ArticleProceedings. Biological sciences2020
Coexisting attractors in the context of cross-scale population dynamics: measles in London as a case study.
Article in Proceedings. Biological sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Toward AI foundation models for epidemics: Promise, challenges, and paths forward.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Deep neural networks for endemic measles dynamics: Comparative analysis and integration with mechanistic models.PLoS computational biology · 2024Article
- Bagged filters for partially observed interacting systems.Journal of the American Statistical Association · 2023Article
- Development and dissemination of infectious disease dynamic transmission models during the COVID-19 pandemic: what can we learn from other pathogens and how can we move forward?The Lancet. Digital health · 2021Review
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Authors and funding
4 authors.
Funding
Abstract
Patterns of measles infection in large urban populations have long been considered the paradigm of synchronized nonlinear dynamics. Indeed, recurrent epidemics appear approximately mass-action despite underlying heterogeneity. However, using a subset of rich, newly digitized mortality data (1897-1906), we challenge that proposition. We find that sub-regions of London exhibited a mixture of simultaneous annual and biennial dynamics, while the aggregate city-level dynamics appears firmly annual. Using a simple stochastic epidemic model and maximum-likelihood inference methods, we show that we can capture this observed variation in periodicity. We identify agreement between theory and data, indicating that both changes in periodicity and epidemic coupling between regions can follow relatively simple rules; in particular we find local variation in seasonality drives periodicity. Our analysis underlines that multiple attractors can coexist in a strongly mixed population and follow theoretical predictions.
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Registered trials
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