  We introduce a mathematical description of the impact of sociality in the
spread of infectious diseases by integrating an epidemiological dynamics with a
kinetic modeling of population-based contacts. The kinetic description leads to
study the evolution over time of Boltzmann-type equations describing the number
densities of social contacts of susceptible, infected and recovered
individuals, whose proportions are driven by a classical SIR-type compartmental
model in epidemiology. Explicit calculations show that the spread of the
disease is closely related to moments of the contact distribution. Furthermore,
the kinetic model allows to clarify how a selective control can be assumed to
achieve a minimal lockdown strategy by only reducing individuals undergoing a
very large number of daily contacts. We conduct numerical simulations which
confirm the ability of the model to describe different phenomena characteristic
of the rapid spread of an epidemic. Motivated by the COVID-19 pandemic, a last
part is dedicated to fit numerical solutions of the proposed model with
infection data coming from different European countries.
