  We study the problem of intervention effects generating various types of
outliers in an integer-valued autoregressive model with Poisson innovations. We
concentrate on outliers which enter the dynamics and can be seen as effects of
extraordinary events. We consider three different scenarios, namely the
detection of an intervention effect of a known type at a known time, the
detection of an intervention effect of unknown type at a known time and the
detection of an intervention effect when both the type and the time are
unknown. We develop F-tests and score tests for the first scenario. For the
second and third scenarios we rely on the maximum of the different F-type or
score statistics. The usefulness of the proposed approach is illustrated using
monthly data on human brucellosis infections in Greece.
