Ontology highlight
ABSTRACT: Objective
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 (R 0) will translate to differences in epidemic trajectories.Methods
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.Results
We find clear effects of geographic space, age structure, population size, and R 0 on epidemic similarity, but notably the effect of age structure was stronger than the baseline assumption that differences in R 0 would be most related to epidemic similarity.Conclusions
Together, this highlights the role of spatial and demographic processes on SARS-CoV2 epidemics in the United States.
SUBMITTER: Dallas TA
PROVIDER: S-EPMC9579807 | biostudies-literature | 2022 Dec
REPOSITORIES: biostudies-literature

Infectious Disease Modelling 20221012 4
<h4>Objective</h4>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 (<i>R</i> <sub>0</sub>) will translate to differences in epidemic trajectories.<h4>Methods</h4>Using COVID-19 case counts fr ...[more]