Stochastic epidemic models in structured populations

拟议研究的目的是发展和分析纳入现实人口结构并在数学上易于处理的随机流行病模型。将调查明确包括家庭结构的随机网络模型，以及允许不同感染严重程度的模型和包含更复杂结构的模型，例如分层混合（例如，城市人口，每个城市都划分为家庭，家庭内、城市内和城市间接触的感染率不同），重叠子组（其中人口以几种方式划分），例如，根据个人的家庭和工作场所)和空间局部混合。对于每个模型，将确定控制爆发是否可以建立的阈值参数，以及其他属性，例如爆发建立的概率和最终结果。将利用各种模型探讨疫苗接种如何影响疫苗接种者对有关疾病的易感性以及如果他/她被感染，他/她传播疾病的能力，从而探讨对疫苗接种战略的影响。这一理论将通过对SARs和大流行性流感等疾病提出的现实接触网络的模拟来进行检验。计划中的研究将导致分析流行病模型的新方法，并增加对感染传播的基本机制以及这种机制对疫苗接种计划的效果的影响的了解。

The aim of the proposed research is to develop and analyse stochastic epidemic models that incorporate realistic population structures and are mathematically tractable. Random network models that explicitly include household structure will be investigated, as will models that allow different severities of infection and models incorporating more complex structures, such as hierarchical mixing (e.g. a population of cities, each of which is partitioned into households, with different infection rates for within-household, within-city and between-city contacts), overlapping subgroups (in which the population is partitioned in several ways, e.g according to both the household and workplace of individuals) and spatial local mixing. For each model, a threshold parameter that governs whether or not an outbreak can become established will be determined, together with other properties, such as the probability that an outbreak does become established and the final outcome if it does. Implications for vaccination strategies will be explored, using a varitey of models for how vaccination affects a vaccinee's susceptibility to the disease in question and his/her ability to transmit the disease if he/she becomes infected. The theory developed will be tested by using simulations on realistic contact networks that have been proposed for diseases such as SARs and pandemic influenza. The planned research will lead to novel methods for analysing epidemic models and to increased understanding of the mechanisms underlying the spread of infection and the effect of such mechanisms on the performance of vaccination schemes.