Role of mathematical modelling in future pandemic response policy

Key messagesMathematical modelling is intrinsically difficult given the complexity of relationships between parameters and difficulty quantifying those parametersModelling needs input from a much wider range of sources including domain expertsData sharing and communication of results could be improved Policy makers and the public often had poor understanding of key concepts such as exponential growth and the limitations of long-term forecastingMathematical modelling underpinned much of the advice that the Scientific Advisory Group for Emergencies (SAGE) and others provided to the UK government during the pandemic. It should therefore be a focus of the UK covid inquiry’s examination of how and why decisions were made.1 Much of the modelling came from the Scientific Pandemic Influenza Group on Modelling (SPI-M), which gives expert advice to the Department of Health and Social Care and the wider UK government on emerging human infectious disease threats. Its members come from a range of UK institutions and…
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