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. 2021 Nov 2;54(15):263–268. doi: 10.1016/j.ifacol.2021.10.266

A SIAT3HE model of the COVID-19 pandemic in Bergamo, Italy

Marco Polver ⁎, Fabio Previdi ⁎, Mirko Mazzoleni ⁎, Alberto Zucchi ⁎⁎
PMCID: PMC8562130  PMID: 38620938

Abstract

The aim of this article is to give a better understanding of the dynamics of the SARS-CoV-2 pandemic in the Bergamo province (Italy), one of the most hit areas of the world, between February and April 2020. A new compartmental model, called SIAT3HE, was designed and fitted on accurate data about the pandemic provided by ATS Bergamo, the health protection agency of the Bergamo province. Our results show that SARS-CoV-2 reached Bergamo in January and infected 318,000 people, the 28.8% of the province population. The 43.1% of the infected individuals stayed asymptomatic. As 6,028 people died due to COVID-19 till April 30th, the infection fatality ratio of SARS-CoV-2 in the Bergamo province was 1.9%. These results are in very good agreement with available information: the number of infections is consistent with the results of recent serological surveys and the number of deaths due to COVID-19 is close to the excess mortality of the considered period.

Keywords: Healthcare management, Nonlinear system identification, System identification, validation, Compartmental models, COVID-19

References

  1. Backer J. Incubation period of 2019 novel coronavirus (2019-nCoV) infections among travellers from Wuhan, China, 20-28 January 2020. Eurosurveil-lance. 2020:25. doi: 10.2807/1560-7917.ES.2020.25.5.2000062. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Buonanno P., Galletta S., Puca M. Estimating the severity of COVID-19: Evidence from the Italian epicenter. Plos one. 2020;15(10):e0239569. doi: 10.1371/journal.pone.0239569. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Calafiore, G.C. et al. (2020). A modified SIR model for the COVID-19 contagion in Italy. arXiv preprint arXiv:2003.14391.
  4. Casella F. Can the COVID-19 epidemic be controlled on the basis of daily test reports? IEEE Control Systems Letters. 2020;5(3):1079–1084. [Google Scholar]
  5. Cereda, D. et al. (2020). The early phase of the COVID-19 outbreak in Lombardy, Italy.
  6. Dipartimento della Protezione Civile (2020). Dati COVID-19 Italia.
  7. Giordano G. Modelling the COVID-19 epidemic and implementation of population-wide interventions in Italy. Nature Medicine. 2020:1–6. doi: 10.1038/s41591-020-0883-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Hethcote H.W. The mathematics of infectious diseases. SIAM review. 2000;42(4):599–653. [Google Scholar]
  9. ISTAT (2020). Decessi anni 2015-2020.
  10. Lavezzo E. Suppression of a SARS-CoV-2 outbreak in the Italian municipality of Vo’. Nature. 2020;584(7821):425–429. doi: 10.1038/s41586-020-2488-1. [DOI] [PubMed] [Google Scholar]
  11. Perico L. COVID-19 and Lombardy: Testing the impact of the first wave of the pandemic. EBioMedicine. 2020;61:103069. doi: 10.1016/j.ebiom.2020.103069. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Qian G. COVID-19 Transmission Within a Family Cluster by Presymptomatic Carriers in China. Clinical Infectious Diseases. 2020;71(15):861–862. doi: 10.1093/cid/ciaa316. [DOI] [PMC free article] [PubMed] [Google Scholar]

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