Your browser doesn't support javascript.
A kernel-modulated SIR model for Covid-19 contagious spread from county to continent.
Geng, Xiaolong; Katul, Gabriel G; Gerges, Firas; Bou-Zeid, Elie; Nassif, Hani; Boufadel, Michel C.
  • Geng X; Department of Civil and Environmental Engineering, New Jersey Institute of Technology, Newark, NJ 07102.
  • Katul GG; Nicholas School of the Environment, Duke University, Durham, NC 27710.
  • Gerges F; Department of Civil and Environmental Engineering, Duke University, Durham, NC 27708.
  • Bou-Zeid E; Department of Civil and Environmental Engineering, New Jersey Institute of Technology, Newark, NJ 07102.
  • Nassif H; Department of Computer Science, New Jersey Institute of Technology, Newark, NJ 07102.
  • Boufadel MC; Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08540.
Proc Natl Acad Sci U S A ; 118(21)2021 05 25.
Article in English | MEDLINE | ID: covidwho-1219283
ABSTRACT
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.
Subject(s)
Keywords

Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study Limits: Humans Country/Region as subject: North America Language: English Year: 2021 Document Type: Article

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study Limits: Humans Country/Region as subject: North America Language: English Year: 2021 Document Type: Article