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Pandemic decision support: mathematical modelling, uncertainty, and serviceable truths
During the COVID-19 pandemic, applied mathematicians across Canada completed modelling to support public health decisions. Predictions had high uncertainty, but were also urgently needed to inform decisions with substantial consequences. I will discuss our modelling to support the public health response to COVID-19 in Newfoundland and Labrador, and reflect on the characteristics of models that might best support decision-makers. I will highlight recent discussions describing the future of infectious disease modelling in Canada. This includes modelling to reach ‘serviceable truths’: truths that are both supported by scientific evidence, and correspond to decisions that are acceptable to the people.