November 2021. The dataset is compliant with the privacy policy, developer agreement, and guidelines for content redistribution of Twitter, as well as with the FAIR principles (Findability, Accessibility, Interoperability, and Reusability) principles for scientific data management. The paper also briefly outlines some potential applications in the fields of Big Data, Data Mining, Natural Language Processing, and their related disciplines, with a specific focus on online learning during this Omicron wave that may be studied, explored, and investigated by using this dataset.

The COVID-19 outbreak resulted in multiple waves of infections that have been associated with different SARS-CoV-2 variants. Studies have reported differential impact of the variants on respiratory health of patients. We explore whether acoustic signals, collected from COVID-19 subjects, show computationally distinguishable acoustic patterns suggesting a possibility to predict the underlying virus variant. We analyze the Coswara dataset which is collected from three subject pools, namely, i) healthy, ii) COVID-19 subjects recorded during the delta variant dominant period, and iii) data from COVID-19 subjects recorded during the omicron surge. Our findings suggest that multiple sound categories, such as cough, breathing, and speech, indicate significant acoustic feature differences when comparing COVID-19 subjects with omicron and delta variants. The classification areas-under-the-curve are significantly above chance for differentiating subjects infected by omicron from those infected by delta. Using a score fusion from multiple sound categories, we obtained an area-under-the-curve of 89% and 52.4% sensitivity at 95% specificity. Additionally, a hierarchical three class approach was used to classify the acoustic data into healthy and COVID-19 positive, and further COVID-19 subjects into delta and omicron variants providing high level of 3-class classification accuracy. These results suggest new ways for designing sound based COVID-19 diagnosis approaches.

As scientists make strides in finding answers about COVID-19, artificial intelligence has aided one Michigan State University researcher and his team in finding answers about the new omicron variant. The MSU researchers report omicron and other variants are evolving increased infectivity and antibody resistance according to an artificial intelligence model. Therefore, new vaccines and antibody therapies are needed, the researchers say. Understanding how SARS-CoV-2 evolves is essential to predicting vaccine breakthrough and designing mutation-proof vaccines and monoclonal antibody treatments. In a recent study in American Chemical Society Infectious Diseases, Guowei Wei, professor in MSU's Departments of Mathematics as well as Electrical and Computer Engineering, and colleagues, analyzed almost 1.5 million SARS-CoV-2 genome sequences taken from people with COVID-19.

In a recent study posted to the bioRxiv* preprint server, researchers designed artificial intelligence (AI)-based primers for the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) Omicron variant. While several mutations seen in Omicron have been detected in earlier variants, a combination of a high number of such mutations confer the variant with high transmissibility, increased binding affinity to the host cell receptor, immune evasion, decreased antibody neutralization among other properties. The identification of the Omicron variant was achieved using multiple targets or the search for gene target failures (S-gene target failure or SGTF), amplification, and sequencing. Although different methodologies exist to detect the Omicron variant in clinical samples, Omicron-specific primers are not available yet. In the present study, the authors developed Omicron-specific primers based on an AI technique.

The scene was a stretch of railroad tracks in Lincoln Heights on Saturday: A blizzard of torn plastic wrappers, cardboard boxes and paper packaging attesting to a wave of rail car thievery that officials say has been on the rise in recent months. Several scavengers picked through the debris, hoping to find electronics, clothes or whatever valuables thieves left behind. "Everything comes on the train -- cellphones, Louis Vuitton purses, designer clothes, toys, lawnmowers, power equipment, power tools," said a 37-year-old man who declined to give his name. He said he comes to the tracks regularly and once found a Louis Vuitton purse and a robotic arm worth five figures: "We find things here and there, make some money off of it." Thieves are pilfering railroad cars in a crime that harks back to the days of horseback-riding bandits, but is fueled by a host of modern realities, including the rise of e-commerce and Southern California's role as a hub for the movement of goods.

Fox News White House correspondent Jacqui Heinrich discusses the Biden administration's failure to deliver at-home COVID tests on'Special Report.' It's been six months since President Biden said the U.S. was close to declaring "independence from COVID-19," and yet the pandemic still shows no signs of slowing after the country set a global record for the number of cases Monday due to the spread of the highly transmissible omicron variant. The U.S. reported more than 1 million new coronavirus infections on Monday, setting a global record and almost doubling the previous record set last week. Hospitalizations have also skyrocketed across the country, but deaths have held relatively steady in recent weeks. President Biden listens during a virtual meeting about reducing the costs of meat through increased competition in the meat processing industry in the South Court Auditorium at the Eisenhower Executive Office Building on Jan. 3, 2022, in Washington, D.C. (Photo by Sarah Silbiger/Getty Images) Biden gave a speech Tuesday maintaining his position that "this continues to be a pandemic of the unvaccinated," even though breakthrough cases of COVID-19 among people who are fully vaccinated continue to rise across the country as new variants emerge.

One month after Japan's first confirmed case of the omicron variant, concerns are continuing to grow fast with Prime Minister Fumio Kishida requesting people to stay vigilant and to take basic preventive measures during the holiday season. "The omicron variant has been widely spreading around the world. While our nation has placed rigorous border measures, we are also proceeding with bringing forward the booster shots, offering more free PCR testing, introducing oral drugs and securing robust medical care systems with an assumption that the worst-scenario could occur," Kishida said in a video message on Wednesday. As many people are expected to return home, travel and have parties during the year-end to New Year holiday season, the prime minister has asked people to thoroughly take basic measures to avoid infection -- washing their hands, wearing face masks and avoiding the 3Cs (closed spaces, crowds and close-contact situations). Since the first omicron case was confirmed in a quarantine check at an airport on Nov. 30, the number of new COVID-19 infections in Japan has been rising, although the overall number of cases remain relatively small compared with the fifth wave.