The ABS runs Australia-wide population surveys using area-based multi-stage designs. One challenge for the ABS and other National Statistical Organizations is to avoid returning to areas selected in other recent surveys so that households are not overburdened with multiple surveys, while ensuring areas have the correct unconditional probabilities of selection for the survey to represent all of the country. There is a well-known method to choose primary-stage units in a way that minimizes overlap and leaves the unconditional probabilities of selection unchanged. However, this method cannot simply be applied when the primary-stage units in the current survey are geographically di erent from those used in previous surveys. We develop two extensions to the existing approach for an ABS household survey facing this challenge. The first method uses simulations as part of computing conditional probabilities of selection, while the second uses a weighted average of conditional probabilities applied on the geographic intersections of the previous and current primary-stage units. We show that both methods preserve the unconditional probability of selection, but do not achieve the same levels of overlap.