In early 2020, it emerged in Italy a large outbreak of Covid-19, the infectious disease caused by severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2). In this context, producing as accurate as possible forecasting models was crucial both for the containment of the epidemic and for the planning of effective policy interventions. In this article I describe the main data sources which have been used to monitor the spread of the Covid-19 virus diffusion in Italy in the early stages of the epidemic (i.e. spring 2020); I focus on administrative records, Big Data from online search engines, and survey data, including data on contagion, fatalities, and Intensive Care Units admissions and exits. I discuss data quality issues associated with these sources of data, and I comment the main challenges faced in the dissemination of data and research findings in the first stages of the epidemic.
Gaia, A. (2021). COVID-19 virus diffusion in Italy: data quality and methodological challenges. RASSEGNA ITALIANA DI SOCIOLOGIA, 62(1), 11-37 [10.1423/100620].
|Citazione:||Gaia, A. (2021). COVID-19 virus diffusion in Italy: data quality and methodological challenges. RASSEGNA ITALIANA DI SOCIOLOGIA, 62(1), 11-37 [10.1423/100620].|
|Tipo:||Articolo in rivista - Articolo scientifico|
|Carattere della pubblicazione:||Scientifica|
|Presenza di un coautore afferente ad Istituzioni straniere:||No|
|Titolo:||COVID-19 virus diffusion in Italy: data quality and methodological challenges|
GAIA, ALESSANDRA (Corresponding)
|Data di pubblicazione:||2021|
|Rivista:||RASSEGNA ITALIANA DI SOCIOLOGIA|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.1423/100620|
|Appare nelle tipologie:||01 - Articolo su rivista|