https://socictopen.socict.org/files/original/808ce8455ae13f9dc37cd64ce670693c.pdf cbd2124ce12853dbf80e183580b8544c Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Estimation and Monitoring of COVID-19's Transmissibility From Publicly Available Data Creator An entity primarily responsible for making the resource Antonio Silveira, Antonio Pereira Description An account of the resource The 2019 coronavirus disease (COVID-19) pandemic began in the city of Wuhan, China, at the end of 2019 and quickly spread worldwide. The disease is caused by contact with the SARS-CoV-2 virus, which probably jumped from an animal host to humans. SARS-CoV-2 infects various tissues in the body, notably the lungs, and patients usually die from respiratory complications. Mathematical models of the disease have been instrumental to guide the implementation of mitigation strategies aimed at slowing the spread of the disease. One of the key parameters of mathematical models is the basic reproduction ratio R0, which measures the degree of infectivity of affected individuals. The goal of mitigation is to reduce R0 as close or below 1 as possible, as it means that new infections are in decline. In this work, we use the recursive least-squares algorithm to establish the stochastic variability of a time-varying R0(t) from eight different countries: Argentina, Belgium, Brazil, Germany, Italy, New Zealand, Spain, and the United States. The proposed system can be implemented as an online tracking application providing information about the dynamics of the pandemic to health officials and the public at large. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource Mathematical modeling, covid-19, Transmission dynamics, epidemic spreading, Pattern recognition, Disease prediction Identifier An unambiguous reference to the resource within a given context 10.3389/fams.2020.565336 Source A related resource from which the described resource is derived Epidemiology and Health Publisher An entity responsible for making the resource available Korean Society of Epidemiology Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Applied mathematics. Quantitative methods, Probabilities. Mathematical statistics