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Jonathan Readcontact networks
When a disease jumps to a new host species and adapts to transmit directly within the new host population, it is often confronted with an entirely new network of possible transmission routes, very different to the structure dictated by the population processes of its original host. Such networks of potential transmission (contact networks) form an important area of research within epidemiology, and understanding them will enable better predictions of what to expect when zoonoses enter a new host population, how best to mitigate such outbreaks, and how the pathogen is likely to adapt and survive within the new host species.
Measuring and understanding contact networks
Surprisingly little is known about contact networks; possibly the best documented examples are livestock animal movements, where legislation compels the recording of movement of animals between farms. Yet the contact network and mixing patterns of humans -- an obvious target species for zoonoses research -- are poorly understood, particularly for infections that can spread through airborne or saliva-based transmission routes.
Work conducted in collaboration with Prof Matt Keeling at Warwick University aims to quantify the social encounters of a large sample of the UK population, through postal and web-based surveys, with the aim of incorporating this information into a detailed UK-scale network model of people’s movements and interactions. This representation of people’s day-to-day interactions will be used to forecast the impact of important emerging infections, such as avian influenza, should a pandemic occur. It will also significantly help in the design of optimal control policies, and should identify high-risk occupations and ‘core’-groups.
Other work being conducted (in collaboration with Dr Derek Cumming and Dr Steven Riley) is the collection of social encounter and travel information of people from both rural and urban districts of Guangdong province, China. This information will be used to explain the observed spatial pattern of seasonal ‘flu within the same study group, which we hope will provide key insights into the temporal-spatial dynamics of disease and the ‘immunological landscape’, as well as help parameterise a model of human interactions and movement in a region linked to the emergence of both SARS and highly-pathogenic avian influenza in recent years.
PUBLICATIONS
Read, J.M., Eames, K.T.D., Edmunds, W.J. (2008) Dynamic social networks and the implications for the spread of infectious disease. Journal of the Royal Society Interface 5(26), 957-1118.
