Spatio-temporal modelling and analysis of bacterial and viral infections

这个项目将开始调查一个关于军团病的实际问题，军团病是一种相对罕见但有据可查的疾病。监测数据的季节趋势将在该地区以前工作的基础上加以考虑（Rickketts天气模式和军团病：气象研究|流行病学与感染|剑桥Core和Sansom等人的Cluster Detection tool，一种病例关联聚类检测和可视化工具，应用于退伍军人病- PubMed（nih.gov）），使用不同的统计技术和最新的流行病学和气象数据。除了方便/易于访问的数据集之外，对感染过程或天气影响的关注有限。在对统计方法和数据科学技术进行审查的同时，数学建模工作将考虑感染机制，并应考虑天气变量。在此基础上，该项目将考虑对替代疾病的应用以及围绕病例定义进行监测的具体问题。

This project will begin with investigating a practical question on Legionnaires disease, a relatively rare but well documented disease. Seasonal trends in surveillance data will be considered building on previous work in area (Rickketts Weather patterns and Legionnaires' disease: a meteorological study | Epidemiology & Infection | Cambridge Core and Sansom et al Cluster Detection tool, A case-association cluster detection and visualisation tool with an application to Legionnaires' disease - PubMed (nih.gov)) using different statistical techniques and up to date epidemiological and meteorological data. Limited attention has been drawn to the process of infection or the impact of weather beyond convenient/easy to access data sets. In tandem with a review of statistical methods and data science techniques, mathematical modelling work will consider the mechanisms of infection should inform the weather variables to consider. Building on this the project will consider application to alternative diseases and specific question on surveillance around case definitions.