  The CDC Vaccine Safety Datalink project has pioneered the use of near
real-time post-market vaccine safety surveillance for the rapid detection of
adverse events. Doing weekly analyses, continuous sequential methods are used,
allowing investigators to evaluate the data near-continuously while still
maintaining the correct overall alpha level. With continuous sequential
monitoring, the null hypothesis may be rejected after only one or two adverse
events are observed. In this paper, we explore continuous sequential monitoring
when we do not allow the null to be rejected until a minimum number of observed
events have occurred. We also evaluate continuous sequential analysis with a
delayed start until a certain sample size has been attained. Tables with exact
critical values, statistical power and the average times to signal are
provided. We show that, with the first option, it is possible to both increase
the power and reduce the expected time to signal, while keeping the alpha level
the same. The second option is only useful if the start of the surveillance is
delayed for logistical reasons, when there is a group of data available at the
first analysis, followed by continuous or near-continuous monitoring
thereafter.
