Waves, Lock-Downs, and Vaccines - Decision Support and Model with Superb Geographical and Sociological Resolution

这项提议旨在进一步开发、验证和部署6月模型，以模拟新冠肺炎在英国的传播以及医疗和非医疗缓解战略的影响。最近构建的JUMP在其虚拟人口模型中结合了出色的地理和社会学分辨率，对日常活动进行了详细、灵活和可调整的模拟，并能够包括缓解战略和其他干预措施，以评估其效果。英国NHS已经使用JUMP来洞察疾病的性质及其传播的动力学，从而为行动计划和支持决策提供信息。在这个建议中，我们将1。继续为NHS、PHE和英国政府提供有价值的见解，例如进一步完全或部分封锁的影响、分级系统和可能的扩展和修改以及不同疫苗接种方案的影响。这尤其包括在可能的未来预测中应用用于不确定性量化的尖端贝叶斯方法，以及制定健全的数据同化协议以改进短期预测。进一步完善人口模型，特别强调少数群体的传播动态和条件，以及社会经济因素对感染率和死亡率的影响。我们还将包括同时影响人口的多种传染病的模型，以量化季节性流感对医疗保健系统的影响。作为副产品，我们将全面记录代码并制作方便的用户界面，以便于在未来的流行病中使用，从而使其成为持久的国家资产。

This proposal aims at further developing, validating, and deploying the JUNE model for the simulation of the spread of COVID-19 in the United Kingdom and the impact of medical and non-medical mitigation strategies. Recently constructed, JUNE combines superb geographical and sociological resolution in its virtual population model with a detailed, flexible and adjustable simulation of daily activities and the ability to include mitigation strategies and other interventions, to asses their effect. JUNE is already being used by NHS England to gain insights into the nature of the disease and the dynamics of its spreading, thereby informing operational planning and supporting decisions.In this proposal we will1. continue to provide valuable insights for the NHS, PHE, and the UK government, for example the impact of further complete or partial lock-downs, of the tier system and possible extensions and modifications, and of different vaccination protocols. This includes, in particular, the application of cutting-edge Bayesian methods for uncertainty quantification in projections of possible futures, and the development of robust data assimilation protocols to improve short-term predictions.2. further refine the population model, with special emphasis on the transmission dynamics and conditions in minorities and on the effect of socio-economic factors on infection and fatality rates. We will also include models for multiple infectious diseases affecting the population concurrently, to quantify the impact of seasonal flu the resulting demands on the health care system.As a by-product we will fully document the code and produce a convenient user-interface, to facilitate its use in future epidemics, thereby turning it into an enduring national asset.