http://socictopen.socict.org/files/original/15a2d1eda7ed978bef499745f1f79bb3.pdf 8f3ace7ada0b257cfbbd9e271fcb6919 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 Impact of Lockdown on the Epidemic Dynamics of COVID-19 in France Creator An entity primarily responsible for making the resource Samuel Soubeyrand, Lionel Roques, Julien Papaïx, Etienne K Klein, Antoine Sar Description An account of the resource The COVID-19 epidemic was reported in the Hubei province in China in December 2019 and then spread around the world reaching the pandemic stage at the beginning of March 2020. Since then, several countries went into lockdown. Using a mechanistic-statistical formalism, we estimate the effect of the lockdown in France on the contact rate and the effective reproduction number Re of the COVID-19. We obtain a reduction by a factor 7 (Re = 0.47, 95%-CI: 0.45–0.50), compared to the estimates carried out in France at the early stage of the epidemic. We also estimate the fraction of the population that would be infected by the beginning of May, at the official date at which the lockdown should be relaxed. We find a fraction of 3.7% (95%-CI: 3.0–4.8%) of the total French population, without taking into account the number of recovered individuals before April 1st, which is not known. This proportion is seemingly too low to reach herd immunity. Thus, even if the lockdown strongly mitigated the first epidemic wave, keeping a low value of Re is crucial to avoid an uncontrolled second wave (initiated with much more infectious cases than the first wave) and to hence avoid the saturation of hospital facilities. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource Bayesian inference, SIR model, SARS-CoV-2, COVID-19, lockdown, mechanistic-statistical model Identifier An unambiguous reference to the resource within a given context DOI: 10.3389/fmed.2020.00274 Source A related resource from which the described resource is derived Frontiers in Medicine Publisher An entity responsible for making the resource available Frontiers Media S.A. Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Medicine (General)