  The pattern formation and spatial spread of infectious populations are
investigated using a kernel-based Susceptible-Infectious-Recovered (SIR) model
applicable across a wide range of basic reproduction numbers $R_o$. The focus
is on the role of geographic spreaders defined here as a portion of the
infected population ($\phi$) experiencing high mobility between identical
communities. The spatial organization of the infected population and invasive
front speeds ($c_{max}$) are determined when the infections are randomly
initiated in space within multiple communities. For small but finite $\phi$,
scaling analysis in 1-dimension and simulation results in 2-dimensions suggest
that $c_{max}\sim (1-\phi) \gamma (R_o-1) \sigma$, where $\gamma$ is the
inverse of the infectious duration, and $\sigma^2$ is the variance of the
spatial kernel describing mobility of long-distance spreaders across
communities. Hence, $c_{max}$ is not significantly affected by the small $\phi$
though reductions in $\phi$ act as retardation factors to the attainment of
$c_{max}$. The $\sigma$ determines the spatial organization of infections
across communities. When $\sigma >5dr$ (long-distance mobility, where $dr$ is
the minimum spatial extent defining adjacent communities), the infectious
population will experience a transient but spatially coherent pattern with a
wavelength that can be derived from the spreading kernel properties.
