发表机构
The Gates Foundation’s Institute for Disease Modeling（盖茨基金会疾病建模研究所）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究通过约束优化方法，为英国60城市构建了高分辨率麻疹传播模型，揭示了子社区开放性与病例报告动态对传播监测及消除推断的关键影响。
AI 中文摘要
我们经常面临这样的情况：麻疹传播模型停留在粗略的人口尺度上。本文旨在提高其分辨率，或者说，为人口的子社区创建一致的模型。我们特别关注这样一个事实：即使整个人口是隔离的，子社区对麻疹输入和人口流动的相关后果也是开放的。事实证明，分辨率问题可以有效地构建为一个约束优化问题，其中约束是对粗略模型的聚合。这种数学框架使我们能够做出集中于大人口尺度的流行病学动机近似，这些近似在该尺度上更为有效，从而使细子社区尺度的估计异常地缺乏结构。我们在疫苗接种前时代的英国60城市数据集的背景下发展了这一想法，为所有60个城市构建了传播模型。我们发现这些模型具有直观的季节性、波动性和输入性元素，但它们依赖于病例报告概率中的非平凡动态。对这些监测过程的潜在解释进行了详细讨论，我们还描述了它们如何影响对竞争性隐秘传播和瞬时消除动态之间平衡的推断。
英文摘要
We're often in a situation where we have models of measles transmission that are stuck at a coarse population scale. This paper is about increasing their resolution or, said differently, creating consistent models for the population's subcommunities. We pay special attention to the fact that even if the full population is isolated, subcommunities are open to measles importations and related consequences of population movement. It turns out that the resolution issue can be productively framed as a constrained optimization problem, where the constraint is aggregation to the coarse model. That mathematical scaffolding allows us to make epidemiologically motivated approximations concentrated at the large population scale, where they're more valid, which leaves the estimates at the fine subcommunity scale atypically unstructured. We develop the idea in the context of the pre-vaccination-era 60 city UK dataset, building transmission models for all 60 cities. We find that they have intuitive seasonality, volatility, and importation elements, but that they depend on nontrivial dynamics in their case reporting probabilities. Potential interpretations of those surveillance processes are discussed in some detail, and we also describe how they influence inference on the balance between competing cryptic transmission and transient elimination dynamics.
