Understanding Variation: The Key To Managing Chaos.epub
COVID-19 is a Severe Acute Respiratory Syndrome (SARS), caused by SARS-CoV-2, a novel virus which belongs to the family Coronaviridae. It was first reported in December 2019 in the Wuhan city of China and soon after, the virus and hence the disease got spread to the entire world. As of February 26, 2021, SARS-CoV-2 has infected 112.20 million people and caused 2.49 million deaths across the globe. Although the case fatality rate among SARS-CoV-2 patient is lower (2.15%) than its earlier relatives, SARS-CoV (9.5%) and MERS-CoV (34.4%), the SARS-CoV-2 has been observed to be more infectious and caused higher morbidity and mortality worldwide. As of now, only the knowledge regarding potential transmission routes and the rapidly developed diagnostics has been guiding the world for managing the disease indicating an immediate need for a detailed understanding of the pathogen and the disease-biology. Over a very short period of time, researchers have generated a lot of information in unprecedented ways in the key areas, including viral entry into the host, dominant mutation, potential transmission routes, diagnostic targets and their detection assays, potential therapeutic targets and drug molecules for inhibiting viral entry and/or its replication in the host including cross-neutralizing antibodies and vaccine candidates that could help us to combat the ongoing COVID-19 pandemic. In the current review, we have summarized the available knowledge about the pathogen and the disease, COVID-19. We believe that this readily available knowledge base would serve as a valuable resource to the scientific and clinical community and may help in faster development of the solution to combat the disease.
Understanding Variation: The Key To Managing Chaos.epub
He was the first to propose a systematic, scientific approach to the design and analysis of experiments, pioneered in his classic and still highly readable book The Design of Experiments, first published in 1935 (Fisher 1935a). He promoted and formalised understanding of close local control (often referred to as blocking) and replication, as ways of increasing the reliability of inferences on the effects of treatments. He pointed out that more information could be gained from an experiment using all combinations of levels of two or more treatment factors (such as sowing date and amount of manure) than from consecutive experiments which each investigated one factor at a time. He emphasised the importance of distinguishing between three sources of variation: experimental treatment, other observed (designed/planned) sources of variation (such as different fields) and unobserved sources of variation. In order to deal with the latter, Fisher also championed the need for randomisation to obtain valid and unbiased estimates of effects (for example, of applications of fertilisers in plant breeding experiments or clinical trials of drug treatments for testing their efficacy) and also valid estimates of their reliability. Fisher particularly emphasised the importance of having statisticians embedded in agricultural, medical and other research institutes, an approach that helped to widen the successful application of his many innovative statistical developments.