COVID-19 mild cases determination from correlating COVID-line calls to reported cases

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. We present a novel and simple algorithm to extract the number of these mild cases by correlating a COVID-line phone 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. We present the plain mathematics of the method and as a working example we apply it to Buenos Aires Province (Argentina), where it is being currently used. The implementation of this algorithm by other regions would be straightforward and would provide compelling information to the corresponding Health Care Administration.