Mathematical modeling and adaptive control to inform real time decision making for the COVID-19 pandemic at the local, regional and national scale

全球目前正受到冠状病毒疾病（COVID-19）大流行的破坏，截至撰写本文时，全球已导致近100万例确诊感染病例和约50，000人死亡。全球约有三分之一的人口受到某种形式的限制--造成巨大的经济负担--对许多国家来说，焦点已经转向如何规划一个“退出策略”，从世界上有史以来最严厉的一些社交距离措施中退出。这个项目将使用英国COVID-19爆发的真实的时间数据来提供可靠的预测，衡量模型预测未来流行病行为的能力。我们将研究在疫情爆发期间，随着更多信息的可用，我们的短期和长期预测如何变化，这如何影响应该采取的适当控制措施的预测，以及何时以及如何放松这些政策。最后，考虑到未来感染浪潮的可能性，我们将使用我们的模型来确定应实施的最佳适应性控制政策，以减少COVID-19爆发导致的死亡人数，并将对卫生服务的影响降至最低。

The world is currently being devastated by a pandemic of coronavirus disease (COVID-19) which, at the time of writing, has resulted in almost 1 million confirmed cases of infection and around 50,000 deaths worldwide. Around one third of the global population are under some form of restriction - causing huge economic burdens - and for many countries, focus has turned to how planning an "exit strategy" from some of the most severe social distancing measures that the world has ever seen.This project will use real time data on the UK COVID-19 outbreak to provide robust predictions, guaging the ability of a model to predict future epidemic behaviour. We will investigate how our short- and long-term predictions change during an outbreak as more information becomes available, how this may effect forecasts of the appropriate control measures that should be introduced and when and how such policies should be relaxed. Finally, taking into account the potential for future waves of infection, we will use our model to determine optimal adaptive control policies that should be implemented to reduce the number of deaths as a result of the COVID-19 outbreak and to minimise the impact on the health service.