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

流感或SARS等传染病是通过密切的人际接触传播的。所以，在疫情爆发期间你生病的风险可能会受到你和谁交往的影响。因此，了解人们如何相互作用可能是设计有效控制政策的关键。由社会网络结构引发的公共卫生干预措施的例子包括针对家庭（例如，当家庭成员生病时，所有家庭成员都得到抗病毒药物治疗，如达菲）或特定年龄组的干预措施。例如，考虑接种季节性流感疫苗。第一项战略是为老年人接种疫苗，因为他们是患严重疾病和死亡的主要危险群体。然而，由于儿童是流感最重要的传播者，因此建议儿童接种疫苗是降低总体死亡率的更好政策。要评估给儿童还是老年人接种疫苗可能更有效，重要的是要准确评估儿童之间以及儿童与其他年龄组之间的相互作用。如果你得了流感，你能说出你是在哪里被谁感染的吗？在回答这个问题时经常遇到的困难是，是什么让它如此具有挑战性？谁从谁那里感染？从而评估不同公共卫生战略的有效性。这项研究的第一个目的是开发一套相对简单的数学和统计工具，可用于进行这种评价。在业务层面，这些工具将使人们能够深入了解干预措施的潜在影响，监测控制措施的效力，并在疫情期间支持实时决策。例如，这项工作可以为英国为大流行性流感设计的监测系统提供支持；并应提高政治家和其他决策者在适当时刻做出正确选择的能力。通过比较传播途径(？谁从谁那里获得感染？)的不同感染和其他社会学指标(？谁与谁交谈？)，我们还将尝试回答有关传播复杂性的基本问题。例如，什么样的社会接触会导致传播？说话吗?拥抱吗?这些看似简单的问题的答案可能会对未来的疾病预防产生重大影响。

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.