  For general penalized Markov processes with soft killing, we propose a simple
criterion ensuring uniform convergence of conditional distributions in
Wasserstein distance to a unique quasi-stationary distribution. We give several
examples of application where our criterion can be checked, including Bernoulli
convolutions and piecewise deterministic Markov processes of the form of
switched dynamical systems, for which convergence in total variation is not
possible.
