Epidemics and pandemics are driven by human behaviour. A key behaviour determining the spread of respiratory or close-contact infectious diseases that can cause rapid and severe epidemics is social interaction. This exciting project aims to develop more realistic models of social interaction to substantially improve epidemic and pandemic modelling and forecasting, and to inform public health policy in the UK and elsewhere. The work will focus on three key questions related to infectious disease transmission and contact networks:

(1) how are epidemic dynamics determined by the multi-scale interface of respiratory pathogen airflow, environment, and interaction patterns?

(2) What is the higher-order structure of social networks relevant to infectious disease transmission, and what are the implication for prediction and control?

(3) How do infected travellers link into the social network of the UK, and what are the surveillance and public health implications?

These research questions will exploit detailed data gathered during the UK covid-19 pandemic, to inform mathematical models of networks, interactions, and transmission. Project partners include the UK Health Security Agency.

Funding Notes
This fully funded PhD studentship includes Home (UK) tuition fees, a stipend paid at UKRI rates, and a bench fee allowance.

Supervisors
Jonathan Read, Sam Moore, Chris Jewell (Lancaster); Steven Riley (UKHSA)