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Spatiotemporal Patterns of the Omicron Wave of COVID-19 in the United States
COVID-19 has undergone multiple mutations, with the Omicron variant proving to be highly contagious and rapidly spreading across many countries. The United States was severely hit by the Omicron variant. However, it was still unclear how Omicron transferred across the United States. Here, we collect...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10385263/ https://www.ncbi.nlm.nih.gov/pubmed/37505645 http://dx.doi.org/10.3390/tropicalmed8070349 |
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author | Zhang, Siyuan Liu, Liran Meng, Qingxiang Zhang, Yixuan Yang, He Xu, Gang |
author_facet | Zhang, Siyuan Liu, Liran Meng, Qingxiang Zhang, Yixuan Yang, He Xu, Gang |
author_sort | Zhang, Siyuan |
collection | PubMed |
description | COVID-19 has undergone multiple mutations, with the Omicron variant proving to be highly contagious and rapidly spreading across many countries. The United States was severely hit by the Omicron variant. However, it was still unclear how Omicron transferred across the United States. Here, we collected daily COVID-19 cases and deaths in each county from 1 December 2021 to 28 February 2022 as the Omicron wave. We adopted space-time scan statistics, the Hoover index, and trajectories of the epicenter to quantify spatiotemporal patterns of the Omicron wave of COVID-19. The results showed that the highest and earliest cluster was located in the Northeast. The Hoover index for both cases and deaths exhibited phases of rapid decline, slow decline, and relative stability, indicating a rapid spread of the Omicron wave across the country. The Hoover index for deaths was consistently higher than that for cases. The epicenter of cases and deaths shifted from the west to the east, then southwest. Nevertheless, cases were more widespread than deaths, with a lag in mortality data. This study uncovers the spatiotemporal patterns of Omicron transmission in the United States, and its underlying mechanisms deserve further exploration. |
format | Online Article Text |
id | pubmed-10385263 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-103852632023-07-30 Spatiotemporal Patterns of the Omicron Wave of COVID-19 in the United States Zhang, Siyuan Liu, Liran Meng, Qingxiang Zhang, Yixuan Yang, He Xu, Gang Trop Med Infect Dis Article COVID-19 has undergone multiple mutations, with the Omicron variant proving to be highly contagious and rapidly spreading across many countries. The United States was severely hit by the Omicron variant. However, it was still unclear how Omicron transferred across the United States. Here, we collected daily COVID-19 cases and deaths in each county from 1 December 2021 to 28 February 2022 as the Omicron wave. We adopted space-time scan statistics, the Hoover index, and trajectories of the epicenter to quantify spatiotemporal patterns of the Omicron wave of COVID-19. The results showed that the highest and earliest cluster was located in the Northeast. The Hoover index for both cases and deaths exhibited phases of rapid decline, slow decline, and relative stability, indicating a rapid spread of the Omicron wave across the country. The Hoover index for deaths was consistently higher than that for cases. The epicenter of cases and deaths shifted from the west to the east, then southwest. Nevertheless, cases were more widespread than deaths, with a lag in mortality data. This study uncovers the spatiotemporal patterns of Omicron transmission in the United States, and its underlying mechanisms deserve further exploration. MDPI 2023-06-30 /pmc/articles/PMC10385263/ /pubmed/37505645 http://dx.doi.org/10.3390/tropicalmed8070349 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zhang, Siyuan Liu, Liran Meng, Qingxiang Zhang, Yixuan Yang, He Xu, Gang Spatiotemporal Patterns of the Omicron Wave of COVID-19 in the United States |
title | Spatiotemporal Patterns of the Omicron Wave of COVID-19 in the United States |
title_full | Spatiotemporal Patterns of the Omicron Wave of COVID-19 in the United States |
title_fullStr | Spatiotemporal Patterns of the Omicron Wave of COVID-19 in the United States |
title_full_unstemmed | Spatiotemporal Patterns of the Omicron Wave of COVID-19 in the United States |
title_short | Spatiotemporal Patterns of the Omicron Wave of COVID-19 in the United States |
title_sort | spatiotemporal patterns of the omicron wave of covid-19 in the united states |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10385263/ https://www.ncbi.nlm.nih.gov/pubmed/37505645 http://dx.doi.org/10.3390/tropicalmed8070349 |
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