疫情时间序列相似性与地理距离和年龄结构有关。
Epidemic time series similarity is related to geographic distance and age structure.
作者信息
Dallas Tad A, Foster Grant, Richards Robert L, Elderd Bret D
机构信息
Department of Biological Sciences, University of South Carolina, Columbia, SC, 29208, USA.
Department of Biological Sciences, Louisiana State University, Baton Rouge, LA, 70802, USA.
出版信息
Infect Dis Model. 2022 Oct 12;7(4):690-697. doi: 10.1016/j.idm.2022.09.002. eCollection 2022 Dec.
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 ( ) 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 on epidemic similarity, but notably the effect of age structure was stronger than the baseline assumption that differences in 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.
目的
地理位置越相近，传染病动态可能越相似。导致疫情相似的假定原因存在明显重叠，如地理距离、年龄结构和人口规模。与基本再生数（ ）的差异会转化为疫情轨迹差异这一基线假设相比，我们比较了这些潜在驱动因素对疫情相似性的影响。
方法
利用美国各县的新冠肺炎病例数，我们探讨了地理距离、人口规模差异和年龄结构差异对由此产生的疫情相似性的重要性。
结果
我们发现地理空间、年龄结构、人口规模和 对疫情相似性有明显影响，但值得注意的是，年龄结构的影响比基线假设更强，即 的差异与疫情相似性最相关。
结论
综上所述，这凸显了空间和人口过程在美国SARS-CoV2疫情中的作用。
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