  In this paper we consider robust models for emergency staff deployment in the
event of a flu pandemic. We focus on managing critical staff levels at
organizations that must remain operational during such an event, and develop
methodologies for managing emergency resources with the goal of minimizing the
impact of the pandemic. We present numerical experiments using realistic data
to study the effectiveness of our approach.
  The underlying methodology is that of robust optimization; we model the
problem as an infinite linear program which is approximately solved using a
variant of Benders decomposition.
