Estimating the impact of social structure on epidemics and predicting the impact of targeted interventions

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Communicable diseases like flu or SARS transmit through close inter-personal contacts. So, the risk that you get ill during an outbreak is likely to be influenced by who you mix with. Understanding how people interact with each other may therefore be the key to designing efficient control policies. Examples of public health interventions which are triggered by the structure of the social network include those which target households (for example, all household members are treated with antivirals such as Tamiflu when a member is sick) or specific age groups. Consider for example vaccination against seasonal influenza. A first strategy is to vaccinate the elderly as they constitute the main risk group for severe disease and mortality. However, vaccination of children has been suggested as a better policy to minimise mortality overall, since children are the most important transmitters of flu. To assess whether vaccinating children or the elderly is likely to be more effective, it is important to precisely assess how children interact with each other and with other age groups. If you had flu, would you be able to say where and by whom you got infected? The frequent difficulty in answering this question is what makes it so challenging to determine ?who acquires infection from whom? and thus assess the effectiveness of the different public health strategies. A first aim of this study will be to develop a set of relatively simple mathematical and statistical tools that can be used to make such an evaluation. On an operational level, those tools will make it possible to gain insight on the potential impact of interventions, to monitor the efficacy of control measures and to support decision making in real-time during an outbreak. This work could for example feed the UK surveillance system designed for pandemic influenza; and should increase the capacity of politicians and other decision makers to make the correct choices at the appropriate moments.By comparing the route of transmission (?who acquires infection from whom?) for different infections and to other sociological indicators (?who talks to whom?), we will also try to answer fundamental questions on the complex nature of transmission. For example, what types of social contact can lead to transmission? Talking? Hugging? Answers to those seemingly simple questions may have major implications in terms of future disease prevention.