  In modern life insurance, Markov processes in continuous time on a finite or
at least countable state space have been over the years an important tool for
the modelling of the states of an insured. Motivated by applications in
disability insurance, we propose in this paper a model for insurance states
based on Markov jump processes with more general state spaces. We use this
model to derive a new type of Thiele's differential equation which e.g. allows
for a consistent calculation of reserves in disability insurance based on
two-parameter continuous time rehabilitation rates.
