Modelling fatality curves of COVID-19 and the effectiveness of intervention strategies

Giovani L. Vasconcelos; Antônio M. S. Macêdo; Raydonal Ospina; Francisco A. G. Almeida; Gerson C. Duarte-Filho; Inês C. L. Souza

In Fig. 1(a) we show the cumulative number of deaths (red circles) attributed to COVID-19 for China, superimposed with the statistical fit of the RGM curve (black solid line), with the respective parameters shown in the inset of the figure. One sees from the figure that the fatality curve in this case, where the epidemic has apparently leveled off, is well adjusted by the RGM formula. This indicates that the evolution of the number of deaths in the COVID-19 epidemic can be effectively described with a dynamical model such as the Richards model. In Fig. 1(b) we show the cumulative deaths for Italy together with the respective RGM fit. Here again the RGM seems to be able to provide a reasonably good fit to the data. In this case, owing to the unavoidable incompleteness of the data, as the epidemics is still ongoing, there is considerably larger uncertainty in the parameters, particularly in the parameter K which represents an estimate of the total numbers of fatalities at the end of the epidemics.