TY - JOUR
T1 - Coexisting attractors in the context of cross-scale population dynamics
T2 - Measles in London as a case study
AU - Becker, Alexander D.
AU - Zhou, Susan H.
AU - Wesolowski, Amy
AU - Grenfell, Bryan T.
N1 - Funding Information:
Data accessibility. Data are provided at https://github.com/adbecker/ LondonRegionalAnalysis/. Authors’ contributions. A.D.B. and S.H.Z. collected the data. A.D.B., S.H.Z. and A.W. performed the analysis. All authors wrote and edited the paper. Competing interests. We declare we have no competing interests. Funding. A.D.B. was supported by a National Science Foundation Graduate Research Fellowship and the Center for Health and Well-being (CHW) at Princeton University. A.W. was supported by a career award at the Scientific Interface from the Burroughs Wellcome Fund and a National Institutes of Health Director’s New Innovator Award. S.H.Z. was supported by the department of Ecology and Evolutionary Biology at Princeton and the CHW. B.T.G. was supported by the Research and Policy for Infectious Disease Dynamics program of the Science and Technology Directorate, Department of Homeland Security, the Fogarty International Center, National Institutes of Health, the Bill and Melinda Gates Foundation and the US Centers for Disease Control and Prevention.
Publisher Copyright:
© 2020 The Authors.
PY - 2020/4/29
Y1 - 2020/4/29
N2 - 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.
AB - 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.
KW - Cross-scale dynamics
KW - Infectious disease dynamics
KW - Measles
KW - Population dynamics
KW - Spatial epidemics
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U2 - 10.1098/rspb.2019.1510
DO - 10.1098/rspb.2019.1510
M3 - Article
C2 - 32315586
AN - SCOPUS:85083871616
SN - 0962-8452
VL - 287
JO - Proceedings of the Royal Society B: Biological Sciences
JF - Proceedings of the Royal Society B: Biological Sciences
IS - 1925
M1 - 20191510
ER -