Social contact survey and modelling the spread of influenza

When the HIV epidemic was recognised in the 1980s, vast amounts of work were undertaken to reveal the networks of sexual encounters through which HIV could spread. Knowing this allowed scientists to develop accurate predictions of the way the epidemic would grow. Given the current risks of pandemic influenza, it is necessary to collect similar information on the types of personal interaction which can lead to the spread of influenza or other airborne infections. We have developed a simple anonymous questionnaire which we wish to distribute to homes in the UK -- as well as developing a web-based questionnaire. The results of this survey will provide a picture of the types, duration and number of social contacts per person in the UK. This data will then enable us to create a far more accurate mathematical model which will be used to predict the spread of influenza in the UK, identify the most at-risk sections of the community, and help to inform policy makers and public-health organisations about the best way to control any outbreaks.

Mathematical models of infectious diseases play an increasingly important role in planning for (re)emerging infections, allowing public health organisations to optimise limited resources or ascertain the level of resources necessary to ensure a particular outcome. However, such models are only as good as the data used to parameterise them. This project seeks to determine the per capita number (and type) of social interactions in the UK, and calculate how such information can be incorporated into state-of-the-art epidemiological models. In particular, we have developed a simple single-use questionnaire that captures the interpersonal interactions that are most important for the spread of airborne infectious disease; we wish to extend our pilot studies to large-scale postal and web-based investigations of the general UK population. This information will be statistically analysed to determine the distribution of (and cross-correlations between) different types of social contacts. In addition, we will develop a range of sophisticated mathematical techniques to determine the plausible transmission-network structures associated with various airborne-infectious diseases, to incorporate this information with existing spatial and household-based modelling approaches, and hence understand how this extra contact information influences disease spread and efficient control. Disseminating the findings of our research to relevant public health organisations and other relevant stakeholders forms an essential component of the project.