One month after the outbreak in Italy the situation remains complicated. Despite the high number of performed swabs as compared to the confirmed cases, the epidemic has been growing with a very high rate. COVID-19 is proving to have a high capacity for infection, probably reinforced by asymptomatic people, who represent a real danger for elderly and fragile individuals. In particular, the disease is showing to be lethal for the elderly (95.2% in patients aged ≥ 60) and men (70.8%) [14]. On the date we finalized this article (30 March 2020), the trend of daily distribution of confirmed cases seems to show an initial decline of the growth of the epidemic. However, the total number of confirmed cases already exceeds those that occurred in China. In addition to this, many individuals died without the possibility of checking if they were actually infected and therefore not recorded as such. The data related to the patients categories give us an estimate of the epidemic in terms of cases that can be treated at home, those who need hospitalization, and the mortality. In general, through the Italian epidemiological findings, countries with similar characteristics to those present in Italy (demographic characteristics of the population, health structures, etc.), should take earlier restrictive measures and arrange the necessary treatments for potential patients.
The forecast model in real-time indicates a total number of national cases greater than 120,000 patients, with a figure of approximately 50,000 in Lombardy only. In addition, duration of the epidemic was estimated of 2 months about. Since the theoretical cumulative curve has an asymptotic pattern (i.e. the maximum value is achieved for the t time towards infinite), considering 99% of the time from the beginning of the outbreak is a convention. Therefore, if instead of 99% of time we considered 99.9%, the overall number of days estimated for the epidemic to come to an end increases by 20% (i.e. ten more days need to be added to the calculation of time). Moreover, several factors could affect the total number of cases and the duration of the epidemic. For example, a contribution to the spread of outbreaks in southern Italy was caused by the movement of students and workers from Northern to Southern Italy following the first governmental restrictions. On the other hand, more stringent restrictions imposed later on by the Government could lower the expected number of total cases and reduce the number of days towards the end of the epidemic. On this specific topic, a previous study on SARS-CoV-2 in China found a nonlinear and chaotic behavior of the virus, which emerged gradually but was highly responsive to massive interventions [15]. Another important factor is related to possible mutations of the novel Coronavirus [16], which could have a positive or negative outcome on the trend of the pandemic.
It is also necessary to consider the intrinsic limitations of this study. First of all, data was not always updated on a daily basis by each Regional Authority (an extract of the warnings list provided from Civil Protection is reported in the supplementary materials, Table SM 1). This limitation can have effects on the trend of the epidemiological curve, therefore on the fit of the data. Another limitation is represented of the reported cumulative counts, that are known be under-reported, especially at the beginning of the pandemic due to public awareness. If the counts are under-reported in the beginning of pandemic, all reported accumulated counts would be all under-estimated. We also have to consider that the number of infected people is underestimated, since there are many undetected asymptomatic individuals. These individuals can unknowingly infect several other persons contributing to the spread of the epidemic. More specifically, in Italy 5.9% of individuals who had a check through a swab were diagnosed as asymptomatic and 12.9% were considered people with non-specific symptoms [14]. These percentages could to be underestimated, because swabs have not performed on the majority of the population. Finally, the factors that determine the trend of the epidemic curve could change without respecting the symmetry of the forecasted model. In fact, the populations’ growth is exponential-like at the beginning (as also verified in [17]), but toward the end it flattens due to saturation. Likely, the tail-end of the logistic curve will be governed by the quarantined population and the consequent social distancing. In fact, in Italy will be supposedly infected few hundreds of thousands of people (considering also the asymptomatic subjects), therefore will be no immunity of the population (in Italy there are about 60 million of citizens), but the end of the epidemic will be due to the virus dying out.
Aware of what is happening in Italy, the other countries of the European Union should adopt agreed measures regarding health and economic aids, and also regulate uniformly the movement of people among the member States, to avoid a new spread of the SARS-CoV-2. The pandemic due to novel Coronavirus is the first in the globalization era, and the lesson about what is happening must be a warning for all countries worldwide, regarding a rapid and complete dissemination of information, surveillance, health organization, and cooperation among the states.