http://socictopen.socict.org/files/original/f45bae4e584fb13ff0fb4cad7609c872.pdf 5cebe9d0ac7dd287536753c8c9460458 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 Epidemics Forecast From SIR-Modeling, Verification and Calculated Effects of Lockdown and Lifting of Interventions Creator An entity primarily responsible for making the resource R. Schlickeiser, R. Schlickeiser, M. Kröger Description An account of the resource Due to the current COVID-19 epidemic plague hitting the worldwide population it is of utmost medical, economical and societal interest to gain reliable predictions on the temporal evolution of the spreading of the infectious diseases in human populations. Of particular interest are the daily rates and cumulative number of new infections, as they are monitored in infected societies, and the influence of non-pharmaceutical interventions due to different lockdown measures as well as their subsequent lifting on these infections. Estimating quantitatively the influence of a later lifting of the interventions on the resulting increase in the case numbers is important to discriminate this increase from the onset of a second wave. The recently discovered new analytical solutions of Susceptible-Infectious-Recovered (SIR) model allow for such forecast. In particular, it is possible to test lockdown and lifting interventions because the new solutions hold for arbitrary time dependence of the infection rate. Here we present simple analytical approximations for the rate and cumulative number of new infections. Date A point or period of time associated with an event in the lifecycle of the resource 2021 Subject The topic of the resource Statistical analysis, coronavirus 2019-ncov, parameter estimation, pandemic spreading, time-dependent infection rate Identifier An unambiguous reference to the resource within a given context 10.3389/fphy.2020.593421 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 Physics