Abstract

Context. The Vista Variables in the Via Lactea (VVV) near-infrared variability survey explores some of the most complex regions of the Milky Way bulge and disk in terms of high extinction and high crowding.Aims. We add a new wavelength dimension to the optical information available at the American Association of Variable Star Observers International Variable Star Index (VSX-AAVSO) catalogue to test the VVV survey near-infrared photometry to better characterise these objects.Methods. We cross-matched the VVV and the VSX-AAVSO catalogues along with Gaia Data Release 2 photometry and parallax.Results. We present a catalogue that includes accurate individual coordinates, near-infrared magnitudes (ZYJHKs), extinctions A(Ks), and distances based on Gaia parallaxes. We also show the near-infrared CMDs and spatial distributions for the different VSX types of variable stars, including important distance indicators, such as RR Lyrae, Cepheids, and Miras. By analysing the photometric flags in our catalogue, we found that about 20% of the stars with measured and verified variability are flagged as non-stellar sources, even when they are outside of the saturation and/or noise regimes. Additionally, we pair-matched our sample with the VIVA catalogue and found that more than half of our sources are missing from the VVV variability list, mostly due to observations with low signal-to-noise ratio or photometric problems with a low percentage due to failures in the selection process.Conclusions. Our results suggest that the current knowledge of the variability in the Galaxy is biased to nearby stars with low extinction. The present catalogue also provides the groundwork for characterising the results of future large variability surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time in the highly crowded and reddened regions of the Galactic plane, as well as follow-up campaigns for characterising specific types of variables. The analysis of the incorrectly flagged stars can be used to improve the photometric classification of the VVV data, allowing us to expand the amount of data considered useful for science purposes. In addition, we provide a list of stars that are missed by the VIVA procedures for which the observations are good and which were missed due to some failure in the VIVA selection process.