Modelling the disorganised ecology of post-pandemic respiratory viruses

在新冠肺炎大流行之前，冬季呼吸道病毒的传播相对可预测。然而，在整个大流行期间实施的疫情控制措施扰乱了常规的季节性模式。流感和呼吸道合胞病毒(RSV)等季节性呼吸道病毒在经历了历史上的低循环后，又卷土重来，其特点是传播异常。造成这一现象的因素可能有多种，例如在严格限制措施期间没有接触到这些病毒。那些通常会被感染的人会获得免疫力，免受感染。然而，对于大多数季节性呼吸道病毒，免疫不是终生的，这意味着在一段时间后有可能再次感染，从而形成感染模式。这个博士项目将利用新冠肺炎大流行对呼吸道病毒正常季节性循环的干扰，以及这些病毒的后续重组，以更好地了解它们如何在环境中传播，以及循环模式是如何创建和维持的。该项目将使用英国健康安全局提供的关于呼吸道感染的公开数据。此外，将与监督人员一起考虑使用欧洲疾病预防和控制中心(ECDC)托管的公开可用的欧洲数据集进行分析的可能性。将对感兴趣的病毒的历史传播进行分析，以便将其与当前的传播和“大流行年”进行比较。将设计和开发数学模型，以调查大流行后季节性呼吸道病毒循环变化的生物学或社会学原因。这种研究方法将对量化技能的发展做出重大贡献。此外，研究问题的方法将是多学科的，因为将考虑公共卫生、病毒学和免疫学以及统计学和计算机编程的要素。因此，由于研究的性质和工作环境，将获得关于传染病模型的深入知识和广度知识。这个项目提供了一个更好地了解季节性呼吸道病毒传播的驱动因素的机会。这些知识可用于制定战略，以减轻呼吸道病毒感染的影响，减轻其对人口的负担，并减轻其对医疗保健系统的压力。该项目的工作将对政府和公共卫生有用；拥有更多的知识，它们可以提供更好的指导和建议，并设计更有效和更有针对性的未来干预措施。

Prior to the COVID-19 pandemic, the circulation of respiratory viruses during the winter was relatively predictable. However, outbreak control measures implemented throughout the pandemic have thrown regular seasonal patterns into disarray. After historically low circulation of seasonal respiratory viruses like influenza and respiratory syncytial virus (RSV), they have returned, characterised by unusual transmission. Various factors may be contributing to this phenomenon, such as the lack of exposure to these viruses during the period of heavy restrictions. Those that would have normally been infected would have gained immunity, protection from infection. However, with most seasonal respiratory viruses, immunity is not lifelong, meaning that after a certain period there is the potential for reinfection, thus creating patterns of infection.This PhD project will use the disruption to usual seasonal circulation of respiratory viruses, caused by the COVID-19 pandemic, and the following reorganisation of these viruses to better understand how they circulate in the environment and how circulation patterns are created and maintained.This project will use publicly available data on respiratory infections from the UK Health Security Agency (HSA). In addition, the possibility of using publicly available European datasets hosted at the European Centre for Disease Prevention and Control (ECDC) for analysis will be considered with the supervisors. An analysis on historical circulation of the viruses of interest will be done so that it can be compared to current circulation and during the "pandemic years". Mathematical models will be designed and developed to investigate biological or sociological reasons for changes in post-pandemic seasonal respiratory virus circulation. The research method will significantly contribute to the development of quantitative skills. In addition, the approach to the research question will be multidisciplinary since elements of public health, virology, and immunology as well as statistics and computer programming will be considered. Therefore, depth of knowledge will be obtained on infectious disease modelling and breadth of knowledge will also be acquired due to the nature of the research and the working environment.This project offers an opportunity to better understand the drivers of seasonal respiratory virus transmission. This knowledge can be useful to establish strategies to mitigate the impact of respiratory virus infections, reduce their burden on the population and alleviate the strain they put on healthcare systems. The work from this project will be useful to governments and public health; equipped with more knowledge they can provide better guidance and advice as well as design more effective and targeted future interventions.