An innovative approach to estimate infection by COVID-19

dc.contributor.authorOliveira, Manuela
dc.contributor.authorGarção, Eugénio
dc.contributor.authorGrilo, Luís M.
dc.contributor.authorAlexandre, Armando
dc.contributor.authorMexia, João T.
dc.date.accessioned2022-12-28T15:28:50Z
dc.date.available2022-12-28T15:28:50Z
dc.date.issued2022-09
dc.description.abstractGiven that individuals in a certain population are different (among other things they have a different immune system), it is possible that some are infected with the known virus COVID-19 and are asymptomatic and therefore not diagnosed with the disease. Thus, estimates of the number of infected and dead with COVID-19 may not correspond to reality. This study seeks to indicate a procedure to estimate the number of individuals in the infected population that are asymptomatic (not diagnosed, but possible transmitters of the disease), based on the number of infected individuals (already diagnosed). We showed how with data (numbers of symptomatic, symptomatic in the hospital and deceased) on the evolution of the pandemic in five regions of mainland Portugal it is possible to estimate the number of asymptomatic and immune individuals in the population.por
dc.identifier.authoremailmmo@uevora.pt
dc.identifier.authoremailjesg@uevora.pt
dc.identifier.authoremaillgrilo@ipt.pt
dc.identifier.authoremailnd
dc.identifier.authoremailjtm@fct.unl.pt
dc.identifier.citationGrilo, Luís M, Oliveira, Manuela, Garção, Eugénio, Mexia, João T. "An innovative approach to estimate infection by COVID-19" in 20th International Conference of Numerical Analysis and Applied Mathematics (ICNAAM 2022). 18-25 September 2022, Crete (Greece).por
dc.identifier.scientificarea335por
dc.identifier.urihttps://icnaam.org
dc.identifier.urihttps://drive.google.com/file/d/1pBVsPAlJ4sVwMQZzsRI8-QFPAHaAN7tX/view
dc.identifier.urihttp://hdl.handle.net/10174/32926
dc.identifier.withinvitedoralpresentationnaopor
dc.identifier.withoralpresentationsimpor
dc.identifier.withposternaopor
dc.language.isoengpor
dc.rightsrestrictedAccesspor
dc.titleAn innovative approach to estimate infection by COVID-19por
dc.typelecturepor

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