A kernel-modulated SIR model for Covid-19 contagious spread from county to continent

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  • Xiaolong Geng
    Department of Civil and Environmental Engineering, New Jersey Institute of Technology, Newark, NJ 07102;
  • Gabriel G. Katul
    Nicholas School of the Environment, Duke University, Durham, NC 27710;
  • Firas Gerges
    Department of Civil and Environmental Engineering, New Jersey Institute of Technology, Newark, NJ 07102;
  • Elie Bou-Zeid
    Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08540;
  • Hani Nassif
    Department of Civil and Environmental Engineering, Rutgers University–New Brunswick, Piscataway, NJ 08854
  • Michel C. Boufadel
    Department of Civil and Environmental Engineering, New Jersey Institute of Technology, Newark, NJ 07102;

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<jats:title>Significance</jats:title> <jats:p> Spatial analysis of daily Covid-19 cases at the US county scale revealed a dynamic multifractal scaling of infections, spanning from 10 to 2,600 km and consistently trending toward that of the susceptible population. A susceptible–infected–recovered model was expanded to include spatial spread across counties using a spatial kernel. The reproduction number <jats:italic>R</jats:italic> <jats:sub>b</jats:sub> (average number of persons infected by an infected person) decreased because of interventions (masks, social distancing). The model shows that reducing <jats:italic>R</jats:italic> <jats:sub>b</jats:sub> in isolation is not sufficient to stem the spread of the disease and concomitant measures such as curfews and lockdowns may be needed. The <jats:italic>R</jats:italic> <jats:sub>b</jats:sub> of 2.0 estimated here in July to October 2020 is large, hinting at super-spreaders and super-spreader events. </jats:p>

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