OBJECTIVES: Aim of the present paper is the study of the large unreported component, characterizing the SARS-CoV-2 epidemic event in Italy, taking advantage of the Istat survey. Particular attention is devoted to the sensitivity and specificity of the serological test and their effects. METHODS: The model satisfactory reproduces the data of the Italian survey showing a relevant predictive power and relegating in a secondary position models which do not include, in the simulation, the presence of asymptomatic groups. The corrections due to the serological test sensitivity (in particular those ones depending on the symptoms onset) are crucial for a realistic analysis of the unreported (and asymptomatic) components. RESULTS: The relevant presence of an unreported component during the second pandemic wave in Italy is confirmed and the ratio of reported to unreported cases is predicted to be roughly 1:4 in the last months of year 2020. A method to correct the serological data on the basis of the antibody sensitivity is suggested and systematically applied. The asymptomatic component is also studied in some detail and its amount quantified. A model analyses of the vaccination scenarios is performed confirming the relevance of a massive campaign (at least 80000 immunized per day) during the first six months of the year 2021, to obtain important immunization effects within August/September 2021. © 2021 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Modelling SARS-CoV-2 unreported cases in Italy: Analysis of serological survey and vaccination scenarios / Traini, Marco Claudio; Caponi, Carla; Ferrari, Riccardo; De Socio, Giuseppe Vittorio. - In: INFECTIOUS DISEASE MODELLING. - ISSN 2468-0427. - STAMPA. - 2021:6(2021), pp. 909-923. [10.1016/j.idm.2021.06.002]

Modelling SARS-CoV-2 unreported cases in Italy: Analysis of serological survey and vaccination scenarios

Traini, Marco Claudio;
2021-01-01

Abstract

OBJECTIVES: Aim of the present paper is the study of the large unreported component, characterizing the SARS-CoV-2 epidemic event in Italy, taking advantage of the Istat survey. Particular attention is devoted to the sensitivity and specificity of the serological test and their effects. METHODS: The model satisfactory reproduces the data of the Italian survey showing a relevant predictive power and relegating in a secondary position models which do not include, in the simulation, the presence of asymptomatic groups. The corrections due to the serological test sensitivity (in particular those ones depending on the symptoms onset) are crucial for a realistic analysis of the unreported (and asymptomatic) components. RESULTS: The relevant presence of an unreported component during the second pandemic wave in Italy is confirmed and the ratio of reported to unreported cases is predicted to be roughly 1:4 in the last months of year 2020. A method to correct the serological data on the basis of the antibody sensitivity is suggested and systematically applied. The asymptomatic component is also studied in some detail and its amount quantified. A model analyses of the vaccination scenarios is performed confirming the relevance of a massive campaign (at least 80000 immunized per day) during the first six months of the year 2021, to obtain important immunization effects within August/September 2021. © 2021 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
2021
6
Traini, Marco Claudio; Caponi, Carla; Ferrari, Riccardo; De Socio, Giuseppe Vittorio
Modelling SARS-CoV-2 unreported cases in Italy: Analysis of serological survey and vaccination scenarios / Traini, Marco Claudio; Caponi, Carla; Ferrari, Riccardo; De Socio, Giuseppe Vittorio. - In: INFECTIOUS DISEASE MODELLING. - ISSN 2468-0427. - STAMPA. - 2021:6(2021), pp. 909-923. [10.1016/j.idm.2021.06.002]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/312830
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