Operationalising Modern Mathematical Epidemiology

Data on healthcare is increasingly collected and processed electronically, creating both opportunities and challenges.

Fortunately, recent years have seen major developments in the field of mathematical epidemiology, which systematically models the patterns of disease and health in the population to disentangle the complexities of the available data.

This project seeks to drive some key insights from mathematical epidemiology into the healthcare system, particularly relating to: the analysis of infectious disease data collected at the household level; how different viruses linked to colds and 'flu hinder and help each others' spread through the population; understanding how people influence each others' health-related behaviours; and cancer radiotherapy.

Other aspects of the project are technical, but seek to answer the questions: What should be done with data that are not experimental, but appear in an uncontrolled way such as during disease outbreaks? And what should we do with data that are constantly being collected through routine surveillance?

The main Impact of the research will be for the general public, who will benefit from improved public health policy relating to infections disease, particularly control measures within households and vaccination policy. The public will also benefit from the situational awareness, detection of emerging threats and other positive outcomes of improved surveillance.

Patients with cancers in need of radiotherapy will benefit from enhanced methods for treatment planning to optimise the trade-off between the probabilities of successful treatment and of normal tissue damage.

Healthcare providers (in the UK, primarily NHS institutions) will benefit from the ability to understand and predict health and healthcare-related behaviours better, and to calibrate these predictions to the population that they serve.