  We give estimates of the distance between the densities of the laws of two
functionals $F$ and $G$ on the Wiener space in terms of the Malliavin-Sobolev
norm of $F-G.$ We actually consider a more general framework which allows one
to treat with similar (Malliavin type) methods functionals of a Poisson point
measure (solutions of jump type stochastic equations). We use the above
estimates in order to obtain a criterion which ensures that convergence in
distribution implies convergence in total variation distance; in particular, if
the functionals at hand are absolutely continuous, this implies convergence in
$L^{1}$ of the densities.
