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This study leveraged the phylogenetic analysis of more than 10K strains of novel coronavirus (SARS-CoV-2) from 67 countries. Due to the requirement of high-end computational power for phylogenetic analysis, we leverage a fast yet highly accurate alignment-free method to develop the phylogenetic tree out of all the strains of novel coronavirus. K-Means clustering and PCA-based dimension reduction technique were used to identify a representative strain from each location. The resulting phylogenetic tree was able to highlight evolutionary relationships of SARS-CoV-2 genome and, subsequently, linked to the interpretation of facts and figures across the globe for the spread of COVID-19. Our analysis revealed that the geographical boundaries could not be explained by the phylogenetic analysis of novel coronavirus as it placed different countries from Asia, Europe and the USA in very close proximity in the tree. Instead, the commute of people from one country to another is the key to the spread of COVID-19. We believe our study will support the policymakers to contain the spread of COVID-19 globally. [ABSTRACT FROM AUTHOR]

COVID-19 pandemic is taking a toll on the social, economic, and psychological well-being of people. During this pandemic period, people have utilized social media platforms (e.g., Twitter) to communicate with each other and share their concerns and updates. In this study, we analyzed nearly 25M COVID-19 related tweets generated from 20 different countries and 28 states of USA over a month. We leveraged sentiment analysis and topic modeling over this collection and clustered different geolocations based on their sentiment. Our analysis identified 3 geo-clusters (country- and US state-based) based on public sentiment and discovered 15 topics that could be summarized under three main themes: government actions, medical issues, and people's mood during the home quarantine. The proposed computational pipeline has adequately captured the Twitter population's emotion and sentiment, which could be linked to government/policy makers' decisions and actions (or lack thereof). We believe that our analysis pipeline could be instrumental for the policymakers in sensing the public emotion/support with respect to the interventions/actions taken, for example, by the government instrumentality. [ABSTRACT FROM AUTHOR]