  RR Lyrae stars (RRLs) are tracers of the Milky Way's fossil record, holding
valuable information on its formation and early evolution. Owing to the high
interstellar extinction endemic to the Galactic plane, distant RRLs lying at
low Galactic latitudes have been elusive. We attained a census of 1892
high-confidence RRLs by exploiting the near-infrared photometric database of
the VVV survey's disk footprint spanning $\sim$70$^\circ$ of Galactic
longitude, using a machine-learned classifier. Novel data-driven methods were
employed to accurately characterize their spatial distribution using sparsely
sampled multi-band photometry. The RRL metallicity distribution function (MDF)
was derived from their $K_s$-band light curve parameters using machine-learning
methods. The MDF shows remarkable structural similarities to both the
spectroscopic MDF of red clump giants and the MDF of bulge RRLs. We model the
MDF with a multi-component density distribution and find that the number
density of stars associated with the different model components systematically
changes with both the Galactocentric radius and vertical distance from the
Galactic plane, equivalent to weak metallicity gradients. Based on the
consistency with results from the ARGOS survey, three MDF modes are attributed
to the old disk populations, while the most metal-poor RRLs are probably halo
interlopers. We propose that the dominant [Fe/H] component with a mean of $-1$
dex might correspond to the outskirts of an ancient Galactic spheroid or
classical bulge component residing in the central Milky Way. The physical
origins of the RRLs in this study need to be verified by kinematical
information.
