  Italy, particularly the Lombardy region, was among the first countries
outside of Asia to report cases of COVID-19. The emergency medical service
called Regional Emergency Agency (AREU) coordinates the intra- and
inter-regional non-hospital emergency network and the European emergency number
service in Lombardy. AREU must deal with daily and seasonal variations of call
volume. The number and type of emergency calls changed dramatically during the
COVID-19 pandemic. A model to predict incoming calls and how many of these turn
into events, i.e., dispatch of transport and equipment until the rescue is
completed, was developed to address the emergency period. We used the
generalized additive model with a negative binomial family to predict the
number of events one, two, five, and seven days ahead. The over-dispersion of
the data was tackled by using the negative binomial family and the nonlinear
relationship between the number of events and covariates (e.g., seasonal
effects) by smoothing splines. The model coefficients show the effect of
variables, e.g., the day of the week, on the number of events and how these
effects change during the pre-COVID-19 period. The proposed model returns
reasonable mean absolute errors for most of the 2020-2021 period.
