The COVID-19 Infection in Italy: A Statistical Study of an Abnormally Severe Disease

Anno: 2020

Autori: De Natale G., Ricciardi V., De Luca G., De Natale D., Di Meglio G., Ferragamo A., Marchitelli V., Piccolo A., Scala A., Somma R., Spina E., Troise C.

Affiliazione autori: ‎INGV, Osservatorio Vesuviano, I-80124 Naples, Italy;‎ CNR, INO, I-80078 Pozzuoli, Italy;‎ Univ Campania L Vanvitelli, Dipartimento Med Sperimentale, I-80138 Naples, Italy;‎ Ist Nazl Fis Nucl, Sez Napoli, I-80126 Naples, Italy; Univ Zurich, Dept Phys, CH-8057 Zurich, Switzerland; CoronaVerus, I-80136 Naples, Italy;‎ Puglia Reg Govt, Env, Dept Mobil, Publ Works,Ecol, I-70100 Bari, Italy;‎ Univ Napoli Federico II, Dept Phys Ettore Pancini, I-80126 Naples, Italy;‎ CNR, IRISS, I-80134 Naples, Italy;‎ Univ Napoli Federico II, Dept Neurosci Reprod & Odontostomatol, I-80131 Naples, Italy

Abstract: We statistically investigate the Coronavirus Disease 19 (COVID-19) pandemic, which became particularly invasive in Italy in March 2020. We show that the high apparent lethality or case fatality ratio (CFR) observed in Italy, as compared with other countries, is likely biased by a strong underestimation of the number of infection cases. To give a more realistic estimate of the lethality of COVID-19, we use the actual (March 2020) estimates of the infection fatality ratio (IFR) of the pandemic based on the minimum observed CFR and analyze data obtained from the Diamond Princess cruise ship, a good representation of a “laboratory” case-study from an isolated system in which all the people have been tested. From such analyses, we derive more realistic estimates of the real extent of the infection as well as more accurate indicators of how fast the infection propagates. We then isolate the dominant factors causing the abnormal severity of the disease in Italy. Finally, we use the death count-the only data estimated to be reliable enough-to predict the total number of people infected and the interval of time when the infection in Italy could end.


Volume: 9 (5)      Da Pagina: 1564  A: 1564

Parole chiavi: COVID-19; epidemic in Italy; statistical forecast
DOI: 10.3390/jcm9051564

Citazioni: 30
dati da “WEB OF SCIENCE” (of Thomson Reuters) aggiornati al: 2022-05-22
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