Seven challenges for metapopulation models of epidemics, including households models
Seven challenges for metapopulation models of epidemics, including households models
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DOI：
10.1016/j.epidem.2014.08.001
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发表时间：
2015-03-01
期刊：
影响因子：
3.8
通讯作者：
Tomba, Gianpaolo Scalia
中科院分区：
文献类型：
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作者：
Ball, Frank;Britton, Tom;Tomba, Gianpaolo Scalia
本文考虑一般意义上的集合种群模型，即种群被划分为子种群（组，斑块，.），无论其生物学解释如何，例如，空间隔离的大型亚群、小家庭或被模拟为病原体群体的宿主本身。这个框架传统上提供了一个有吸引力的方法，将更现实的接触结构到流行病模型，因为它往往保留分析的易处理性（在随机以及确定性模型），但也捕捉到最突出的结构不均匀性接触模式在许多应用的情况下。尽管在这两个集合种群模型的理论和应用方面取得了进展，我们在这里提出了几个主要的挑战，仍然为未来的工作，专注于模型，与基于代理的，是服从数学分析。挑战的范围从澄清弱耦合的大型亚群系统在模拟特定疾病的传播的有用性，以发展一个理论与家庭结构的地方病模型。它们还包括为流行病新出现阶段的数据开发推理方法，将集合种群模型扩展到更复杂的人类社会结构形式，开发集合种群模型以反映空间种群结构，开发计算流行病学模型关键数量的计算效率高的方法，以及将宿主内和宿主间的动态整合到模型中。(C)2014作者由爱思唯尔公司出版
This paper considers metapopulation models in the general sense, i.e. where the population is partitioned into sub-populations (groups, patches,...), irrespective of the biological interpretation they have, e.g. spatially segregated large sub-populations, small households or hosts themselves modelled as populations of pathogens. This framework has traditionally provided an attractive approach to incorporating more realistic contact structure into epidemic models, since it often preserves analytic tractability (in stochastic as well as deterministic models) but also captures the most salient structural inhomogeneity in contact patterns in many applied contexts. Despite the progress that has been made in both the theory and application of such metapopulation models, we present here several major challenges that remain for future work, focusing on models that, in contrast to agent-based ones, are amenable to mathematical analysis. The challenges range from clarifying the usefulness of systems of weakly-coupled large sub-populations in modelling the spread of specific diseases to developing a theory for endemic models with household structure. They include also developing inferential methods for data on the emerging phase of epidemics, extending metapopulation models to more complex forms of human social structure, developing metapopulation models to reflect spatial population structure, developing computationally efficient methods for calculating key epidemiological model quantities, and integrating within- and between-host dynamics in models. (C) 2014 The Authors. Published by Elsevier B.V.