One month after the outbreak in Italy the situation remains complicated. Despite the high number of performed swabs compared to the confirmed cases, the epidemic kept on growing at very speed. COVID-19 proved to have a high capacity for infection, probably reinforced by asymptomatic people, representing 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%) . 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 at this point in time. In addition to this, many deaths were not recorded as due to COVID-19 (there was no possibility of checking if the deceased had been infected) and therefore not recorded as such [19, 20]. The data related to the patient 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. The implications in terms of public health, workload in hospitals, and economic damage were worrisome. The hospital beds, in particular in intensive care, were saturated in several areas of Northern Italy [21,22,23], while the lockdown imposed from the Government to limit the infections has stopped almost all commercial activities in the whole country. 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 230,000 patients, with a figure of approximately 90,000 in Lombardy only. In addition, the model estimates the duration of the epidemic in approximately 4 months. Since the theoretical cumulative curve has an asymptotic pattern (i.e. the maximum value is achieved for the t time towards infinite), considering 100 new cases in a day as the end of the outbreak is a convention. Therefore, if we considered 50 new cases in a day instead of 100, then the overall timeline estimated for the epidemic to come to an end would increase by approximately 21 days. Instead, if we considered 200 new cases, then the timeline would decrease by approximately by 19 days.
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 . Another important factor is related to possible mutations of the novel Coronavirus , which could have a positive or negative outcome on the trend of the pandemic.
Considering what happened in Italy, other EU countries 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. As a matter of fact, the pandemic due to novel Coronavirus is the most widespread in the globalization era, and the lesson about what is happening must be a warning for all countries worldwide. A rapid and thorough dissemination of information, surveillance, optimization of health systems, and cooperation among states is needed in order to reduce contagion and economic damages.
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 accidentally 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 . Such percentages could be underestimated, since the majority of the population did not take a swab. Finally, the factors that determine the trend of the epidemic curve could change without respecting the pattern of the forecasted model. As a matter of fact, the infected population growth is exponential at the beginning (as also verified in ), but tends to flatten towards the end due to saturation. Likewise, the tail-end of the log-logistic curve will be governed by the quarantined population and the consequent social distancing. Ultimately, the epidemic could end either through immunization of individuals affected (herd immunity) or thanks to the extinction of the virus. Since the overall number of infected citizens did not reach the majority of the population (approximately 60 million), the end of the epidemic is expected to occur with the extinction of the virus.