https://socictopen.socict.org/files/original/ef88f77a5c444ce1421b7ad80b285277.pdf 5b8b97c901b393436c52a37e8d4e49ac 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 Simulation-based evaluation of school reopening strategies during COVID-19: A case study of São Paulo, Brazil. Creator An entity primarily responsible for making the resource E H M Cruz, J M Maciel, C L Clozato, M S Serpa, P O A Navaux, E Meneses, M Abdalah, M Diener Description An account of the resource During the coronavirus disease 2019 (COVID-19) pandemic, many countries opted for strict public health measures, including closing schools. After some time, they have started relaxing some of those restrictions. To avoid overwhelming health systems, predictions for the number of new COVID-19 cases need to be considered when choosing a school reopening strategy. Using a computer simulation based on a stochastic compartmental model that includes a heterogeneous and dynamic network, we analyse different strategies to reopen schools in the São Paulo Metropolitan Area, including one similar to the official reopening plan. Our model allows us to describe different types of relations between people, each type with a different infectiousness. Based on our simulations and model assumptions, our results indicate that reopening schools with all students at once has a big impact on the number of new COVID-19 cases, which could cause a collapse of the health system. On the other hand, our results also show that a controlled school reopening could possibly avoid the collapse of the health system, depending on how people follow sanitary measures. We estimate that postponing the schools' return date for after a vaccine becomes available may save tens of thousands of lives just in the São Paulo Metropolitan Area compared to a controlled reopening considering a worst-case scenario. We also discuss our model constraints and the uncertainty of its parameters. Date A point or period of time associated with an event in the lifecycle of the resource 2021 Subject The topic of the resource epidemiology, coronavirus, covid-19, epidemics, Mathematical Modelling Identifier An unambiguous reference to the resource within a given context 10.1017/S0950268821001059 Source A related resource from which the described resource is derived Epidemiology and infection