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Study on the spatial decomposition of the infection probability of COVID-19
by
Liu, Lu
in
692/699/255/1578
/ 692/699/255/2514
/ 692/700/1538
/ 692/700/228
/ 692/700/3934
/ COVID-19
/ Disease transmission
/ Environmental factors
/ Humanities and Social Sciences
/ Local population
/ multidisciplinary
/ Pandemics
/ Science
/ Science (multidisciplinary)
/ Spatial analysis
/ Statistical analysis
2023
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Study on the spatial decomposition of the infection probability of COVID-19
by
Liu, Lu
in
692/699/255/1578
/ 692/699/255/2514
/ 692/700/1538
/ 692/700/228
/ 692/700/3934
/ COVID-19
/ Disease transmission
/ Environmental factors
/ Humanities and Social Sciences
/ Local population
/ multidisciplinary
/ Pandemics
/ Science
/ Science (multidisciplinary)
/ Spatial analysis
/ Statistical analysis
2023
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Do you wish to request the book?
Study on the spatial decomposition of the infection probability of COVID-19
by
Liu, Lu
in
692/699/255/1578
/ 692/699/255/2514
/ 692/700/1538
/ 692/700/228
/ 692/700/3934
/ COVID-19
/ Disease transmission
/ Environmental factors
/ Humanities and Social Sciences
/ Local population
/ multidisciplinary
/ Pandemics
/ Science
/ Science (multidisciplinary)
/ Spatial analysis
/ Statistical analysis
2023
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Study on the spatial decomposition of the infection probability of COVID-19
Journal Article
Study on the spatial decomposition of the infection probability of COVID-19
2023
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Overview
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.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
Subject
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