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Cited by 1,740COVID-19 epidemiological studiesMathematical and Theoretical Epidemiology and Ecology ModelsCOVID-19 Prevention and Impact

Modelling the COVID-19 epidemic and implementation of population-wide interventions in Italy

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Giordano, Giulia, Blanchini, Franco, Bruno, Raffaele, Colaneri, Patrizio, Di Filippo, Alessandro, Di Matteo, Angela, Colaneri, Marta·2020·Nature Medicine
DOI 10.1038/s41591-020-0883-7PMC PMC7175834
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Abstract

In Italy, 128,948 confirmed cases and 15,887 deaths of people who tested positive for SARS-CoV-2 were registered as of 5 April 2020. Ending the global SARS-CoV-2 pandemic requires implementation of multiple population-wide strategies, including social distancing, testing and contact tracing. We propose a new model that predicts the course of the epidemic to help plan an effective control strategy. The model considers eight stages of infection: susceptible (S), infected (I), diagnosed (D), ailing (A), recognized (R), threatened (T), healed (H) and extinct (E), collectively termed SIDARTHE. Our SIDARTHE model discriminates between infected individuals depending on whether they have been diagnosed and on the severity of their symptoms. The distinction between diagnosed and non-diagnosed individuals is important because the former are typically isolated and hence less likely to spread the infection. This delineation also helps to explain misperceptions of the case fatality rate and of the epidemic spread. We compare simulation results with real data on the COVID-19 epidemic in Italy, and we model possible scenarios of implementation of countermeasures. Our results demonstrate that restrictive social-distancing measures will need to be combined with widespread testing and contact tracing to end the ongoing COVID-19 pandemic.

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Cited by

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Authors
Giordano, G., Blanchini, F., Bruno, R., Colaneri, P., Di Filippo, A., Di Matteo, A., & Colaneri, M.
Affiliations
  • University of Trento (IT)
  • University of Udine (IT)
  • University of Pavia (IT)
  • Institute of Electronics, Computer and Telecommunication Engineering (IT)
  • Policlinico San Matteo Fondazione (IT)
Corresponding author
Giordano, Giulia
ORCID
Venue
Nature Medicine
Publisher
Springer Science and Business Media LLC
Published
2020-04-22
Volume
26
Issue
6
Pages
855-860
ISSN
  • 1078-8956 (ISSN-L)
  • 1546-170X
DOI
10.1038/s41591-020-0883-7
PMC
PMC7175834
OpenAlex
W3018782651
Cited by
1,740
References
2
Citations by year
2026: 38 · 2025: 88 · 2024: 112 · 2023: 178 · 2022: 318 · 2021: 562 · 2020: 443 · 2017: 1
FWCI
59.66
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Medicine (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • Virtual Community of Pathological Anatomy (University of Castilla La Mancha) (submittedVersion, other-oa)
  • Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano) (submittedVersion, other-oa)
  • Institutional Research Information System (University of Udine) (submittedVersion)
  • Iris (University of Trento) (submittedVersion)
  • arXiv (Cornell University)
Funders
Ministero dell‘Istruzione, dell’Università e della Ricerca (PRIN 2017YKXYXJ)
Topics
  • Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Mathematical and Theoretical Epidemiology and Ecology Models
  • Social Sciences › Sociology and Political Science › COVID-19 Prevention and Impact
Keywords
COVID-19 pandemic, SARS-CoV-2, epidemic modeling, social distancing, case fatality rate, infection stage, epidemic control measures, Italy
MeSH terms
Betacoronavirus, COVID-19, SARS-CoV-2, Computer Simulation, Female, Humans, Italy, Male, Pneumonia, Viral, Quarantine, Coronavirus Infections, Pandemics

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