Confronting COVID-19: Surging critical care capacity in Italy

Jose Manuel Rodriguez Llanes; Rafael Castro Delgado; Morten Gram Pedersen; Pedro Arcos Gonzalez; Matteo Meneghini

The second set of approaches is promoted by SIRS models, which scientists feed with the available information on the characteristics of the epidemic, disease course and epidemiology (for example numbers of infected and seeking care, hospitalization bed rates, UCI admission rates) and government and civic measures adopted. The main limitation of these models is that they rely on a sequence of equations based on best available numbers (20) . As shown earlier, some of these numbers proved to be very incorrect and can have a vast impact on calculations and predictions. While we applaud these efforts to provide a range of policy options and their consequences on health and demand for critical care, such an undertake also includes large uncertainty in the numbers produced. The authors reported that certain policy options were robust to model uncertainty derived from potential variability in essential parameters such as the severity of the virus as captured by the proportion of cases requiring ICU admission or the basic reproduction number R0 (20) . Other studies show how vast these uncertainties can be, for the mere prediction of the course of this epidemic (21) .