More similar locations may have similar infectious disease dynamics. There is clear overlap in putative causes for epidemic similarity, such as geographic distance, age structure, and population size. We compare the effects of these potential drivers on epidemic similarity compared to a baseline assumption that differences in the basic reproductive number (R0) will translate to differences in epidemic trajectories.
Using COVID-19 case counts from United States counties, we explore the importance of geographic distance, population size differences, and age structure dissimilarity on resulting epidemic similarity.
We find clear effects of geographic space, age structure, population size, and R0 on epidemic similarity, but notably the effect of age structure was stronger than the baseline assumption that differences in R0 would be most related to epidemic similarity.
Together, this highlights the role of spatial and demographic processes on SARS-CoV2 epidemics in the United States.
Digital Object Identifier (DOI)
Published in Infectious Disease Modelling, Volume 7, Issue 14, 2022, pages 690-697.
© 2022 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).
Dallas, T. A., Foster, G., Richards, R. L., & Elderd, B. D. (2022). Epidemic time series similarity is related to geographic distance and age structure. Infectious Disease Modelling, 7(4), 690–697. https://doi.org/10.1016/j.idm.2022.09.002