Understanding the dynamics and drivers of the COVID-2019 epidemic using real-time outbreak analytics

点击翻译按钮获取中文摘要

Tracking and predicting an epidemic can help tailor public health measures so that werespond quickly and appropriately to evolving threats. We will fit statistical models toemerging data to monitor key epidemiological and clinical parameters related totransmissibility and severity, and their likely impact on health services. Mathematicalmodels will be fitted to surveillance data to forecast future cases and hospitalisations andevaluate the impact of different public health policies. Importantly, we will also measurepeople’s behaviour over time to detect changes in response to the epidemic, assessingwhat measures they take to reduce risk and where they get their evidence from. Thisinformation will be used to refine our models and improve epidemiological forecasting. Itwill also allow public health authorities to tailor their messaging to ensure that peoplerespond appropriately to changes in risk. The information that we generate, either fromour analyses of the emerging data, epidemic forecasts, or from our panel of respondents,will be rapidly summarised and shared on easy-to-use websites so that scientists, healthworkers and the public can be best informed about the threats posed by COVID-19 andthe efficacy of different measures to reduce risk.