0000000000323050

AUTHOR

Giovanna Jona-lasinio

showing 4 related works from this author

Estimating COVID-19-induced Excess Mortality in Lombardy

2021

AbstractWe compare the expected all-cause mortality with the observed one for different age classes during the pandemic in Lombardy, which was the epicenter of the epidemic in Italy and still is the region most affected by the pandemic. A generalized linear mixed model is introduced to model weekly mortality from 2011 to 2019, taking into account seasonal patterns and year-specific trends. Based on the 2019 year-specific conditional best linear unbiased predictions, a significant excess of mortality is estimated in 2020, leading to approximately 35000 more deaths than expected, mainly arising during the first wave. In 2021, instead, the excess mortality is not significantly different from z…

Excess mortality2019-20 coronavirus outbreakCoronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)PandemicStatisticsBiologyGeneralized linear mixed model
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Unreliable predictions about COVID‐19 infections and hospitalizations make people worry: The case of Italy

2021

Computer modeling &ltmedicine.medical_specialty2019-20 coronavirus outbreakCoronavirus disease 2019 (COVID-19)BioinformaticsSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)media_common.quotation_subjectcomputer modeling < biostatistics & bioinformatics; epidemiology; statistical inference < biostatistics & bioinformaticsMEDLINEVirologycomputer modeling < biostatistics & bioinformaticsEpidemiologyHumansMedicineLetters to the EditorIntensive care medicineLetter to the Editormedia_commonSARS-CoV-2business.industryCommunicationBiostatistics &ampCOVID-19Computer modeling &lt; Biostatistics &amp; Bioinformaticsstatistical inference < biostatistics & bioinformaticsVirologyInfectious DiseasesItalyStatistical inference &lt; Biostatistics &amp; BioinformaticsepidemiologyWorrySettore SECS-S/01businessForecastingJournal of Medical Virology
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Estimating COVID-19-induced Excess Mortality in Lombardy, Italy.

2022

We compare the expected all-cause mortality with the observed one for different age classes during the pandemic in Lombardy, which was the epicenter of the epidemic in Italy. The first case in Italy was found in Lombardy in early 2020, and the first wave was mainly centered in Lombardy. The other three waves, in Autumn 2020, March 2021 and Summer 2021 are also characterized by a high number of cases in absolute terms. A generalized linear mixed model is introduced to model weekly mortality from 2011 to 2019, taking into account seasonal patterns and year-specific trends. Based on the 2019 year-specific conditional best linear unbiased predictions, a significant excess of mortality is estima…

AgingSurveillanceSARS-CoV-2Short CommunicationCOVID-19Excess mortalityAll-cause mortalitySettore MED/01 - Statistica MedicaItalyAll-cause mortality; COVID-19; Excess mortality; Surveillance; Humans; Italy; Linear Models; Mortality; Pandemics; SARS-CoV-2; COVID-19Linear ModelsHumansGeriatrics and GerontologyMortalitySettore SECS-S/01Settore SECS-S/01 - StatisticaPandemics
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An ensemble approach to short-term forecast of COVID-19 intensive care occupancy in Italian Regions

2020

Abstract The availability of intensive care beds during the COVID‐19 epidemic is crucial to guarantee the best possible treatment to severely affected patients. In this work we show a simple strategy for short‐term prediction of COVID‐19 intensive care unit (ICU) beds, that has proved very effective during the Italian outbreak in February to May 2020. Our approach is based on an optimal ensemble of two simple methods: a generalized linear mixed regression model, which pools information over different areas, and an area‐specific nonstationary integer autoregressive methodology. Optimal weights are estimated using a leave‐last‐out rationale. The approach has been set up and validated during t…

FOS: Computer and information sciencesStatistics and ProbabilityTime FactorsOccupancyCoronavirus disease 2019 (COVID-19)Computer science01 natural sciencesGeneralized linear mixed modelSARS‐CoV‐2law.inventionclustered data; COVID-19; generalized linear mixed model; integer autoregressive; integer autoregressive model; panel data; SARS-CoV-2; weighted ensembleMethodology (stat.ME)panel data010104 statistics & probability03 medical and health sciences0302 clinical medicinelawCOVID‐19Intensive careEconometricsHumansclustered data030212 general & internal medicine0101 mathematicsPandemicsStatistics - MethodologySARS-CoV-2Reproducibility of ResultsCOVID-19General Medicineweighted ensembleIntensive care unitResearch PapersTerm (time)integer autoregressiveIntensive Care UnitsAutoregressive modelItalyNonlinear Dynamicsgeneralized linear mixed modelinteger autoregressive modelclustered data; COVID-19; generalized linear mixed model; integer autoregressive; integer autoregressive model; panel data; SARS-CoV-2; weighted ensemble; COVID-19; Humans; Intensive Care Units; Italy; Nonlinear Dynamics; Pandemics; Reproducibility of Results; Time Factors; ForecastingStatistics Probability and UncertaintySettore SECS-S/01Settore SECS-S/01 - StatisticaPanel dataResearch PaperForecasting
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