A Review of COVID-19 and Its Waterfall Effect on the Changed World (preprint)

2019 novel coronavirus has affected over 19.3 million people and caused over 718 thousand deaths globally (as at 7 August 2020). The disease was named as “Covid19” and the virus that causes it was Severe Acute Respiratory Syndrome Corona Virus -2 (SARS-COV-2). On the eve of 2020, when the whole world was celebrating the new year, the virus was unleashing and conquering new territories, minute by minute. So, how come a small virus that is said to have originated from Wuhan, China was able to create such a big havoc? How did a flu-like-symptom virus was able to shackle economies and change the world we live in? What caused Governments to announce relief, fiscal and economic packages to prevent the large-scale economic collapse? The response lies in the way the virus made man-kind to live in the new world. Social distancing was the new norm that led to fewer interactions among people. Next, mass scale shut downs announced by the governments led to closure of financial markets, stock exchanges, corporate offices, exchange of trade as well as several events. No country was immune by the shocks caused by the waterfall effect of COVID19. The compounding rate at which the virus spread hinted several sectors were going to be severely disrupted. The current paper will analyze the waterfall effect of COVID19 on several sectors in the first half of 2020 (Jan to June 2020) and ascertain the fiscal, economic and monetary policies announced by governments in the top 5 affected countries and UAE as at 7 August 2020. The study will qualitatively ascertain how lockdowns and social distancing changed the world we live in and provide certain recommendations for future pandemics/ crises as part of research contribution.

Network theoretic analysis of JAK/STAT pathway and extrapolation to drugs and viruses including COVID-19 (preprint)

Whenever some phenomenon can be represented as a graph or a network it seems pertinent to explore how much the mathematical properties of that network impact the phenomenon. In this study we explore the same philosophy in the context of immunology. Our objective was to assess the correlation of “size” (number of edges and minimum vertex cover) of the JAK/STAT network with treatment effect in rheumatoid arthritis (RA), phenotype of viral infection and effect of immunosuppressive agents on a system infected with the coronavirus. We extracted the JAK/STAT pathway from Kyoto Encyclopedia of Genes and Genomes (KEGG, hsa04630). The effects of the following drugs, and their combinations, commonly used in RA were tested: methotrexate, prednisolone, rituximab, tocilizumab, tofacitinib and baricitinib. Following viral systems were also tested for their ability to evade the JAK/STAT pathway: Measles, Influenza A, West Nile virus, Japanese B virus, Yellow Fever virus, respiratory syncytial virus, Kaposi’s sarcoma virus, Hepatitis B and C virus, cytomegalovirus, Hendra and Nipah virus and Coronavirus. Good correlation of edges and minimum vertex cover with clinical efficacy were observed (for edge, rho= -0.815, R 2 = 0.676, p=0.007, for vertex cover rho= -0.793, R 2 = 0.635, p=0.011). In the viral systems both edges and vertex cover were associated with acuteness of viral infections. In the JAK/STAT system already infected with coronavirus, maximum reduction in size was achieved with baricitinib. To conclude, algebraic and combinatorial invariant of a network may explain its biological behaviour. At least theoretically, baricitinib may be an attractive target for treatment of coronavirus infection.