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Study on the spatial decomposition of the infection probability of COVID-19
In the course of our observations of the transmission of COVID-19 around the world, we perceived substantial concern about imported cases versus cases of local transmission. This study, therefore, tries to isolate cases due to local transmission (also called community spread) from those due to exter...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10427675/ https://www.ncbi.nlm.nih.gov/pubmed/37582929 http://dx.doi.org/10.1038/s41598-023-40307-1 |
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author | Liu, Lu |
author_facet | Liu, Lu |
author_sort | Liu, Lu |
collection | PubMed |
description | In the course of our observations of the transmission of COVID-19 around the world, we perceived substantial concern about imported cases versus cases of local transmission. This study, therefore, tries to isolate cases due to local transmission (also called community spread) from those due to externally introduced COVID-19 infection, which can be key to understanding the spread pattern of the pandemic. In particular, we offer a probabilistic perspective to estimate the scale of the outbreak at the epicenter of the COVID-19 epidemic with an environmental focus. First, this study proposes a novel explanation of the probability of COVID-19 cases in the local population of the target city, in which the chain of probability is based on the assumption of independent distribution. Then it conducts a spatial statistical analysis on the spread of COVID-19, using two model specifications to identify the spatial dependence, more commonly known as the spillover effect. The results are found to have strong spatial dependence. Finally, it confirms the significance of residential waste in the transmission of COVID-19, which indicates that the fight against COVID-19 requires us to pay close attention to environmental factors. The method shown in this study is critical and has high practical value, because it can be easily applied elsewhere and to other future pandemics. |
format | Online Article Text |
id | pubmed-10427675 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-104276752023-08-17 Study on the spatial decomposition of the infection probability of COVID-19 Liu, Lu Sci Rep Article In the course of our observations of the transmission of COVID-19 around the world, we perceived substantial concern about imported cases versus cases of local transmission. This study, therefore, tries to isolate cases due to local transmission (also called community spread) from those due to externally introduced COVID-19 infection, which can be key to understanding the spread pattern of the pandemic. In particular, we offer a probabilistic perspective to estimate the scale of the outbreak at the epicenter of the COVID-19 epidemic with an environmental focus. First, this study proposes a novel explanation of the probability of COVID-19 cases in the local population of the target city, in which the chain of probability is based on the assumption of independent distribution. Then it conducts a spatial statistical analysis on the spread of COVID-19, using two model specifications to identify the spatial dependence, more commonly known as the spillover effect. The results are found to have strong spatial dependence. Finally, it confirms the significance of residential waste in the transmission of COVID-19, which indicates that the fight against COVID-19 requires us to pay close attention to environmental factors. The method shown in this study is critical and has high practical value, because it can be easily applied elsewhere and to other future pandemics. Nature Publishing Group UK 2023-08-15 /pmc/articles/PMC10427675/ /pubmed/37582929 http://dx.doi.org/10.1038/s41598-023-40307-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Liu, Lu Study on the spatial decomposition of the infection probability of COVID-19 |
title | Study on the spatial decomposition of the infection probability of COVID-19 |
title_full | Study on the spatial decomposition of the infection probability of COVID-19 |
title_fullStr | Study on the spatial decomposition of the infection probability of COVID-19 |
title_full_unstemmed | Study on the spatial decomposition of the infection probability of COVID-19 |
title_short | Study on the spatial decomposition of the infection probability of COVID-19 |
title_sort | study on the spatial decomposition of the infection probability of covid-19 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10427675/ https://www.ncbi.nlm.nih.gov/pubmed/37582929 http://dx.doi.org/10.1038/s41598-023-40307-1 |
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