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DOI10.1073/pnas.2023321118
A kernel-modulated SIR model for Covid-19 contagious spread from county to continent
Geng X.; Katul G.G.; Gerges F.; Bou-Zeid E.; Nassif H.; Boufadel M.C.
发表日期2021
ISSN0027-8424
卷号118期号:21
英文摘要The tempo-spatial patterns of Covid-19 infections are a result of nested personal, societal, and political decisions that involve complicated epidemiological dynamics across overlapping spatial scales. High infection “hotspots” interspersed within regions where infections remained sporadic were ubiquitous early in the outbreak, but the spatial signature of the infection evolved to affect most regions equally, albeit with distinct temporal patterns. The sparseness of Covid-19 infections in the United States was analyzed at scales spanning from 10 to 2,600 km (county to continental scale). Spatial evolution of Covid-19 cases in the United States followed multifractal scaling. A rapid increase in the spatial correlation was identified early in the outbreak (March to April). Then, the increase continued at a slower rate and approached the spatial correlation of human population. Instead of adopting agent-based models that require tracking of individuals, a kernel-modulated approach is developed to characterize the dynamic spreading of disease in a multifractal distributed susceptible population. Multiphase Covid-19 epidemics were reasonably reproduced by the proposed kernel-modulated susceptible–infectious–recovered (SIR) model. The work explained the fact that while the reproduction number was reduced due to nonpharmaceutical interventions (e.g., masks, social distancing, etc.), subsequent multiple epidemic waves still occurred; this was due to an increase in susceptible population flow following a relaxation of travel restrictions and corollary stay-at-home orders. This study provides an original interpretation of Covid-19 spread together with a pragmatic approach that can be imminently used to capture the spatial intermittency at all epidemiologically relevant scales while preserving the “disordered” spatial pattern of infectious cases. © 2021 National Academy of Sciences. All rights reserved.
英文关键词Coronavirus disease; Fourier analysis; Multifractals; Population agglomeration; Susceptible–infectious–recovered approach
语种英语
scopus关键词Article; controlled study; coronavirus disease 2019; correlational study; epidemic; epidemiological data; human; infection control; infection risk; infection sensitivity; kernel method; social distancing; stay-at-home order; travel restriction; United States; epidemiology; isolation and purification; mask; metabolism; pandemic; theoretical model; COVID-19; Humans; Masks; Models, Theoretical; Pandemics; Physical Distancing; SARS-CoV-2; United States
来源期刊Proceedings of the National Academy of Sciences of the United States of America
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/238735
作者单位Department of Civil and Environmental Engineering, New Jersey Institute of Technology, Newark, NJ 07102, United States; Nicholas School of the Environment, Duke University, Durham, NC 27710, United States; Department of Civil and Environmental Engineering, Duke University, Durham, NC 27708, United States; Department of Computer Science, New Jersey Institute of Technology, Newark, NJ 07102, United States; Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08540, United States; Department of Civil and Environmental Engineering, Rutgers University–New Brunswick, Piscataway, NJ 08854, United States
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Geng X.,Katul G.G.,Gerges F.,et al. A kernel-modulated SIR model for Covid-19 contagious spread from county to continent[J],2021,118(21).
APA Geng X.,Katul G.G.,Gerges F.,Bou-Zeid E.,Nassif H.,&Boufadel M.C..(2021).A kernel-modulated SIR model for Covid-19 contagious spread from county to continent.Proceedings of the National Academy of Sciences of the United States of America,118(21).
MLA Geng X.,et al."A kernel-modulated SIR model for Covid-19 contagious spread from county to continent".Proceedings of the National Academy of Sciences of the United States of America 118.21(2021).
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