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Dataset . 2022
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Dataset . 2022
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ZENODO
Dataset . 2022
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Italian COVID-19 Integrated Surveillance Dataset (v42.0.0)

Authors: Monticone, Pietro; Moroni, Claudio;

Italian COVID-19 Integrated Surveillance Dataset (v42.0.0)

Abstract

Abstract COVID-19 integrated surveillance data provided by the Italian National Institute of Health and processed via UnrollingAverages.jl to deconvolve the weekly simple moving averages. Overview Every week the National Institute for Nuclear Physics (INFN) imports an anonymous individual-level dataset from the Italian National Institute of Health (ISS) and converts it into an incidence time series data organized by date of event and disaggregated by sex, age and administrative level with a consolidation period of approximately two weeks. The information available to the INFN is summarised in the following meta-table. Output Data The output data has been stored here and contain the following information: Reconstructed daily time series of confirmed cases by date of diagnosis stratified by sex and age at the regional level; Reconstructed daily time series of symptomatic cases by date of symptoms onset stratified by sex and age at the regional level; Reconstructed daily time series of ordinary hospital admissions by date of admission stratified by sex and age at the regional level; Reconstructed daily time series of intensive hospital admissions by date of admission stratified by sex and age at the regional level; Reconstructed daily time series of deceased cases by date of death stratified by sex and age at the regional level.

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Keywords

Data, Surveillance, Epidemiology, SARS-CoV-2, Scenario Analysis, COVID-19, Time Series, Nowcasting, Modelling, Forecasting

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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