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This research focuses on improving influenza forecast accuracy through refined allocation methods, despite challenges posed by sparse data. Utilizing data from MUSC, Prisma, and CDC, the study employs a Rate-by-Test framework to forecast 0-3 weeks ahead, validated using metrics like PA, MAE, and RMSE. Results indicate strong regional predictive accuracy and effective method validation, with visual analyses through line charts and heatmaps. Conclusions affirm reliable regional allocations and...