The role of uncertainty in infectious disease modelling

The study found that many models provided only cursory reference to the uncertainties of the information and data, or the parameters used Research by scientists at the University of Liverpool has found that greater consideration of the limitations and uncertainties in infectious disease modelling would improve its usefulness and value. Infectious disease dynamical modelling plays a central role in planning for outbreaks of human and livestock diseases. They forecast how they might progress and inform policy responses. Informing policy decisions Modelling is commissioned by governments or may be developed independently by researchers. It has been used to inform policy decisions for human and animal diseases such as SARS, H1N1 swine influenza, foot-and-mouth disease and is being used to inform action in the campaign to control bovine TB. In a study published in PLOS One, researchers analysed scientific papers, s, policies, reports and outcomes of previous infectious disease outbreaks in the UK to ascertain the role uncertainties played in previous models, and how these were understood by both the designers of the model and the users of the model. "Whilst it isn't possible to calculate the level of uncertainty, a better understanding and communication of the model's limitations is needed and could lead to better policy” - They found that many models  provided only cursory reference to the uncertainties of the information and data or the parameters used.