  We propose a simple model of spreading of some infection in an originally
healthy population which is different from other models existing in the
literature. In particular, we use an operator technique which allows us to
describe in a natural way the possible interactions between healthy and
un-healthy populations, and their transformation into recovered and to dead
people. After a rather general discussion, we apply our method to the analysis
of Chinese data for the SARS-2003 (Severe acute respiratory syndrome;
SARS-CoV-1) and the Coronavirus COVID-19 (Corona Virus Disease; SARS-CoV-2 )
and we show that the model works very well in reproducing the long-time
behaviour of the disease, and in particular in finding the number of affected
and dead people in the limit of large time. Moreover, we show how the model can
be easily modified to consider some lockdown measure, and we deduce that this
procedure drastically reduces the asymptotic value of infected individuals, as
expected, and observed in real life.
