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This paper examines the spatial and temporal distribution of all COVID-19 cases from January to June 2020 against the underlying distribution of population in the United States. It is found that, as time passes, COVID-19 cases become a power law with cutoff, resembling the underlying spatial distribution of populations. The power law implies that many states and counties have a low number of cases, while only a few highly populated states and counties have a high number of cases. To further differentiate patterns between the underlying populations and COVID-19 cases, we derived their inherent hierarchy or spatial heterogeneity characterized by the ht-index. We found that the ht-index of COVID-19 cases persistently approaches that of the populations; that is, 5 and 7 at the state and county levels, respectively. Mapping the ht-index of COVID-19 cases against that of populations shows that the pandemic is largely shaped by the underlying population with the R-square value between infection and population up to 0.82.
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篇名 A power-law-based approach to mapping COVID-19 cases in the United States
来源期刊 地球空间信息科学学报(英文版) 学科
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年,卷(期) 2021,(3) 所属期刊栏目
研究方向 页码范围 333-339
页数 7页 分类号
字数 语种 英文
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地球空间信息科学学报(英文版)
季刊
1009-5020
42-1610/P
16开
武汉市珞瑜路129号武汉大学测绘校区
1998
eng
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958
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2719
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