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We apply the model to retrospectively evaluate U.S. blood safety policies for Zika and West Nile virus for the years 2017, 2018, and 2019, defining donor groups based on season and geography. We leverage structural properties to efficiently find an optimal solution. We find that the optimal portfolio varies geographically, seasonally, and over time. Additionally, we show that for this problem the approximated model yields the same optimal solution as the exact model. Our method enables systematic identification of the optimal blood safety portfolio in any s
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