Pooling Mobility Obscures Epidemic Invasion Routes

2026-08-26

AI Summary

研究解决了疫情模型中因合并不同交通方式导致的入侵路径信息丢失问题，通过定向多层流和重尾变化分析，提出恢复路径组成的条件及监控决策成本。

Abstract

Epidemic models often pool air travel, commuting, and other mobility layers into a single weighted network. Pooling keeps the total imported infections into a region but discards the transport mode and route that delivered them, the information a mode-specific intervention needs. We make this precise for directed multilayer flows with heavy-tailed variation. Pooling acts as an asymmetric filter. The magnitude of an extreme importation, its radial tail index, is an exact invariant of sampling and nonnegative aggregation, whereas its composition across layers and routes, the angular part, is reweighted by layer-specific sampling and can be irrecoverably merged. We give a necessary and sufficient condition for recovering route composition, attach a surveillance decision cost to the loss, and show that the first established route need not be the busiest. A controlled metapopulation study calibrates the cost, and two contrasting reconstructions show where it bites. In US pandemic influenza, air adds fitted information beyond commuting, and a layer-resolved ranking targets more air-import burden than a pooled one. In the early Italian COVID-19 wave, commuting improves onset reconstruction while air attribution stays unresolved. Pooling can therefore support total-importation surveillance but cannot in general identify the mode or route behind an importation.

Problem

• Epidemic models
• Pooling mobility
• Transport mode
• Infection routes
• Multilayer flows

Innovation

• multilayer flows
• asymmetric filter
• radial tail index
• route composition
• mode-specific intervention