  Background: One of the most challenging keys to understand COVID-19 evolution
is to have a measure on those mild cases which are never tested because their
few symptoms are soft and/or fade away soon. The problem is not only that they
are difficult to identify and test, but also that it is believed that they may
constitute the bulk of the cases and could be crucial in the pandemic equation.
  Methods: We present a novel algorithm to extract the number of these mild
cases by correlating a COVID-line calls to reported cases in given districts.
The key assumption is to realize that, being a highly contagious disease, the
number of calls by mild cases should be proportional to the number of reported
cases. Whereas a background of calls not related to infected people should be
proportional to the district population.
  Results: We find that for Buenos Aires Province, in addition to the
background, there are in signal 6.6 +/- 0.4 calls per each reported COVID-19
case. Using this we estimate in Buenos Aires Province 20 +/- 2 COVID-19
symptomatic cases for each one reported.
  Conclusions: A very simple algorithm that models the COVID-line calls as sum
of signal plus background allows to estimate the crucial number of the rate of
symptomatic to reported COVID-19 cases in a given district. The result from
this method is an early and inexpensive estimate and should be contrasted to
other methods such as serology and/or massive testing.
