The article highlights the damage COVID-19 can cause by attacking brain tissue which can lead to several neurological disorders; it is a collection of systematic review and meta-analysis reviews as well as different scientific studies. The article addresses the background of COVID-19 and the distinction between Long COVID and COVID-19, along with the general pathway that the virus of COVID-19 takes to infect a cell at a cellular level. The variety of symptoms that individuals experience can be a topic of interest, and this article discusses the variability in COVID-19 infection. Moreover, SARS-COV-2 can enter the body in different ways and attack different types of cells within the body, thus the article brings attention to the different mechanisms of infection. Due to the brain damage that can be caused by COVID-19, there are several neurological disorders the article addresses including status epilepticus, stroke, acute necrotizing encephalopathy, encephalitis, hypogeusia, hyposmia, guillain-barre syndrome, and systemic inflammatory response syndrome. Although these disorders have different routes of treatment, the article briefly talks about general treatments for COVID-19 that include antiviral drugs, immune modulators, and monoclonal antibody treatment. Given the significance of COVID-19, more research should be done to understand the variety of neurological disorders that can be an effect of COVID-19 infection.

The COVID-19 pandemic began in March of 2020 and drastically affected the global human population. Millions of people died due to a SARS-CoV-2 infection while many who survived developed devastating sequelae of the disease. In addition, the closure of schools and businesses led to international economic struggle in the year 2020 as global economies declined. Since the beginning of the pandemic, over 200,000 scientific articles have been published and compiled into a database that grows daily— a rare occurrence within the scientific community. This thesis uses natural language processing tools via Python and VOSviewer software to perform a bibliometric analysis on 205,712 papers published between January of 2020 and February of 2021 pertaining to COVID-19. We first investigate how to analyze these publications most effectively in terms of title versus abstract keyword searches, we further obtain the focus of the current scientific literature via co-occurrence analysis and clustering, and we at last discuss the time evolution of these topics over the course of 14 months.