Multiscale Modelling Reveals Accelerating Community Outbreak Risks of Measles in the United States

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Authors: Siyu Chen, Ana I. Bento
Cited by: 1
References: 16

Abstract

Abstract Measles resurgence in high-income countries that previously achieved elimination reveals a critical surveillance failure: current systems rely on county-level aggregates that obscure fine-scale clustering where outbreaks originate. We assembled the nationwide multiscale vaccination database spanning 45 US states (2013–2025), encompassing over 50,000 schools, 13,000 districts, and 3,000 counties. We developed a gravity-based transmission framework and demonstrate that school-level effective reproduction numbers crossed the epidemic threshold in 2022–2023, a transition invisible to aggregated surveillance. Average susceptibility doubled from approximately 5% to 10% following the COVID-19 pandemic. Three independent mechanisms drive aggregation bias: enrollment-weighted averaging systematically dilutes small under-vaccinated schools; gravity kernels attenuate transmission potential with coarser spatial scales; and clustering signal erasure converts heterogeneous risk landscapes into falsely uniform county averages. School district boundaries frequently misalign with counties, creating cross-boundary transmission corridors that push well-vaccinated counties above epidemic threshold through spillover alone. State trajectories diverge markedly, shaped by exemption policies and local infrastructure. Preventing measles re-endemicity requires surveillance systems operating at the spatial scale where vulnerability accumulates.

Fields of Study & Subjects

Virology and Viral Diseases COVID-19 epidemiological studies Vaccine Coverage and Hesitancy

Publication details

Journal / source
medRxiv
Publisher
openRxiv
Publication date
30 January 2026
Document type
Preprint