Major disease outbreaks often generate multiple modeling efforts to assist with forecasting and management. Uncertainty about appropriate parameters, model structure and management intervention implementation can generate significant disagreements, which in turns hampers policy-making for animal and public health. Using examples from human and livestock diseases, I outline approaches to address uncertainty and learning to help improve epidemiological management outcomes.